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working on model Multimodal-middle-fusion-model-based-on-AlexNet with RANDOM
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]
Traceback (most recent call last):
File "/home/agaut/CS229-Project/experiments/experiment.py", line 168, in run_experiments
self.tester.test_model(curr_model)
File "/home/agaut/CS229-Project/test_framework/tester.py", line 144, in test_model
model.train(shuffled_x, shuffled_y)
File "/home/agaut/CS229-Project/models/multimodal/middle_fusion_model.py", line 229, in train
self.TRAINING_MINIBATCH_SIZE, verbose=self.train_verbose)
File "/home/agaut/CS229-Project/models/multimodal/middle_fusion_model.py", line 26, in train_model_given_numpy_arrays
dataloader = DataLoader(dataset,batch_size=batch_size,num_workers=0,shuffle=True)
File "/opt/conda/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 268, in __init__
sampler = RandomSampler(dataset, generator=generator)
File "/opt/conda/lib/python3.7/site-packages/torch/utils/data/sampler.py", line 103, in __init__
"value, but got num_samples={}".format(self.num_samples))
ValueError: num_samples should be a positive integer value, but got num_samples=0
Got exception num_samples should be a positive integer value, but got num_samples=0 for model RANDOM with stack trace:
None
working on model Multimodal-middle-fusion-model-based-on-AlexNet with MIN_MAX
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]
Traceback (most recent call last):
File "/home/agaut/CS229-Project/experiments/experiment.py", line 168, in run_experiments
self.tester.test_model(curr_model)
File "/home/agaut/CS229-Project/test_framework/tester.py", line 144, in test_model
model.train(shuffled_x, shuffled_y)
File "/home/agaut/CS229-Project/models/multimodal/middle_fusion_model.py", line 229, in train
self.TRAINING_MINIBATCH_SIZE, verbose=self.train_verbose)
File "/home/agaut/CS229-Project/models/multimodal/middle_fusion_model.py", line 26, in train_model_given_numpy_arrays
dataloader = DataLoader(dataset,batch_size=batch_size,num_workers=0,shuffle=True)
File "/opt/conda/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 268, in __init__
sampler = RandomSampler(dataset, generator=generator)
File "/opt/conda/lib/python3.7/site-packages/torch/utils/data/sampler.py", line 103, in __init__
"value, but got num_samples={}".format(self.num_samples))
ValueError: num_samples should be a positive integer value, but got num_samples=0
Got exception num_samples should be a positive integer value, but got num_samples=0 for model MIN_MAX with stack trace:
None
working on model Multimodal-middle-fusion-model-based-on-AlexNet with MIN_MARGIN
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]
Traceback (most recent call last):
File "/home/agaut/CS229-Project/experiments/experiment.py", line 168, in run_experiments
self.tester.test_model(curr_model)
File "/home/agaut/CS229-Project/test_framework/tester.py", line 144, in test_model
model.train(shuffled_x, shuffled_y)
File "/home/agaut/CS229-Project/models/multimodal/middle_fusion_model.py", line 229, in train
self.TRAINING_MINIBATCH_SIZE, verbose=self.train_verbose)
File "/home/agaut/CS229-Project/models/multimodal/middle_fusion_model.py", line 26, in train_model_given_numpy_arrays
dataloader = DataLoader(dataset,batch_size=batch_size,num_workers=0,shuffle=True)
File "/opt/conda/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 268, in __init__
sampler = RandomSampler(dataset, generator=generator)
File "/opt/conda/lib/python3.7/site-packages/torch/utils/data/sampler.py", line 103, in __init__
"value, but got num_samples={}".format(self.num_samples))
ValueError: num_samples should be a positive integer value, but got num_samples=0
Got exception num_samples should be a positive integer value, but got num_samples=0 for model MIN_MARGIN with stack trace:
None
working on model Multimodal-middle-fusion-model-based-on-AlexNet with MAX_ENTROPY
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]
Traceback (most recent call last):
File "/home/agaut/CS229-Project/experiments/experiment.py", line 168, in run_experiments
self.tester.test_model(curr_model)
File "/home/agaut/CS229-Project/test_framework/tester.py", line 144, in test_model
model.train(shuffled_x, shuffled_y)
File "/home/agaut/CS229-Project/models/multimodal/middle_fusion_model.py", line 229, in train
self.TRAINING_MINIBATCH_SIZE, verbose=self.train_verbose)
File "/home/agaut/CS229-Project/models/multimodal/middle_fusion_model.py", line 26, in train_model_given_numpy_arrays
dataloader = DataLoader(dataset,batch_size=batch_size,num_workers=0,shuffle=True)
File "/opt/conda/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 268, in __init__
sampler = RandomSampler(dataset, generator=generator)
File "/opt/conda/lib/python3.7/site-packages/torch/utils/data/sampler.py", line 103, in __init__
"value, but got num_samples={}".format(self.num_samples))
ValueError: num_samples should be a positive integer value, but got num_samples=0
Got exception num_samples should be a positive integer value, but got num_samples=0 for model MAX_ENTROPY with stack trace:
None
working on model Multimodal-middle-fusion-model-based-on-AlexNet with CLUSTER_MARGIN
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]
Traceback (most recent call last):
File "/home/agaut/CS229-Project/experiments/experiment.py", line 168, in run_experiments
self.tester.test_model(curr_model)
File "/home/agaut/CS229-Project/test_framework/tester.py", line 144, in test_model
model.train(shuffled_x, shuffled_y)
File "/home/agaut/CS229-Project/models/multimodal/middle_fusion_model.py", line 229, in train
self.TRAINING_MINIBATCH_SIZE, verbose=self.train_verbose)
File "/home/agaut/CS229-Project/models/multimodal/middle_fusion_model.py", line 26, in train_model_given_numpy_arrays
dataloader = DataLoader(dataset,batch_size=batch_size,num_workers=0,shuffle=True)
File "/opt/conda/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 268, in __init__
sampler = RandomSampler(dataset, generator=generator)
File "/opt/conda/lib/python3.7/site-packages/torch/utils/data/sampler.py", line 103, in __init__
"value, but got num_samples={}".format(self.num_samples))
ValueError: num_samples should be a positive integer value, but got num_samples=0
Got exception num_samples should be a positive integer value, but got num_samples=0 for model CLUSTER_MARGIN with stack trace:
None
working on model Multimodal-middle-fusion-model-based-on-AlexNet with BADGE
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]
Traceback (most recent call last):
File "/home/agaut/CS229-Project/experiments/experiment.py", line 168, in run_experiments
self.tester.test_model(curr_model)
File "/home/agaut/CS229-Project/test_framework/tester.py", line 144, in test_model
model.train(shuffled_x, shuffled_y)
File "/home/agaut/CS229-Project/models/multimodal/middle_fusion_model.py", line 229, in train
self.TRAINING_MINIBATCH_SIZE, verbose=self.train_verbose)
File "/home/agaut/CS229-Project/models/multimodal/middle_fusion_model.py", line 26, in train_model_given_numpy_arrays
dataloader = DataLoader(dataset,batch_size=batch_size,num_workers=0,shuffle=True)
File "/opt/conda/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 268, in __init__
sampler = RandomSampler(dataset, generator=generator)
File "/opt/conda/lib/python3.7/site-packages/torch/utils/data/sampler.py", line 103, in __init__
"value, but got num_samples={}".format(self.num_samples))
ValueError: num_samples should be a positive integer value, but got num_samples=0
Got exception num_samples should be a positive integer value, but got num_samples=0 for model BADGE with stack trace:
None
No handles with labels found to put in legend.
No handles with labels found to put in legend.
working on model Multimodal-late-fusion-model-based-on-AlexNet with RANDOM
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 0: Data size 0: : 10%|█ | 1/10 [00:00<00:05, 1.69it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 0: Data size 1: : 10%|█ | 1/10 [00:00<00:05, 1.69it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 0: Data size 1: : 10%|█ | 1/10 [00:01<00:05, 1.69it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 0: Data size 1: : 20%|██ | 2/10 [00:01<00:04, 1.79it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.79it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.79it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 30%|███ | 3/10 [00:01<00:03, 1.83it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 30%|███ | 3/10 [00:01<00:03, 1.83it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 30%|███ | 3/10 [00:02<00:03, 1.83it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 40%|████ | 4/10 [00:02<00:03, 1.86it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.86it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.86it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 50%|█████ | 5/10 [00:02<00:02, 1.87it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 50%|█████ | 5/10 [00:02<00:02, 1.87it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 50%|█████ | 5/10 [00:03<00:02, 1.87it/s, data_size=5, test_acc=0.25, train_acc=0.25]Test 0: Data size 5: : 60%|██████ | 6/10 [00:03<00:02, 1.88it/s, data_size=5, test_acc=0.25, train_acc=0.25]Test 0: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.88it/s, data_size=5, test_acc=0.25, train_acc=0.25]Test 0: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.88it/s, data_size=6, test_acc=0.25, train_acc=0.25]Test 0: Data size 6: : 70%|███████ | 7/10 [00:03<00:01, 1.88it/s, data_size=6, test_acc=0.25, train_acc=0.25]Test 0: Data size 7: : 70%|███████ | 7/10 [00:03<00:01, 1.88it/s, data_size=6, test_acc=0.25, train_acc=0.25]Test 0: Data size 7: : 70%|███████ | 7/10 [00:04<00:01, 1.88it/s, data_size=7, test_acc=0.25, train_acc=0.25]Test 0: Data size 7: : 80%|████████ | 8/10 [00:04<00:01, 1.88it/s, data_size=7, test_acc=0.25, train_acc=0.25]Test 0: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.88it/s, data_size=7, test_acc=0.25, train_acc=0.25]Test 0: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.88it/s, data_size=8, test_acc=0.25, train_acc=0.25]Test 0: Data size 8: : 90%|█████████ | 9/10 [00:04<00:00, 1.87it/s, data_size=8, test_acc=0.25, train_acc=0.25]Test 0: Data size 9: : 90%|█████████ | 9/10 [00:04<00:00, 1.87it/s, data_size=8, test_acc=0.25, train_acc=0.25]Test 0: Data size 9: : 90%|█████████ | 9/10 [00:05<00:00, 1.87it/s, data_size=9, test_acc=0.25, train_acc=0.25]Test 0: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.87it/s, data_size=9, test_acc=0.25, train_acc=0.25]Test 0: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.86it/s, data_size=9, test_acc=0.25, train_acc=0.25]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s, data_size=0, test_acc=0.179, train_acc=nan]Test 1: Data size 0: : 10%|█ | 1/10 [00:00<00:04, 1.88it/s, data_size=0, test_acc=0.179, train_acc=nan]Test 1: Data size 1: : 10%|█ | 1/10 [00:00<00:04, 1.88it/s, data_size=0, test_acc=0.179, train_acc=nan]Test 1: Data size 1: : 10%|█ | 1/10 [00:00<00:04, 1.88it/s, data_size=1, test_acc=0.179, train_acc=nan]Test 1: Data size 1: : 20%|██ | 2/10 [00:01<00:04, 1.88it/s, data_size=1, test_acc=0.179, train_acc=nan]Test 1: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.88it/s, data_size=1, test_acc=0.179, train_acc=nan]Test 1: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.88it/s, data_size=2, test_acc=0.179, train_acc=nan]Test 1: Data size 2: : 30%|███ | 3/10 [00:01<00:03, 1.88it/s, data_size=2, test_acc=0.179, train_acc=nan]Test 1: Data size 3: : 30%|███ | 3/10 [00:01<00:03, 1.88it/s, data_size=2, test_acc=0.179, train_acc=nan]Test 1: Data size 3: : 30%|███ | 3/10 [00:02<00:03, 1.88it/s, data_size=3, test_acc=0.179, train_acc=nan]Test 1: Data size 3: : 40%|████ | 4/10 [00:02<00:03, 1.87it/s, data_size=3, test_acc=0.179, train_acc=nan]Test 1: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.87it/s, data_size=3, test_acc=0.179, train_acc=nan]Test 1: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.87it/s, data_size=4, test_acc=0.179, train_acc=nan]Test 1: Data size 4: : 50%|█████ | 5/10 [00:02<00:02, 1.87it/s, data_size=4, test_acc=0.179, train_acc=nan]Test 1: Data size 5: : 50%|█████ | 5/10 [00:02<00:02, 1.87it/s, data_size=4, test_acc=0.179, train_acc=nan]Test 1: Data size 5: : 50%|█████ | 5/10 [00:03<00:02, 1.87it/s, data_size=5, test_acc=0.179, train_acc=0.25]Test 1: Data size 5: : 60%|██████ | 6/10 [00:03<00:02, 1.87it/s, data_size=5, test_acc=0.179, train_acc=0.25]Test 1: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.87it/s, data_size=5, test_acc=0.179, train_acc=0.25]Test 1: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.87it/s, data_size=6, test_acc=0.179, train_acc=0.25]Test 1: Data size 6: : 70%|███████ | 7/10 [00:03<00:01, 1.86it/s, data_size=6, test_acc=0.179, train_acc=0.25]Test 1: Data size 7: : 70%|███████ | 7/10 [00:03<00:01, 1.86it/s, data_size=6, test_acc=0.179, train_acc=0.25]Test 1: Data size 7: : 70%|███████ | 7/10 [00:04<00:01, 1.86it/s, data_size=7, test_acc=0.179, train_acc=0.25]Test 1: Data size 7: : 80%|████████ | 8/10 [00:04<00:01, 1.86it/s, data_size=7, test_acc=0.179, train_acc=0.25]Test 1: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.86it/s, data_size=7, test_acc=0.179, train_acc=0.25]Test 1: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.86it/s, data_size=8, test_acc=0.179, train_acc=0.25]Test 1: Data size 8: : 90%|█████████ | 9/10 [00:04<00:00, 1.85it/s, data_size=8, test_acc=0.179, train_acc=0.25]Test 1: Data size 9: : 90%|█████████ | 9/10 [00:04<00:00, 1.85it/s, data_size=8, test_acc=0.179, train_acc=0.25]Test 1: Data size 9: : 90%|█████████ | 9/10 [00:05<00:00, 1.85it/s, data_size=9, test_acc=0.179, train_acc=0.25]Test 1: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.84it/s, data_size=9, test_acc=0.179, train_acc=0.25]Test 1: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.86it/s, data_size=9, test_acc=0.179, train_acc=0.25]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 2: Data size 0: : 10%|█ | 1/10 [00:00<00:04, 1.87it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 2: Data size 1: : 10%|█ | 1/10 [00:00<00:04, 1.87it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 2: Data size 1: : 10%|█ | 1/10 [00:00<00:04, 1.87it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 2: Data size 1: : 20%|██ | 2/10 [00:01<00:04, 1.86it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 2: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.86it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 2: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.86it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 2: : 30%|███ | 3/10 [00:01<00:03, 1.83it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 30%|███ | 3/10 [00:01<00:03, 1.83it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 30%|███ | 3/10 [00:02<00:03, 1.83it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 40%|████ | 4/10 [00:02<00:03, 1.83it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.83it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.83it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 50%|█████ | 5/10 [00:02<00:02, 1.84it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 50%|█████ | 5/10 [00:02<00:02, 1.84it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 50%|█████ | 5/10 [00:03<00:02, 1.84it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 60%|██████ | 6/10 [00:03<00:02, 1.83it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.83it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.83it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 70%|███████ | 7/10 [00:03<00:01, 1.83it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 70%|███████ | 7/10 [00:03<00:01, 1.83it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 70%|███████ | 7/10 [00:04<00:01, 1.83it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 80%|████████ | 8/10 [00:04<00:01, 1.83it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 2: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.83it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 2: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.83it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 2: Data size 8: : 90%|█████████ | 9/10 [00:04<00:00, 1.83it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 2: Data size 9: : 90%|█████████ | 9/10 [00:04<00:00, 1.83it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 2: Data size 9: : 90%|█████████ | 9/10 [00:05<00:00, 1.83it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 2: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.83it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 2: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.83it/s, data_size=9, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 3: Data size 0: : 10%|█ | 1/10 [00:00<00:04, 1.83it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 3: Data size 1: : 10%|█ | 1/10 [00:00<00:04, 1.83it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 3: Data size 1: : 10%|█ | 1/10 [00:00<00:04, 1.83it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 3: Data size 1: : 20%|██ | 2/10 [00:01<00:04, 1.83it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 3: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.83it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 3: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.83it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 2: : 30%|███ | 3/10 [00:01<00:03, 1.81it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 30%|███ | 3/10 [00:01<00:03, 1.81it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 30%|███ | 3/10 [00:02<00:03, 1.81it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 40%|████ | 4/10 [00:02<00:03, 1.81it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.81it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.81it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 50%|█████ | 5/10 [00:02<00:02, 1.81it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 50%|█████ | 5/10 [00:02<00:02, 1.81it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 50%|█████ | 5/10 [00:03<00:02, 1.81it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 60%|██████ | 6/10 [00:03<00:02, 1.81it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.81it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.81it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 70%|███████ | 7/10 [00:03<00:01, 1.80it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 3: Data size 7: : 70%|███████ | 7/10 [00:03<00:01, 1.80it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 3: Data size 7: : 70%|███████ | 7/10 [00:04<00:01, 1.80it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 3: Data size 7: : 80%|████████ | 8/10 [00:04<00:01, 1.80it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 3: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.80it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 3: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.80it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 3: Data size 8: : 90%|█████████ | 9/10 [00:04<00:00, 1.80it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 3: Data size 9: : 90%|█████████ | 9/10 [00:04<00:00, 1.80it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 3: Data size 9: : 90%|█████████ | 9/10 [00:05<00:00, 1.80it/s, data_size=9, test_acc=0.25, train_acc=0.25]Test 3: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.79it/s, data_size=9, test_acc=0.25, train_acc=0.25]Test 3: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.80it/s, data_size=9, test_acc=0.25, train_acc=0.25]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 4: Data size 0: : 10%|█ | 1/10 [00:00<00:04, 1.88it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 4: Data size 1: : 10%|█ | 1/10 [00:00<00:04, 1.88it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 4: Data size 1: : 10%|█ | 1/10 [00:00<00:04, 1.88it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 4: Data size 1: : 20%|██ | 2/10 [00:01<00:04, 1.87it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.87it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.87it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 30%|███ | 3/10 [00:01<00:03, 1.87it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 30%|███ | 3/10 [00:01<00:03, 1.87it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 30%|███ | 3/10 [00:02<00:03, 1.87it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 40%|████ | 4/10 [00:02<00:03, 1.88it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.88it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.88it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 50%|█████ | 5/10 [00:02<00:02, 1.88it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 50%|█████ | 5/10 [00:02<00:02, 1.88it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 50%|█████ | 5/10 [00:03<00:02, 1.88it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 60%|██████ | 6/10 [00:03<00:02, 1.87it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.87it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.87it/s, data_size=6, test_acc=0.25, train_acc=0.25]Test 4: Data size 6: : 70%|███████ | 7/10 [00:03<00:01, 1.87it/s, data_size=6, test_acc=0.25, train_acc=0.25]Test 4: Data size 7: : 70%|███████ | 7/10 [00:03<00:01, 1.87it/s, data_size=6, test_acc=0.25, train_acc=0.25]Test 4: Data size 7: : 70%|███████ | 7/10 [00:04<00:01, 1.87it/s, data_size=7, test_acc=0.25, train_acc=0.25]Test 4: Data size 7: : 80%|████████ | 8/10 [00:04<00:01, 1.86it/s, data_size=7, test_acc=0.25, train_acc=0.25]Test 4: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.86it/s, data_size=7, test_acc=0.25, train_acc=0.25]Test 4: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.86it/s, data_size=8, test_acc=0.25, train_acc=0.25]Test 4: Data size 8: : 90%|█████████ | 9/10 [00:04<00:00, 1.85it/s, data_size=8, test_acc=0.25, train_acc=0.25]Test 4: Data size 9: : 90%|█████████ | 9/10 [00:04<00:00, 1.85it/s, data_size=8, test_acc=0.25, train_acc=0.25]Test 4: Data size 9: : 90%|█████████ | 9/10 [00:05<00:00, 1.85it/s, data_size=9, test_acc=0.25, train_acc=0.25]Test 4: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.85it/s, data_size=9, test_acc=0.25, train_acc=0.25]Test 4: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.86it/s, data_size=9, test_acc=0.25, train_acc=0.25]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 5: Data size 0: : 10%|█ | 1/10 [00:00<00:04, 1.85it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 5: Data size 1: : 10%|█ | 1/10 [00:00<00:04, 1.85it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 5: Data size 1: : 10%|█ | 1/10 [00:00<00:04, 1.85it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 5: Data size 1: : 20%|██ | 2/10 [00:01<00:04, 1.84it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 5: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.84it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 5: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.84it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 2: : 30%|███ | 3/10 [00:01<00:03, 1.84it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 30%|███ | 3/10 [00:01<00:03, 1.84it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 30%|███ | 3/10 [00:02<00:03, 1.84it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 40%|████ | 4/10 [00:02<00:03, 1.84it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.84it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.84it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 50%|█████ | 5/10 [00:02<00:02, 1.84it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 5: Data size 5: : 50%|█████ | 5/10 [00:02<00:02, 1.84it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 5: Data size 5: : 50%|█████ | 5/10 [00:03<00:02, 1.84it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 5: : 60%|██████ | 6/10 [00:03<00:02, 1.84it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.84it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.84it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 70%|███████ | 7/10 [00:03<00:01, 1.83it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 70%|███████ | 7/10 [00:03<00:01, 1.83it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 70%|███████ | 7/10 [00:04<00:01, 1.83it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 80%|████████ | 8/10 [00:04<00:01, 1.83it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 5: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.83it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 5: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.83it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 5: Data size 8: : 90%|█████████ | 9/10 [00:04<00:00, 1.82it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 5: Data size 9: : 90%|█████████ | 9/10 [00:04<00:00, 1.82it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 5: Data size 9: : 90%|█████████ | 9/10 [00:05<00:00, 1.82it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 5: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.82it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 5: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.83it/s, data_size=9, test_acc=0.25, train_acc=nan]
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0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 7: Data size 0: : 10%|█ | 1/10 [00:00<00:04, 1.90it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 7: Data size 1: : 10%|█ | 1/10 [00:00<00:04, 1.90it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 7: Data size 1: : 10%|█ | 1/10 [00:00<00:04, 1.90it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 7: Data size 1: : 20%|██ | 2/10 [00:01<00:04, 1.89it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 7: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.89it/s, data_size=1, test_acc=0.25, train_acc=nan]Test 7: Data size 2: : 20%|██ | 2/10 [00:01<00:04, 1.89it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 2: : 30%|███ | 3/10 [00:01<00:03, 1.89it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 30%|███ | 3/10 [00:01<00:03, 1.89it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 30%|███ | 3/10 [00:01<00:03, 1.89it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 40%|████ | 4/10 [00:02<00:03, 1.88it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.88it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 40%|████ | 4/10 [00:02<00:03, 1.88it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 50%|█████ | 5/10 [00:02<00:02, 1.88it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 50%|█████ | 5/10 [00:02<00:02, 1.88it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 50%|█████ | 5/10 [00:03<00:02, 1.88it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 60%|██████ | 6/10 [00:03<00:02, 1.88it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.88it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 60%|██████ | 6/10 [00:03<00:02, 1.88it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 70%|███████ | 7/10 [00:03<00:01, 1.88it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 70%|███████ | 7/10 [00:03<00:01, 1.88it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 70%|███████ | 7/10 [00:04<00:01, 1.88it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 80%|████████ | 8/10 [00:04<00:01, 1.88it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.88it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 80%|████████ | 8/10 [00:04<00:01, 1.88it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 90%|█████████ | 9/10 [00:04<00:00, 1.88it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 90%|█████████ | 9/10 [00:04<00:00, 1.88it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 90%|█████████ | 9/10 [00:05<00:00, 1.88it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.87it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 100%|██████████| 10/10 [00:05<00:00, 1.88it/s, data_size=9, test_acc=0.25, train_acc=nan]
working on model Multimodal-late-fusion-model-based-on-AlexNet with MIN_MAX
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 0: : 0%| | 0/10 [00:03<?, ?it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 0: Data size 0: : 10%|█ | 1/10 [00:04<00:37, 4.13s/it, data_size=0, test_acc=0.25, train_acc=nan]Test 0: Data size 1: : 10%|█ | 1/10 [00:04<00:37, 4.13s/it, data_size=0, test_acc=0.25, train_acc=nan]Test 0: Data size 1: : 10%|█ | 1/10 [00:08<00:37, 4.13s/it, data_size=1, test_acc=0.25, train_acc=nan]Test 0: Data size 1: : 20%|██ | 2/10 [00:08<00:32, 4.12s/it, data_size=1, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 20%|██ | 2/10 [00:08<00:32, 4.12s/it, data_size=1, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 20%|██ | 2/10 [00:12<00:32, 4.12s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 30%|███ | 3/10 [00:12<00:28, 4.11s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 30%|███ | 3/10 [00:12<00:28, 4.11s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 30%|███ | 3/10 [00:16<00:28, 4.11s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 40%|████ | 4/10 [00:16<00:24, 4.11s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 40%|████ | 4/10 [00:16<00:24, 4.11s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 40%|████ | 4/10 [00:20<00:24, 4.11s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 50%|█████ | 5/10 [00:20<00:20, 4.12s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 50%|█████ | 5/10 [00:20<00:20, 4.12s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 50%|█████ | 5/10 [00:24<00:20, 4.12s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 60%|██████ | 6/10 [00:24<00:16, 4.12s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 60%|██████ | 6/10 [00:24<00:16, 4.12s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 60%|██████ | 6/10 [00:28<00:16, 4.12s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 70%|███████ | 7/10 [00:28<00:12, 4.13s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 0: Data size 7: : 70%|███████ | 7/10 [00:28<00:12, 4.13s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 0: Data size 7: : 70%|███████ | 7/10 [00:32<00:12, 4.13s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 0: Data size 7: : 80%|████████ | 8/10 [00:32<00:08, 4.13s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 0: Data size 8: : 80%|████████ | 8/10 [00:32<00:08, 4.13s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 0: Data size 8: : 80%|████████ | 8/10 [00:36<00:08, 4.13s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 8: : 90%|█████████ | 9/10 [00:37<00:04, 4.13s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 90%|█████████ | 9/10 [00:37<00:04, 4.13s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 90%|█████████ | 9/10 [00:41<00:04, 4.13s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 100%|██████████| 10/10 [00:41<00:00, 4.12s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 100%|██████████| 10/10 [00:41<00:00, 4.12s/it, data_size=9, test_acc=0.25, train_acc=nan]
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0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 0: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 0: : 0%| | 0/10 [00:04<?, ?it/s, data_size=0, test_acc=0.25, train_acc=nan]Test 4: Data size 0: : 10%|█ | 1/10 [00:04<00:37, 4.18s/it, data_size=0, test_acc=0.25, train_acc=nan]Test 4: Data size 1: : 10%|█ | 1/10 [00:04<00:37, 4.18s/it, data_size=0, test_acc=0.25, train_acc=nan]Test 4: Data size 1: : 10%|█ | 1/10 [00:08<00:37, 4.18s/it, data_size=1, test_acc=0.25, train_acc=nan]Test 4: Data size 1: : 20%|██ | 2/10 [00:08<00:33, 4.18s/it, data_size=1, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 20%|██ | 2/10 [00:08<00:33, 4.18s/it, data_size=1, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 20%|██ | 2/10 [00:12<00:33, 4.18s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 30%|███ | 3/10 [00:12<00:29, 4.18s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 30%|███ | 3/10 [00:12<00:29, 4.18s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 30%|███ | 3/10 [00:16<00:29, 4.18s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 40%|████ | 4/10 [00:16<00:25, 4.18s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 40%|████ | 4/10 [00:16<00:25, 4.18s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 40%|████ | 4/10 [00:20<00:25, 4.18s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 50%|█████ | 5/10 [00:20<00:20, 4.18s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 50%|█████ | 5/10 [00:20<00:20, 4.18s/it, data_size=4, test_acc=0.25, train_acc=nan]working on model Multimodal-middle-fusion-model-based-on-AlexNet with RANDOM
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label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 0: Data size 2: : 0%| | 0/10 [00:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 10%|█ | 1/10 [00:06<00:56, 6.26s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:06<00:56, 6.26s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:12<00:56, 6.26s/it, data_size=3, test_acc=0.26, train_acc=nan]Test 0: Data size 3: : 20%|██ | 2/10 [00:12<00:50, 6.32s/it, data_size=3, test_acc=0.26, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:12<00:50, 6.32s/it, data_size=3, test_acc=0.26, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:18<00:50, 6.32s/it, data_size=4, test_acc=0.486, train_acc=nan]Test 0: Data size 4: : 30%|███ | 3/10 [00:19<00:44, 6.38s/it, data_size=4, test_acc=0.486, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:19<00:44, 6.38s/it, data_size=4, test_acc=0.486, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:25<00:44, 6.38s/it, data_size=5, test_acc=0.397, train_acc=nan]Test 0: Data size 5: : 40%|████ | 4/10 [00:25<00:38, 6.43s/it, data_size=5, test_acc=0.397, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:25<00:38, 6.43s/it, data_size=5, test_acc=0.397, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:32<00:38, 6.43s/it, data_size=6, test_acc=0.5, train_acc=0.5] Test 0: Data size 6: : 50%|█████ | 5/10 [00:32<00:32, 6.50s/it, data_size=6, test_acc=0.5, train_acc=0.5]Test 0: Data size 7: : 50%|█████ | 5/10 [00:32<00:32, 6.50s/it, data_size=6, test_acc=0.5, train_acc=0.5]Test 0: Data size 7: : 50%|█████ | 5/10 [00:38<00:32, 6.50s/it, data_size=7, test_acc=0.5, train_acc=0.5]Test 0: Data size 7: : 60%|██████ | 6/10 [00:38<00:26, 6.59s/it, data_size=7, test_acc=0.5, train_acc=0.5]Test 0: Data size 8: : 60%|██████ | 6/10 [00:38<00:26, 6.59s/it, data_size=7, test_acc=0.5, train_acc=0.5]Test 0: Data size 8: : 60%|██████ | 6/10 [00:45<00:26, 6.59s/it, data_size=8, test_acc=0.5, train_acc=0.5]Test 0: Data size 8: : 70%|███████ | 7/10 [00:45<00:19, 6.65s/it, data_size=8, test_acc=0.5, train_acc=0.5]Test 0: Data size 9: : 70%|███████ | 7/10 [00:45<00:19, 6.65s/it, data_size=8, test_acc=0.5, train_acc=0.5]Test 0: Data size 9: : 70%|███████ | 7/10 [00:52<00:19, 6.65s/it, data_size=9, test_acc=0.641, train_acc=0.75]Test 0: Data size 9: : 80%|████████ | 8/10 [00:52<00:13, 6.78s/it, data_size=9, test_acc=0.641, train_acc=0.75]Test 0: Data size 10: : 80%|████████ | 8/10 [00:52<00:13, 6.78s/it, data_size=9, test_acc=0.641, train_acc=0.75]Test 0: Data size 10: : 80%|████████ | 8/10 [01:00<00:13, 6.78s/it, data_size=10, test_acc=0.646, train_acc=0.75]Test 0: Data size 10: : 90%|█████████ | 9/10 [01:00<00:06, 6.98s/it, data_size=10, test_acc=0.646, train_acc=0.75]Test 0: Data size 11: : 90%|█████████ | 9/10 [01:00<00:06, 6.98s/it, data_size=10, test_acc=0.646, train_acc=0.75]Test 0: Data size 11: : 90%|█████████ | 9/10 [01:07<00:06, 6.98s/it, data_size=11, test_acc=0.6, train_acc=0.75] Test 0: Data size 11: : 100%|██████████| 10/10 [01:07<00:00, 7.04s/it, data_size=11, test_acc=0.6, train_acc=0.75]Test 0: Data size 11: : 100%|██████████| 10/10 [01:07<00:00, 6.74s/it, data_size=11, test_acc=0.6, train_acc=0.75]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 2: : 10%|█ | 1/10 [00:06<00:57, 6.40s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:06<00:57, 6.40s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:12<00:57, 6.40s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 20%|██ | 2/10 [00:12<00:51, 6.39s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:12<00:51, 6.39s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:19<00:51, 6.39s/it, data_size=4, test_acc=0.459, train_acc=nan]Test 1: Data size 4: : 30%|███ | 3/10 [00:19<00:45, 6.45s/it, data_size=4, test_acc=0.459, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:19<00:45, 6.45s/it, data_size=4, test_acc=0.459, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:25<00:45, 6.45s/it, data_size=5, test_acc=0.25, train_acc=nan] Test 1: Data size 5: : 40%|████ | 4/10 [00:25<00:39, 6.50s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:25<00:39, 6.50s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:32<00:39, 6.50s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 50%|█████ | 5/10 [00:32<00:33, 6.60s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:32<00:33, 6.60s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:39<00:33, 6.60s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 1: Data size 7: : 60%|██████ | 6/10 [00:39<00:26, 6.66s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 1: Data size 8: : 60%|██████ | 6/10 [00:39<00:26, 6.66s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 1: Data size 8: : 60%|██████ | 6/10 [00:46<00:26, 6.66s/it, data_size=8, test_acc=0.492, train_acc=0.5]Test 1: Data size 8: : 70%|███████ | 7/10 [00:46<00:20, 6.75s/it, data_size=8, test_acc=0.492, train_acc=0.5]Test 1: Data size 9: : 70%|███████ | 7/10 [00:46<00:20, 6.75s/it, data_size=8, test_acc=0.492, train_acc=0.5]Test 1: Data size 9: : 70%|███████ | 7/10 [00:53<00:20, 6.75s/it, data_size=9, test_acc=0.489, train_acc=0.5]Test 1: Data size 9: : 80%|████████ | 8/10 [00:53<00:13, 6.87s/it, data_size=9, test_acc=0.489, train_acc=0.5]Test 1: Data size 10: : 80%|████████ | 8/10 [00:53<00:13, 6.87s/it, data_size=9, test_acc=0.489, train_acc=0.5]Test 1: Data size 10: : 80%|████████ | 8/10 [01:00<00:13, 6.87s/it, data_size=10, test_acc=0.559, train_acc=0.75]Test 1: Data size 10: : 90%|█████████ | 9/10 [01:00<00:06, 6.96s/it, data_size=10, test_acc=0.559, train_acc=0.75]Test 1: Data size 11: : 90%|█████████ | 9/10 [01:00<00:06, 6.96s/it, data_size=10, test_acc=0.559, train_acc=0.75]Test 1: Data size 11: : 90%|█████████ | 9/10 [01:07<00:06, 6.96s/it, data_size=11, test_acc=0.561, train_acc=0.75]Test 1: Data size 11: : 100%|██████████| 10/10 [01:07<00:00, 7.07s/it, data_size=11, test_acc=0.561, train_acc=0.75]Test 1: Data size 11: : 100%|██████████| 10/10 [01:07<00:00, 6.80s/it, data_size=11, test_acc=0.561, train_acc=0.75]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 2: : 10%|█ | 1/10 [00:06<00:57, 6.37s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:06<00:57, 6.37s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:12<00:57, 6.37s/it, data_size=3, test_acc=0.441, train_acc=nan]Test 2: Data size 3: : 20%|██ | 2/10 [00:12<00:51, 6.41s/it, data_size=3, test_acc=0.441, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:12<00:51, 6.41s/it, data_size=3, test_acc=0.441, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:19<00:51, 6.41s/it, data_size=4, test_acc=0.25, train_acc=nan] Test 2: Data size 4: : 30%|███ | 3/10 [00:19<00:45, 6.45s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:19<00:45, 6.45s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:25<00:45, 6.45s/it, data_size=5, test_acc=0.25, train_acc=0.25]Test 2: Data size 5: : 40%|████ | 4/10 [00:25<00:39, 6.52s/it, data_size=5, test_acc=0.25, train_acc=0.25]Test 2: Data size 6: : 40%|████ | 4/10 [00:25<00:39, 6.52s/it, data_size=5, test_acc=0.25, train_acc=0.25]Test 2: Data size 6: : 40%|████ | 4/10 [00:32<00:39, 6.52s/it, data_size=6, test_acc=0.482, train_acc=0.5]Test 2: Data size 6: : 50%|█████ | 5/10 [00:32<00:32, 6.57s/it, data_size=6, test_acc=0.482, train_acc=0.5]Test 2: Data size 7: : 50%|█████ | 5/10 [00:32<00:32, 6.57s/it, data_size=6, test_acc=0.482, train_acc=0.5]Test 2: Data size 7: : 50%|█████ | 5/10 [00:39<00:32, 6.57s/it, data_size=7, test_acc=0.503, train_acc=0.5]Test 2: Data size 7: : 60%|██████ | 6/10 [00:39<00:26, 6.63s/it, data_size=7, test_acc=0.503, train_acc=0.5]Test 2: Data size 8: : 60%|██████ | 6/10 [00:39<00:26, 6.63s/it, data_size=7, test_acc=0.503, train_acc=0.5]Test 2: Data size 8: : 60%|██████ | 6/10 [00:46<00:26, 6.63s/it, data_size=8, test_acc=0.699, train_acc=0.75]Test 2: Data size 8: : 70%|███████ | 7/10 [00:46<00:20, 6.69s/it, data_size=8, test_acc=0.699, train_acc=0.75]Test 2: Data size 9: : 70%|███████ | 7/10 [00:46<00:20, 6.69s/it, data_size=8, test_acc=0.699, train_acc=0.75]Test 2: Data size 9: : 70%|███████ | 7/10 [00:53<00:20, 6.69s/it, data_size=9, test_acc=0.7, train_acc=0.75] Test 2: Data size 9: : 80%|████████ | 8/10 [00:53<00:13, 6.81s/it, data_size=9, test_acc=0.7, train_acc=0.75]Test 2: Data size 10: : 80%|████████ | 8/10 [00:53<00:13, 6.81s/it, data_size=9, test_acc=0.7, train_acc=0.75]Test 2: Data size 10: : 80%|████████ | 8/10 [01:00<00:13, 6.81s/it, data_size=10, test_acc=0.672, train_acc=0.75]Test 2: Data size 10: : 90%|█████████ | 9/10 [01:00<00:06, 6.94s/it, data_size=10, test_acc=0.672, train_acc=0.75]Test 2: Data size 11: : 90%|█████████ | 9/10 [01:00<00:06, 6.94s/it, data_size=10, test_acc=0.672, train_acc=0.75]Test 2: Data size 11: : 90%|█████████ | 9/10 [01:07<00:06, 6.94s/it, data_size=11, test_acc=0.654, train_acc=0.75]Test 2: Data size 11: : 100%|██████████| 10/10 [01:07<00:00, 7.05s/it, data_size=11, test_acc=0.654, train_acc=0.75]Test 2: Data size 11: : 100%|██████████| 10/10 [01:07<00:00, 6.78s/it, data_size=11, test_acc=0.654, train_acc=0.75]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:06<?, ?it/s, data_size=2, test_acc=0.344, train_acc=nan]Test 3: Data size 2: : 10%|█ | 1/10 [00:06<00:57, 6.41s/it, data_size=2, test_acc=0.344, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:06<00:57, 6.41s/it, data_size=2, test_acc=0.344, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:12<00:57, 6.41s/it, data_size=3, test_acc=0.415, train_acc=nan]Test 3: Data size 3: : 20%|██ | 2/10 [00:12<00:51, 6.38s/it, data_size=3, test_acc=0.415, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:12<00:51, 6.38s/it, data_size=3, test_acc=0.415, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:19<00:51, 6.38s/it, data_size=4, test_acc=0.693, train_acc=nan]Test 3: Data size 4: : 30%|███ | 3/10 [00:19<00:45, 6.46s/it, data_size=4, test_acc=0.693, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:19<00:45, 6.46s/it, data_size=4, test_acc=0.693, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:25<00:45, 6.46s/it, data_size=5, test_acc=0.421, train_acc=nan]Test 3: Data size 5: : 40%|████ | 4/10 [00:25<00:39, 6.53s/it, data_size=5, test_acc=0.421, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [00:25<00:39, 6.53s/it, data_size=5, test_acc=0.421, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [00:32<00:39, 6.53s/it, data_size=6, test_acc=0.628, train_acc=0.75]Test 3: Data size 6: : 50%|█████ | 5/10 [00:32<00:33, 6.60s/it, data_size=6, test_acc=0.628, train_acc=0.75]Test 3: Data size 7: : 50%|█████ | 5/10 [00:32<00:33, 6.60s/it, data_size=6, test_acc=0.628, train_acc=0.75]Test 3: Data size 7: : 50%|█████ | 5/10 [00:39<00:33, 6.60s/it, data_size=7, test_acc=0.546, train_acc=0.75]Test 3: Data size 7: : 60%|██████ | 6/10 [00:39<00:26, 6.67s/it, data_size=7, test_acc=0.546, train_acc=0.75]Test 3: Data size 8: : 60%|██████ | 6/10 [00:39<00:26, 6.67s/it, data_size=7, test_acc=0.546, train_acc=0.75]Test 3: Data size 8: : 60%|██████ | 6/10 [00:46<00:26, 6.67s/it, data_size=8, test_acc=0.614, train_acc=0.75]Test 3: Data size 8: : 70%|███████ | 7/10 [00:46<00:20, 6.73s/it, data_size=8, test_acc=0.614, train_acc=0.75]Test 3: Data size 9: : 70%|███████ | 7/10 [00:46<00:20, 6.73s/it, data_size=8, test_acc=0.614, train_acc=0.75]Test 3: Data size 9: : 70%|███████ | 7/10 [00:53<00:20, 6.73s/it, data_size=9, test_acc=0.609, train_acc=0.75]Test 3: Data size 9: : 80%|████████ | 8/10 [00:53<00:13, 6.84s/it, data_size=9, test_acc=0.609, train_acc=0.75]Test 3: Data size 10: : 80%|████████ | 8/10 [00:53<00:13, 6.84s/it, data_size=9, test_acc=0.609, train_acc=0.75]Test 3: Data size 10: : 80%|████████ | 8/10 [01:00<00:13, 6.84s/it, data_size=10, test_acc=0.673, train_acc=0.75]Test 3: Data size 10: : 90%|█████████ | 9/10 [01:00<00:06, 6.92s/it, data_size=10, test_acc=0.673, train_acc=0.75]Test 3: Data size 11: : 90%|█████████ | 9/10 [01:00<00:06, 6.92s/it, data_size=10, test_acc=0.673, train_acc=0.75]Test 3: Data size 11: : 90%|█████████ | 9/10 [01:07<00:06, 6.92s/it, data_size=11, test_acc=0.607, train_acc=0.5] Test 3: Data size 11: : 100%|██████████| 10/10 [01:07<00:00, 7.02s/it, data_size=11, test_acc=0.607, train_acc=0.5]Test 3: Data size 11: : 100%|██████████| 10/10 [01:07<00:00, 6.78s/it, data_size=11, test_acc=0.607, train_acc=0.5]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 10%|█ | 1/10 [00:06<00:57, 6.38s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:06<00:57, 6.38s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:12<00:57, 6.38s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 20%|██ | 2/10 [00:12<00:51, 6.41s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:12<00:51, 6.41s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:19<00:51, 6.41s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 30%|███ | 3/10 [00:19<00:45, 6.44s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:19<00:45, 6.44s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:25<00:45, 6.44s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 40%|████ | 4/10 [00:25<00:39, 6.51s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:25<00:39, 6.51s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:32<00:39, 6.51s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 50%|█████ | 5/10 [00:32<00:32, 6.56s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:32<00:32, 6.56s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:39<00:32, 6.56s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 60%|██████ | 6/10 [00:39<00:26, 6.62s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:39<00:26, 6.62s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:45<00:26, 6.62s/it, data_size=8, test_acc=0.252, train_acc=nan]Test 4: Data size 8: : 70%|███████ | 7/10 [00:46<00:19, 6.67s/it, data_size=8, test_acc=0.252, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:46<00:19, 6.67s/it, data_size=8, test_acc=0.252, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:52<00:19, 6.67s/it, data_size=9, test_acc=0.498, train_acc=nan]Test 4: Data size 9: : 80%|████████ | 8/10 [00:53<00:13, 6.77s/it, data_size=9, test_acc=0.498, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [00:53<00:13, 6.77s/it, data_size=9, test_acc=0.498, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [01:00<00:13, 6.77s/it, data_size=10, test_acc=0.503, train_acc=nan]Test 4: Data size 10: : 90%|█████████ | 9/10 [01:00<00:06, 6.91s/it, data_size=10, test_acc=0.503, train_acc=nan]Test 4: Data size 11: : 90%|█████████ | 9/10 [01:00<00:06, 6.91s/it, data_size=10, test_acc=0.503, train_acc=nan]Test 4: Data size 11: : 90%|█████████ | 9/10 [01:07<00:06, 6.91s/it, data_size=11, test_acc=0.682, train_acc=nan]Test 4: Data size 11: : 100%|██████████| 10/10 [01:07<00:00, 7.01s/it, data_size=11, test_acc=0.682, train_acc=nan]Test 4: Data size 11: : 100%|██████████| 10/10 [01:07<00:00, 6.75s/it, data_size=11, test_acc=0.682, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 2: : 10%|█ | 1/10 [00:06<00:56, 6.28s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:06<00:56, 6.28s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:12<00:56, 6.28s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 20%|██ | 2/10 [00:12<00:50, 6.32s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:12<00:50, 6.32s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:18<00:50, 6.32s/it, data_size=4, test_acc=0.248, train_acc=nan]Test 5: Data size 4: : 30%|███ | 3/10 [00:18<00:44, 6.34s/it, data_size=4, test_acc=0.248, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:18<00:44, 6.34s/it, data_size=4, test_acc=0.248, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:25<00:44, 6.34s/it, data_size=5, test_acc=0.25, train_acc=nan] Test 5: Data size 5: : 40%|████ | 4/10 [00:25<00:38, 6.40s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:25<00:38, 6.40s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:31<00:38, 6.40s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 50%|█████ | 5/10 [00:32<00:32, 6.45s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:32<00:32, 6.45s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:38<00:32, 6.45s/it, data_size=7, test_acc=0.289, train_acc=nan]Test 5: Data size 7: : 60%|██████ | 6/10 [00:38<00:25, 6.46s/it, data_size=7, test_acc=0.289, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [00:38<00:25, 6.46s/it, data_size=7, test_acc=0.289, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [00:44<00:25, 6.46s/it, data_size=8, test_acc=0.304, train_acc=0.5]Test 5: Data size 8: : 70%|███████ | 7/10 [00:45<00:19, 6.48s/it, data_size=8, test_acc=0.304, train_acc=0.5]Test 5: Data size 9: : 70%|███████ | 7/10 [00:45<00:19, 6.48s/it, data_size=8, test_acc=0.304, train_acc=0.5]Test 5: Data size 9: : 70%|███████ | 7/10 [00:51<00:19, 6.48s/it, data_size=9, test_acc=0.304, train_acc=0.5]Test 5: Data size 9: : 80%|████████ | 8/10 [00:51<00:13, 6.59s/it, data_size=9, test_acc=0.304, train_acc=0.5]Test 5: Data size 10: : 80%|████████ | 8/10 [00:51<00:13, 6.59s/it, data_size=9, test_acc=0.304, train_acc=0.5]Test 5: Data size 10: : 80%|████████ | 8/10 [00:58<00:13, 6.59s/it, data_size=10, test_acc=0.469, train_acc=0.75]Test 5: Data size 10: : 90%|█████████ | 9/10 [00:58<00:06, 6.70s/it, data_size=10, test_acc=0.469, train_acc=0.75]Test 5: Data size 11: : 90%|█████████ | 9/10 [00:58<00:06, 6.70s/it, data_size=10, test_acc=0.469, train_acc=0.75]Test 5: Data size 11: : 90%|█████████ | 9/10 [01:05<00:06, 6.70s/it, data_size=11, test_acc=0.568, train_acc=0.75]Test 5: Data size 11: : 100%|██████████| 10/10 [01:05<00:00, 6.78s/it, data_size=11, test_acc=0.568, train_acc=0.75]Test 5: Data size 11: : 100%|██████████| 10/10 [01:05<00:00, 6.58s/it, data_size=11, test_acc=0.568, train_acc=0.75]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 2: : 10%|█ | 1/10 [00:06<00:55, 6.20s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:06<00:55, 6.20s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:12<00:55, 6.20s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 20%|██ | 2/10 [00:12<00:49, 6.20s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:12<00:49, 6.20s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:18<00:49, 6.20s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 30%|███ | 3/10 [00:18<00:43, 6.22s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:18<00:43, 6.22s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:24<00:43, 6.22s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 40%|████ | 4/10 [00:24<00:37, 6.27s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:24<00:37, 6.27s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:31<00:37, 6.27s/it, data_size=6, test_acc=0.395, train_acc=0.25]Test 6: Data size 6: : 50%|█████ | 5/10 [00:31<00:31, 6.29s/it, data_size=6, test_acc=0.395, train_acc=0.25]Test 6: Data size 7: : 50%|█████ | 5/10 [00:31<00:31, 6.29s/it, data_size=6, test_acc=0.395, train_acc=0.25]Test 6: Data size 7: : 50%|█████ | 5/10 [00:37<00:31, 6.29s/it, data_size=7, test_acc=0.25, train_acc=0.25] Test 6: Data size 7: : 60%|██████ | 6/10 [00:37<00:25, 6.31s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 6: Data size 8: : 60%|██████ | 6/10 [00:37<00:25, 6.31s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 6: Data size 8: : 60%|██████ | 6/10 [00:44<00:25, 6.31s/it, data_size=8, test_acc=0.416, train_acc=0.25]Test 6: Data size 8: : 70%|███████ | 7/10 [00:44<00:19, 6.37s/it, data_size=8, test_acc=0.416, train_acc=0.25]Test 6: Data size 9: : 70%|███████ | 7/10 [00:44<00:19, 6.37s/it, data_size=8, test_acc=0.416, train_acc=0.25]Test 6: Data size 9: : 70%|███████ | 7/10 [00:50<00:19, 6.37s/it, data_size=9, test_acc=0.406, train_acc=0.25]Test 6: Data size 9: : 80%|████████ | 8/10 [00:50<00:12, 6.47s/it, data_size=9, test_acc=0.406, train_acc=0.25]Test 6: Data size 10: : 80%|████████ | 8/10 [00:50<00:12, 6.47s/it, data_size=9, test_acc=0.406, train_acc=0.25]Test 6: Data size 10: : 80%|████████ | 8/10 [00:57<00:12, 6.47s/it, data_size=10, test_acc=0.525, train_acc=0.625]Test 6: Data size 10: : 90%|█████████ | 9/10 [00:57<00:06, 6.56s/it, data_size=10, test_acc=0.525, train_acc=0.625]Test 6: Data size 11: : 90%|█████████ | 9/10 [00:57<00:06, 6.56s/it, data_size=10, test_acc=0.525, train_acc=0.625]Test 6: Data size 11: : 90%|█████████ | 9/10 [01:04<00:06, 6.56s/it, data_size=11, test_acc=0.615, train_acc=0.667]Test 6: Data size 11: : 100%|██████████| 10/10 [01:04<00:00, 6.65s/it, data_size=11, test_acc=0.615, train_acc=0.667]Test 6: Data size 11: : 100%|██████████| 10/10 [01:04<00:00, 6.45s/it, data_size=11, test_acc=0.615, train_acc=0.667]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 2: : 10%|█ | 1/10 [00:06<00:55, 6.18s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:06<00:55, 6.18s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:12<00:55, 6.18s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 20%|██ | 2/10 [00:12<00:49, 6.21s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:12<00:49, 6.21s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:18<00:49, 6.21s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 30%|███ | 3/10 [00:18<00:43, 6.28s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:18<00:43, 6.28s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:25<00:43, 6.28s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 40%|████ | 4/10 [00:25<00:37, 6.32s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [00:25<00:37, 6.32s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [00:31<00:37, 6.32s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 50%|█████ | 5/10 [00:31<00:31, 6.39s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [00:31<00:31, 6.39s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [00:38<00:31, 6.39s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 60%|██████ | 6/10 [00:38<00:25, 6.46s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 60%|██████ | 6/10 [00:38<00:25, 6.46s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 60%|██████ | 6/10 [00:44<00:25, 6.46s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 70%|███████ | 7/10 [00:44<00:19, 6.50s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 70%|███████ | 7/10 [00:44<00:19, 6.50s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 70%|███████ | 7/10 [00:51<00:19, 6.50s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 80%|████████ | 8/10 [00:51<00:13, 6.62s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 10: : 80%|████████ | 8/10 [00:51<00:13, 6.62s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 10: : 80%|████████ | 8/10 [00:58<00:13, 6.62s/it, data_size=10, test_acc=0.371, train_acc=nan]Test 7: Data size 10: : 90%|█████████ | 9/10 [00:58<00:06, 6.73s/it, data_size=10, test_acc=0.371, train_acc=nan]Test 7: Data size 11: : 90%|█████████ | 9/10 [00:58<00:06, 6.73s/it, data_size=10, test_acc=0.371, train_acc=nan]Test 7: Data size 11: : 90%|█████████ | 9/10 [01:05<00:06, 6.73s/it, data_size=11, test_acc=0.315, train_acc=nan]Test 7: Data size 11: : 100%|██████████| 10/10 [01:05<00:00, 6.82s/it, data_size=11, test_acc=0.315, train_acc=nan]Test 7: Data size 11: : 100%|██████████| 10/10 [01:05<00:00, 6.57s/it, data_size=11, test_acc=0.315, train_acc=nan]
working on model Multimodal-middle-fusion-model-based-on-AlexNet with MIN_MAX
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.99s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.99s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:12<00:53, 5.99s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 20%|██ | 2/10 [00:12<00:48, 6.08s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:12<00:48, 6.08s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:18<00:48, 6.08s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.14s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.14s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.14s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 40%|████ | 4/10 [00:24<00:37, 6.18s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:24<00:37, 6.18s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:30<00:37, 6.18s/it, data_size=6, test_acc=0.38, train_acc=nan]Test 0: Data size 6: : 50%|█████ | 5/10 [00:30<00:31, 6.25s/it, data_size=6, test_acc=0.38, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [00:30<00:31, 6.25s/it, data_size=6, test_acc=0.38, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [00:37<00:31, 6.25s/it, data_size=7, test_acc=0.474, train_acc=nan]Test 0: Data size 7: : 60%|██████ | 6/10 [00:37<00:25, 6.30s/it, data_size=7, test_acc=0.474, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [00:37<00:25, 6.30s/it, data_size=7, test_acc=0.474, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [00:43<00:25, 6.30s/it, data_size=8, test_acc=0.332, train_acc=nan]Test 0: Data size 8: : 70%|███████ | 7/10 [00:43<00:19, 6.38s/it, data_size=8, test_acc=0.332, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [00:43<00:19, 6.38s/it, data_size=8, test_acc=0.332, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [00:50<00:19, 6.38s/it, data_size=9, test_acc=0.327, train_acc=nan]Test 0: Data size 9: : 80%|████████ | 8/10 [00:50<00:13, 6.50s/it, data_size=9, test_acc=0.327, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [00:50<00:13, 6.50s/it, data_size=9, test_acc=0.327, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [00:57<00:13, 6.50s/it, data_size=10, test_acc=0.423, train_acc=nan]Test 0: Data size 10: : 90%|█████████ | 9/10 [00:57<00:06, 6.61s/it, data_size=10, test_acc=0.423, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [00:57<00:06, 6.61s/it, data_size=10, test_acc=0.423, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [01:04<00:06, 6.61s/it, data_size=11, test_acc=0.588, train_acc=nan]Test 0: Data size 11: : 100%|██████████| 10/10 [01:04<00:00, 6.73s/it, data_size=11, test_acc=0.588, train_acc=nan]Test 0: Data size 11: : 100%|██████████| 10/10 [01:04<00:00, 6.45s/it, data_size=11, test_acc=0.588, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 2: : 10%|█ | 1/10 [00:06<00:55, 6.18s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:06<00:55, 6.18s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:12<00:55, 6.18s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 20%|██ | 2/10 [00:12<00:49, 6.22s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:12<00:49, 6.22s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:18<00:49, 6.22s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 30%|███ | 3/10 [00:18<00:43, 6.28s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:18<00:43, 6.28s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:25<00:43, 6.28s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 40%|████ | 4/10 [00:25<00:37, 6.33s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:25<00:37, 6.33s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:31<00:37, 6.33s/it, data_size=6, test_acc=0.406, train_acc=nan]Test 1: Data size 6: : 50%|█████ | 5/10 [00:31<00:31, 6.39s/it, data_size=6, test_acc=0.406, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:31<00:31, 6.39s/it, data_size=6, test_acc=0.406, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:38<00:31, 6.39s/it, data_size=7, test_acc=0.495, train_acc=nan]Test 1: Data size 7: : 60%|██████ | 6/10 [00:38<00:25, 6.47s/it, data_size=7, test_acc=0.495, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [00:38<00:25, 6.47s/it, data_size=7, test_acc=0.495, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [00:44<00:25, 6.47s/it, data_size=8, test_acc=0.369, train_acc=nan]Test 1: Data size 8: : 70%|███████ | 7/10 [00:44<00:19, 6.52s/it, data_size=8, test_acc=0.369, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [00:44<00:19, 6.52s/it, data_size=8, test_acc=0.369, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [00:51<00:19, 6.52s/it, data_size=9, test_acc=0.25, train_acc=nan] Test 1: Data size 9: : 80%|████████ | 8/10 [00:51<00:13, 6.62s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 80%|████████ | 8/10 [00:51<00:13, 6.62s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 80%|████████ | 8/10 [00:58<00:13, 6.62s/it, data_size=10, test_acc=0.369, train_acc=nan]Test 1: Data size 10: : 90%|█████████ | 9/10 [00:58<00:06, 6.71s/it, data_size=10, test_acc=0.369, train_acc=nan]Test 1: Data size 11: : 90%|█████████ | 9/10 [00:58<00:06, 6.71s/it, data_size=10, test_acc=0.369, train_acc=nan]Test 1: Data size 11: : 90%|█████████ | 9/10 [01:05<00:06, 6.71s/it, data_size=11, test_acc=0.586, train_acc=nan]Test 1: Data size 11: : 100%|██████████| 10/10 [01:05<00:00, 6.81s/it, data_size=11, test_acc=0.586, train_acc=nan]Test 1: Data size 11: : 100%|██████████| 10/10 [01:05<00:00, 6.57s/it, data_size=11, test_acc=0.586, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 2: : 10%|█ | 1/10 [00:06<00:55, 6.19s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:06<00:55, 6.19s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:12<00:55, 6.19s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 20%|██ | 2/10 [00:12<00:49, 6.23s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:12<00:49, 6.23s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:18<00:49, 6.23s/it, data_size=4, test_acc=0.404, train_acc=nan]Test 2: Data size 4: : 30%|███ | 3/10 [00:18<00:44, 6.29s/it, data_size=4, test_acc=0.404, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:18<00:44, 6.29s/it, data_size=4, test_acc=0.404, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:25<00:44, 6.29s/it, data_size=5, test_acc=0.295, train_acc=nan]Test 2: Data size 5: : 40%|████ | 4/10 [00:25<00:38, 6.36s/it, data_size=5, test_acc=0.295, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:25<00:38, 6.36s/it, data_size=5, test_acc=0.295, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:31<00:38, 6.36s/it, data_size=6, test_acc=0.307, train_acc=nan]Test 2: Data size 6: : 50%|█████ | 5/10 [00:31<00:32, 6.44s/it, data_size=6, test_acc=0.307, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [00:31<00:32, 6.44s/it, data_size=6, test_acc=0.307, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [00:38<00:32, 6.44s/it, data_size=7, test_acc=0.619, train_acc=nan]Test 2: Data size 7: : 60%|██████ | 6/10 [00:38<00:25, 6.49s/it, data_size=7, test_acc=0.619, train_acc=nan]Test 2: Data size 8: : 60%|██████ | 6/10 [00:38<00:25, 6.49s/it, data_size=7, test_acc=0.619, train_acc=nan]Test 2: Data size 8: : 60%|██████ | 6/10 [00:45<00:25, 6.49s/it, data_size=8, test_acc=0.491, train_acc=nan]Test 2: Data size 8: : 70%|███████ | 7/10 [00:45<00:19, 6.57s/it, data_size=8, test_acc=0.491, train_acc=nan]Test 2: Data size 9: : 70%|███████ | 7/10 [00:45<00:19, 6.57s/it, data_size=8, test_acc=0.491, train_acc=nan]Test 2: Data size 9: : 70%|███████ | 7/10 [00:51<00:19, 6.57s/it, data_size=9, test_acc=0.462, train_acc=nan]Test 2: Data size 9: : 80%|████████ | 8/10 [00:52<00:13, 6.68s/it, data_size=9, test_acc=0.462, train_acc=nan]Test 2: Data size 10: : 80%|████████ | 8/10 [00:52<00:13, 6.68s/it, data_size=9, test_acc=0.462, train_acc=nan]Test 2: Data size 10: : 80%|████████ | 8/10 [00:58<00:13, 6.68s/it, data_size=10, test_acc=0.507, train_acc=nan]Test 2: Data size 10: : 90%|█████████ | 9/10 [00:59<00:06, 6.78s/it, data_size=10, test_acc=0.507, train_acc=nan]Test 2: Data size 11: : 90%|█████████ | 9/10 [00:59<00:06, 6.78s/it, data_size=10, test_acc=0.507, train_acc=nan]Test 2: Data size 11: : 90%|█████████ | 9/10 [01:06<00:06, 6.78s/it, data_size=11, test_acc=0.646, train_acc=0.7]Test 2: Data size 11: : 100%|██████████| 10/10 [01:06<00:00, 6.89s/it, data_size=11, test_acc=0.646, train_acc=0.7]Test 2: Data size 11: : 100%|██████████| 10/10 [01:06<00:00, 6.62s/it, data_size=11, test_acc=0.646, train_acc=0.7]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.344, train_acc=nan]Test 3: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.98s/it, data_size=2, test_acc=0.344, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.98s/it, data_size=2, test_acc=0.344, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.98s/it, data_size=3, test_acc=0.355, train_acc=nan]Test 3: Data size 3: : 20%|██ | 2/10 [00:12<00:48, 6.02s/it, data_size=3, test_acc=0.355, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:12<00:48, 6.02s/it, data_size=3, test_acc=0.355, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:18<00:48, 6.02s/it, data_size=4, test_acc=0.455, train_acc=nan]Test 3: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.06s/it, data_size=4, test_acc=0.455, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.06s/it, data_size=4, test_acc=0.455, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.06s/it, data_size=5, test_acc=0.59, train_acc=0.75]Test 3: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.11s/it, data_size=5, test_acc=0.59, train_acc=0.75]Test 3: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.11s/it, data_size=5, test_acc=0.59, train_acc=0.75]Test 3: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.11s/it, data_size=6, test_acc=0.501, train_acc=0.75]Test 3: Data size 6: : 50%|█████ | 5/10 [00:30<00:31, 6.21s/it, data_size=6, test_acc=0.501, train_acc=0.75]Test 3: Data size 7: : 50%|█████ | 5/10 [00:30<00:31, 6.21s/it, data_size=6, test_acc=0.501, train_acc=0.75]Test 3: Data size 7: : 50%|█████ | 5/10 [00:36<00:31, 6.21s/it, data_size=7, test_acc=0.409, train_acc=0.75]Test 3: Data size 7: : 60%|██████ | 6/10 [00:37<00:25, 6.28s/it, data_size=7, test_acc=0.409, train_acc=0.75]Test 3: Data size 8: : 60%|██████ | 6/10 [00:37<00:25, 6.28s/it, data_size=7, test_acc=0.409, train_acc=0.75]Test 3: Data size 8: : 60%|██████ | 6/10 [00:43<00:25, 6.28s/it, data_size=8, test_acc=0.452, train_acc=0.75]Test 3: Data size 8: : 70%|███████ | 7/10 [00:43<00:19, 6.37s/it, data_size=8, test_acc=0.452, train_acc=0.75]Test 3: Data size 9: : 70%|███████ | 7/10 [00:43<00:19, 6.37s/it, data_size=8, test_acc=0.452, train_acc=0.75]Test 3: Data size 9: : 70%|███████ | 7/10 [00:50<00:19, 6.37s/it, data_size=9, test_acc=0.574, train_acc=0.667]Test 3: Data size 9: : 80%|████████ | 8/10 [00:50<00:12, 6.46s/it, data_size=9, test_acc=0.574, train_acc=0.667]Test 3: Data size 10: : 80%|████████ | 8/10 [00:50<00:12, 6.46s/it, data_size=9, test_acc=0.574, train_acc=0.667]Test 3: Data size 10: : 80%|████████ | 8/10 [00:57<00:12, 6.46s/it, data_size=10, test_acc=0.594, train_acc=0.917]Test 3: Data size 10: : 90%|█████████ | 9/10 [00:57<00:06, 6.57s/it, data_size=10, test_acc=0.594, train_acc=0.917]Test 3: Data size 11: : 90%|█████████ | 9/10 [00:57<00:06, 6.57s/it, data_size=10, test_acc=0.594, train_acc=0.917]Test 3: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.57s/it, data_size=11, test_acc=0.582, train_acc=1] Test 3: Data size 11: : 100%|██████████| 10/10 [01:04<00:00, 6.69s/it, data_size=11, test_acc=0.582, train_acc=1]Test 3: Data size 11: : 100%|██████████| 10/10 [01:04<00:00, 6.41s/it, data_size=11, test_acc=0.582, train_acc=1]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 10%|█ | 1/10 [00:06<00:55, 6.17s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:06<00:55, 6.17s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:12<00:55, 6.17s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 20%|██ | 2/10 [00:12<00:49, 6.21s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:12<00:49, 6.21s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:18<00:49, 6.21s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 30%|███ | 3/10 [00:18<00:43, 6.26s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:18<00:43, 6.26s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:25<00:43, 6.26s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 40%|████ | 4/10 [00:25<00:37, 6.32s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:25<00:37, 6.32s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:31<00:37, 6.32s/it, data_size=6, test_acc=0.299, train_acc=nan]Test 4: Data size 6: : 50%|█████ | 5/10 [00:31<00:31, 6.38s/it, data_size=6, test_acc=0.299, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:31<00:31, 6.38s/it, data_size=6, test_acc=0.299, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:38<00:31, 6.38s/it, data_size=7, test_acc=0.412, train_acc=nan]Test 4: Data size 7: : 60%|██████ | 6/10 [00:38<00:25, 6.45s/it, data_size=7, test_acc=0.412, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:38<00:25, 6.45s/it, data_size=7, test_acc=0.412, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:44<00:25, 6.45s/it, data_size=8, test_acc=0.471, train_acc=nan]Test 4: Data size 8: : 70%|███████ | 7/10 [00:44<00:19, 6.52s/it, data_size=8, test_acc=0.471, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:44<00:19, 6.52s/it, data_size=8, test_acc=0.471, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:51<00:19, 6.52s/it, data_size=9, test_acc=0.461, train_acc=nan]Test 4: Data size 9: : 80%|████████ | 8/10 [00:51<00:13, 6.66s/it, data_size=9, test_acc=0.461, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [00:51<00:13, 6.66s/it, data_size=9, test_acc=0.461, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [00:58<00:13, 6.66s/it, data_size=10, test_acc=0.471, train_acc=0.583]Test 4: Data size 10: : 90%|█████████ | 9/10 [00:58<00:06, 6.75s/it, data_size=10, test_acc=0.471, train_acc=0.583]Test 4: Data size 11: : 90%|█████████ | 9/10 [00:58<00:06, 6.75s/it, data_size=10, test_acc=0.471, train_acc=0.583]Test 4: Data size 11: : 90%|█████████ | 9/10 [01:05<00:06, 6.75s/it, data_size=11, test_acc=0.431, train_acc=0.688]Test 4: Data size 11: : 100%|██████████| 10/10 [01:05<00:00, 6.86s/it, data_size=11, test_acc=0.431, train_acc=0.688]Test 4: Data size 11: : 100%|██████████| 10/10 [01:05<00:00, 6.59s/it, data_size=11, test_acc=0.431, train_acc=0.688]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 2: : 10%|█ | 1/10 [00:06<00:54, 6.03s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:06<00:54, 6.03s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:11<00:54, 6.03s/it, data_size=3, test_acc=0.248, train_acc=nan]Test 5: Data size 3: : 20%|██ | 2/10 [00:12<00:48, 6.05s/it, data_size=3, test_acc=0.248, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:12<00:48, 6.05s/it, data_size=3, test_acc=0.248, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:18<00:48, 6.05s/it, data_size=4, test_acc=0.248, train_acc=nan]Test 5: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.08s/it, data_size=4, test_acc=0.248, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.08s/it, data_size=4, test_acc=0.248, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.08s/it, data_size=5, test_acc=0.456, train_acc=nan]Test 5: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.14s/it, data_size=5, test_acc=0.456, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.14s/it, data_size=5, test_acc=0.456, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.14s/it, data_size=6, test_acc=0.42, train_acc=nan] Test 5: Data size 6: : 50%|█████ | 5/10 [00:30<00:31, 6.22s/it, data_size=6, test_acc=0.42, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:30<00:31, 6.22s/it, data_size=6, test_acc=0.42, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:37<00:31, 6.22s/it, data_size=7, test_acc=0.391, train_acc=nan]Test 5: Data size 7: : 60%|██████ | 6/10 [00:37<00:25, 6.27s/it, data_size=7, test_acc=0.391, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [00:37<00:25, 6.27s/it, data_size=7, test_acc=0.391, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [00:43<00:25, 6.27s/it, data_size=8, test_acc=0.42, train_acc=nan] Test 5: Data size 8: : 70%|███████ | 7/10 [00:43<00:19, 6.34s/it, data_size=8, test_acc=0.42, train_acc=nan]Test 5: Data size 9: : 70%|███████ | 7/10 [00:43<00:19, 6.34s/it, data_size=8, test_acc=0.42, train_acc=nan]Test 5: Data size 9: : 70%|███████ | 7/10 [00:50<00:19, 6.34s/it, data_size=9, test_acc=0.42, train_acc=nan]Test 5: Data size 9: : 80%|████████ | 8/10 [00:50<00:12, 6.46s/it, data_size=9, test_acc=0.42, train_acc=nan]Test 5: Data size 10: : 80%|████████ | 8/10 [00:50<00:12, 6.46s/it, data_size=9, test_acc=0.42, train_acc=nan]Test 5: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.46s/it, data_size=10, test_acc=0.552, train_acc=nan]Test 5: Data size 10: : 90%|█████████ | 9/10 [00:57<00:06, 6.55s/it, data_size=10, test_acc=0.552, train_acc=nan]Test 5: Data size 11: : 90%|█████████ | 9/10 [00:57<00:06, 6.55s/it, data_size=10, test_acc=0.552, train_acc=nan]Test 5: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.55s/it, data_size=11, test_acc=0.573, train_acc=nan]Test 5: Data size 11: : 100%|██████████| 10/10 [01:04<00:00, 6.67s/it, data_size=11, test_acc=0.573, train_acc=nan]Test 5: Data size 11: : 100%|██████████| 10/10 [01:04<00:00, 6.41s/it, data_size=11, test_acc=0.573, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 2: : 10%|█ | 1/10 [00:06<00:55, 6.22s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:06<00:55, 6.22s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:12<00:55, 6.22s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 20%|██ | 2/10 [00:12<00:50, 6.25s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:12<00:50, 6.25s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:18<00:50, 6.25s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 30%|███ | 3/10 [00:18<00:44, 6.30s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:18<00:44, 6.30s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:25<00:44, 6.30s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 40%|████ | 4/10 [00:25<00:38, 6.34s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:25<00:38, 6.34s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:31<00:38, 6.34s/it, data_size=6, test_acc=0.359, train_acc=nan]Test 6: Data size 6: : 50%|█████ | 5/10 [00:31<00:32, 6.41s/it, data_size=6, test_acc=0.359, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:31<00:32, 6.41s/it, data_size=6, test_acc=0.359, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:38<00:32, 6.41s/it, data_size=7, test_acc=0.444, train_acc=nan]Test 6: Data size 7: : 60%|██████ | 6/10 [00:38<00:25, 6.46s/it, data_size=7, test_acc=0.444, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:38<00:25, 6.46s/it, data_size=7, test_acc=0.444, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:44<00:25, 6.46s/it, data_size=8, test_acc=0.342, train_acc=nan]Test 6: Data size 8: : 70%|███████ | 7/10 [00:45<00:19, 6.53s/it, data_size=8, test_acc=0.342, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:45<00:19, 6.53s/it, data_size=8, test_acc=0.342, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:51<00:19, 6.53s/it, data_size=9, test_acc=0.469, train_acc=nan]Test 6: Data size 9: : 80%|████████ | 8/10 [00:51<00:13, 6.66s/it, data_size=9, test_acc=0.469, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [00:51<00:13, 6.66s/it, data_size=9, test_acc=0.469, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [00:58<00:13, 6.66s/it, data_size=10, test_acc=0.405, train_acc=nan]Test 6: Data size 10: : 90%|█████████ | 9/10 [00:58<00:06, 6.77s/it, data_size=10, test_acc=0.405, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [00:58<00:06, 6.77s/it, data_size=10, test_acc=0.405, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [01:05<00:06, 6.77s/it, data_size=11, test_acc=0.5, train_acc=nan] Test 6: Data size 11: : 100%|██████████| 10/10 [01:06<00:00, 6.89s/it, data_size=11, test_acc=0.5, train_acc=nan]Test 6: Data size 11: : 100%|██████████| 10/10 [01:06<00:00, 6.61s/it, data_size=11, test_acc=0.5, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 2: : 10%|█ | 1/10 [00:06<00:54, 6.03s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:06<00:54, 6.03s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:11<00:54, 6.03s/it, data_size=3, test_acc=0.255, train_acc=nan]Test 7: Data size 3: : 20%|██ | 2/10 [00:12<00:48, 6.06s/it, data_size=3, test_acc=0.255, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:12<00:48, 6.06s/it, data_size=3, test_acc=0.255, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:18<00:48, 6.06s/it, data_size=4, test_acc=0.264, train_acc=nan]Test 7: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.14s/it, data_size=4, test_acc=0.264, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.14s/it, data_size=4, test_acc=0.264, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.14s/it, data_size=5, test_acc=0.28, train_acc=nan] Test 7: Data size 5: : 40%|████ | 4/10 [00:24<00:37, 6.17s/it, data_size=5, test_acc=0.28, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [00:24<00:37, 6.17s/it, data_size=5, test_acc=0.28, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [00:30<00:37, 6.17s/it, data_size=6, test_acc=0.392, train_acc=nan]Test 7: Data size 6: : 50%|█████ | 5/10 [00:30<00:30, 6.19s/it, data_size=6, test_acc=0.392, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [00:30<00:30, 6.19s/it, data_size=6, test_acc=0.392, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [00:37<00:30, 6.19s/it, data_size=7, test_acc=0.471, train_acc=0.5]Test 7: Data size 7: : 60%|██████ | 6/10 [00:37<00:25, 6.28s/it, data_size=7, test_acc=0.471, train_acc=0.5]Test 7: Data size 8: : 60%|██████ | 6/10 [00:37<00:25, 6.28s/it, data_size=7, test_acc=0.471, train_acc=0.5]Test 7: Data size 8: : 60%|██████ | 6/10 [00:43<00:25, 6.28s/it, data_size=8, test_acc=0.508, train_acc=0.417]Test 7: Data size 8: : 70%|███████ | 7/10 [00:43<00:19, 6.34s/it, data_size=8, test_acc=0.508, train_acc=0.417]Test 7: Data size 9: : 70%|███████ | 7/10 [00:43<00:19, 6.34s/it, data_size=8, test_acc=0.508, train_acc=0.417]Test 7: Data size 9: : 70%|███████ | 7/10 [00:50<00:19, 6.34s/it, data_size=9, test_acc=0.423, train_acc=0.583]Test 7: Data size 9: : 80%|████████ | 8/10 [00:50<00:12, 6.44s/it, data_size=9, test_acc=0.423, train_acc=0.583]Test 7: Data size 10: : 80%|████████ | 8/10 [00:50<00:12, 6.44s/it, data_size=9, test_acc=0.423, train_acc=0.583]Test 7: Data size 10: : 80%|████████ | 8/10 [00:57<00:12, 6.44s/it, data_size=10, test_acc=0.468, train_acc=0.625]Test 7: Data size 10: : 90%|█████████ | 9/10 [00:57<00:06, 6.55s/it, data_size=10, test_acc=0.468, train_acc=0.625]Test 7: Data size 11: : 90%|█████████ | 9/10 [00:57<00:06, 6.55s/it, data_size=10, test_acc=0.468, train_acc=0.625]Test 7: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.55s/it, data_size=11, test_acc=0.56, train_acc=0.688] Test 7: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.64s/it, data_size=11, test_acc=0.56, train_acc=0.688]Test 7: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.40s/it, data_size=11, test_acc=0.56, train_acc=0.688]
working on model Multimodal-middle-fusion-model-based-on-AlexNet with MIN_MARGIN
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.94s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.94s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.94s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 20%|██ | 2/10 [00:11<00:47, 5.98s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:11<00:47, 5.98s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:17<00:47, 5.98s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.06s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.06s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.06s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.09s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.09s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.09s/it, data_size=6, test_acc=0.37, train_acc=nan]Test 0: Data size 6: : 50%|█████ | 5/10 [00:30<00:30, 6.15s/it, data_size=6, test_acc=0.37, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [00:30<00:30, 6.15s/it, data_size=6, test_acc=0.37, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [00:36<00:30, 6.15s/it, data_size=7, test_acc=0.465, train_acc=nan]Test 0: Data size 7: : 60%|██████ | 6/10 [00:36<00:24, 6.22s/it, data_size=7, test_acc=0.465, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [00:36<00:24, 6.22s/it, data_size=7, test_acc=0.465, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [00:43<00:24, 6.22s/it, data_size=8, test_acc=0.481, train_acc=nan]Test 0: Data size 8: : 70%|███████ | 7/10 [00:43<00:18, 6.28s/it, data_size=8, test_acc=0.481, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [00:43<00:18, 6.28s/it, data_size=8, test_acc=0.481, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [00:49<00:18, 6.28s/it, data_size=9, test_acc=0.494, train_acc=nan]Test 0: Data size 9: : 80%|████████ | 8/10 [00:49<00:12, 6.41s/it, data_size=9, test_acc=0.494, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [00:49<00:12, 6.41s/it, data_size=9, test_acc=0.494, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.41s/it, data_size=10, test_acc=0.478, train_acc=nan]Test 0: Data size 10: : 90%|█████████ | 9/10 [00:56<00:06, 6.50s/it, data_size=10, test_acc=0.478, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [00:56<00:06, 6.50s/it, data_size=10, test_acc=0.478, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.50s/it, data_size=11, test_acc=0.561, train_acc=nan]Test 0: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.58s/it, data_size=11, test_acc=0.561, train_acc=nan]Test 0: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.34s/it, data_size=11, test_acc=0.561, train_acc=nan]
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0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.99s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.99s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.99s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 20%|██ | 2/10 [00:12<00:48, 6.02s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:12<00:48, 6.02s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:17<00:48, 6.02s/it, data_size=4, test_acc=0.276, train_acc=nan]Test 2: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.04s/it, data_size=4, test_acc=0.276, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.04s/it, data_size=4, test_acc=0.276, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.04s/it, data_size=5, test_acc=0.344, train_acc=nan]Test 2: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.11s/it, data_size=5, test_acc=0.344, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.11s/it, data_size=5, test_acc=0.344, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.11s/it, data_size=6, test_acc=0.443, train_acc=nan]Test 2: Data size 6: : 50%|█████ | 5/10 [00:30<00:30, 6.18s/it, data_size=6, test_acc=0.443, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [00:30<00:30, 6.18s/it, data_size=6, test_acc=0.443, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [00:36<00:30, 6.18s/it, data_size=7, test_acc=0.439, train_acc=nan]Test 2: Data size 7: : 60%|██████ | 6/10 [00:36<00:24, 6.21s/it, data_size=7, test_acc=0.439, train_acc=nan]Test 2: Data size 8: : 60%|██████ | 6/10 [00:36<00:24, 6.21s/it, data_size=7, test_acc=0.439, train_acc=nan]Test 2: Data size 8: : 60%|██████ | 6/10 [00:43<00:24, 6.21s/it, data_size=8, test_acc=0.443, train_acc=nan]Test 2: Data size 8: : 70%|███████ | 7/10 [00:43<00:18, 6.25s/it, data_size=8, test_acc=0.443, train_acc=nan]Test 2: Data size 9: : 70%|███████ | 7/10 [00:43<00:18, 6.25s/it, data_size=8, test_acc=0.443, train_acc=nan]Test 2: Data size 9: : 70%|███████ | 7/10 [00:49<00:18, 6.25s/it, data_size=9, test_acc=0.298, train_acc=nan]Test 2: Data size 9: : 80%|████████ | 8/10 [00:49<00:12, 6.39s/it, data_size=9, test_acc=0.298, train_acc=nan]Test 2: Data size 10: : 80%|████████ | 8/10 [00:49<00:12, 6.39s/it, data_size=9, test_acc=0.298, train_acc=nan]Test 2: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.39s/it, data_size=10, test_acc=0.417, train_acc=nan]Test 2: Data size 10: : 90%|█████████ | 9/10 [00:56<00:06, 6.50s/it, data_size=10, test_acc=0.417, train_acc=nan]Test 2: Data size 11: : 90%|█████████ | 9/10 [00:56<00:06, 6.50s/it, data_size=10, test_acc=0.417, train_acc=nan]Test 2: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.50s/it, data_size=11, test_acc=0.441, train_acc=nan]Test 2: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.60s/it, data_size=11, test_acc=0.441, train_acc=nan]Test 2: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.35s/it, data_size=11, test_acc=0.441, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.405, train_acc=nan]Test 3: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.97s/it, data_size=2, test_acc=0.405, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.97s/it, data_size=2, test_acc=0.405, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.97s/it, data_size=3, test_acc=0.252, train_acc=nan]Test 3: Data size 3: : 20%|██ | 2/10 [00:12<00:48, 6.06s/it, data_size=3, test_acc=0.252, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:12<00:48, 6.06s/it, data_size=3, test_acc=0.252, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:18<00:48, 6.06s/it, data_size=4, test_acc=0.25, train_acc=nan] Test 3: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.14s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.14s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.14s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 40%|████ | 4/10 [00:24<00:37, 6.18s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [00:24<00:37, 6.18s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [00:30<00:37, 6.18s/it, data_size=6, test_acc=0.5, train_acc=nan] Test 3: Data size 6: : 50%|█████ | 5/10 [00:30<00:31, 6.21s/it, data_size=6, test_acc=0.5, train_acc=nan]Test 3: Data size 7: : 50%|█████ | 5/10 [00:30<00:31, 6.21s/it, data_size=6, test_acc=0.5, train_acc=nan]Test 3: Data size 7: : 50%|█████ | 5/10 [00:37<00:31, 6.21s/it, data_size=7, test_acc=0.663, train_acc=nan]Test 3: Data size 7: : 60%|██████ | 6/10 [00:37<00:24, 6.25s/it, data_size=7, test_acc=0.663, train_acc=nan]Test 3: Data size 8: : 60%|██████ | 6/10 [00:37<00:24, 6.25s/it, data_size=7, test_acc=0.663, train_acc=nan]Test 3: Data size 8: : 60%|██████ | 6/10 [00:43<00:24, 6.25s/it, data_size=8, test_acc=0.704, train_acc=0.75]Test 3: Data size 8: : 70%|███████ | 7/10 [00:43<00:18, 6.33s/it, data_size=8, test_acc=0.704, train_acc=0.75]Test 3: Data size 9: : 70%|███████ | 7/10 [00:43<00:18, 6.33s/it, data_size=8, test_acc=0.704, train_acc=0.75]Test 3: Data size 9: : 70%|███████ | 7/10 [00:50<00:18, 6.33s/it, data_size=9, test_acc=0.672, train_acc=0.667]Test 3: Data size 9: : 80%|████████ | 8/10 [00:50<00:12, 6.45s/it, data_size=9, test_acc=0.672, train_acc=0.667]Test 3: Data size 10: : 80%|████████ | 8/10 [00:50<00:12, 6.45s/it, data_size=9, test_acc=0.672, train_acc=0.667]Test 3: Data size 10: : 80%|████████ | 8/10 [00:57<00:12, 6.45s/it, data_size=10, test_acc=0.635, train_acc=0.75]Test 3: Data size 10: : 90%|█████████ | 9/10 [00:57<00:06, 6.57s/it, data_size=10, test_acc=0.635, train_acc=0.75]Test 3: Data size 11: : 90%|█████████ | 9/10 [00:57<00:06, 6.57s/it, data_size=10, test_acc=0.635, train_acc=0.75]Test 3: Data size 11: : 90%|█████████ | 9/10 [01:04<00:06, 6.57s/it, data_size=11, test_acc=0.682, train_acc=0.75]Test 3: Data size 11: : 100%|██████████| 10/10 [01:04<00:00, 6.68s/it, data_size=11, test_acc=0.682, train_acc=0.75]Test 3: Data size 11: : 100%|██████████| 10/10 [01:04<00:00, 6.41s/it, data_size=11, test_acc=0.682, train_acc=0.75]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.98s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.98s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.98s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 20%|██ | 2/10 [00:12<00:48, 6.01s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:12<00:48, 6.01s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:17<00:48, 6.01s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.04s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.04s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.04s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.10s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.10s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.10s/it, data_size=6, test_acc=0.299, train_acc=nan]Test 4: Data size 6: : 50%|█████ | 5/10 [00:30<00:30, 6.17s/it, data_size=6, test_acc=0.299, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:30<00:30, 6.17s/it, data_size=6, test_acc=0.299, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:36<00:30, 6.17s/it, data_size=7, test_acc=0.412, train_acc=nan]Test 4: Data size 7: : 60%|██████ | 6/10 [00:36<00:24, 6.21s/it, data_size=7, test_acc=0.412, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:36<00:24, 6.21s/it, data_size=7, test_acc=0.412, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:43<00:24, 6.21s/it, data_size=8, test_acc=0.471, train_acc=0.5]Test 4: Data size 8: : 70%|███████ | 7/10 [00:43<00:18, 6.31s/it, data_size=8, test_acc=0.471, train_acc=0.5]Test 4: Data size 9: : 70%|███████ | 7/10 [00:43<00:18, 6.31s/it, data_size=8, test_acc=0.471, train_acc=0.5]Test 4: Data size 9: : 70%|███████ | 7/10 [00:49<00:18, 6.31s/it, data_size=9, test_acc=0.471, train_acc=0.5]Test 4: Data size 9: : 80%|████████ | 8/10 [00:50<00:12, 6.43s/it, data_size=9, test_acc=0.471, train_acc=0.5]Test 4: Data size 10: : 80%|████████ | 8/10 [00:50<00:12, 6.43s/it, data_size=9, test_acc=0.471, train_acc=0.5]Test 4: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.43s/it, data_size=10, test_acc=0.495, train_acc=0.5]Test 4: Data size 10: : 90%|█████████ | 9/10 [00:56<00:06, 6.51s/it, data_size=10, test_acc=0.495, train_acc=0.5]Test 4: Data size 11: : 90%|█████████ | 9/10 [00:56<00:06, 6.51s/it, data_size=10, test_acc=0.495, train_acc=0.5]Test 4: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.51s/it, data_size=11, test_acc=0.48, train_acc=0.667]Test 4: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.60s/it, data_size=11, test_acc=0.48, train_acc=0.667]Test 4: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.36s/it, data_size=11, test_acc=0.48, train_acc=0.667]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.99s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.99s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:12<00:53, 5.99s/it, data_size=3, test_acc=0.248, train_acc=nan]Test 5: Data size 3: : 20%|██ | 2/10 [00:12<00:48, 6.08s/it, data_size=3, test_acc=0.248, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:12<00:48, 6.08s/it, data_size=3, test_acc=0.248, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:18<00:48, 6.08s/it, data_size=4, test_acc=0.248, train_acc=nan]Test 5: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.14s/it, data_size=4, test_acc=0.248, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.14s/it, data_size=4, test_acc=0.248, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.14s/it, data_size=5, test_acc=0.463, train_acc=nan]Test 5: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.15s/it, data_size=5, test_acc=0.463, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.15s/it, data_size=5, test_acc=0.463, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.15s/it, data_size=6, test_acc=0.289, train_acc=nan]Test 5: Data size 6: : 50%|█████ | 5/10 [00:30<00:31, 6.20s/it, data_size=6, test_acc=0.289, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:30<00:31, 6.20s/it, data_size=6, test_acc=0.289, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:37<00:31, 6.20s/it, data_size=7, test_acc=0.378, train_acc=0.5]Test 5: Data size 7: : 60%|██████ | 6/10 [00:37<00:25, 6.26s/it, data_size=7, test_acc=0.378, train_acc=0.5]Test 5: Data size 8: : 60%|██████ | 6/10 [00:37<00:25, 6.26s/it, data_size=7, test_acc=0.378, train_acc=0.5]Test 5: Data size 8: : 60%|██████ | 6/10 [00:43<00:25, 6.26s/it, data_size=8, test_acc=0.483, train_acc=0.5]Test 5: Data size 8: : 70%|███████ | 7/10 [00:43<00:18, 6.31s/it, data_size=8, test_acc=0.483, train_acc=0.5]Test 5: Data size 9: : 70%|███████ | 7/10 [00:43<00:18, 6.31s/it, data_size=8, test_acc=0.483, train_acc=0.5]Test 5: Data size 9: : 70%|███████ | 7/10 [00:50<00:18, 6.31s/it, data_size=9, test_acc=0.483, train_acc=0.417]Test 5: Data size 9: : 80%|████████ | 8/10 [00:50<00:12, 6.45s/it, data_size=9, test_acc=0.483, train_acc=0.417]Test 5: Data size 10: : 80%|████████ | 8/10 [00:50<00:12, 6.45s/it, data_size=9, test_acc=0.483, train_acc=0.417]Test 5: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.45s/it, data_size=10, test_acc=0.448, train_acc=0.438]Test 5: Data size 10: : 90%|█████████ | 9/10 [00:57<00:06, 6.55s/it, data_size=10, test_acc=0.448, train_acc=0.438]Test 5: Data size 11: : 90%|█████████ | 9/10 [00:57<00:06, 6.55s/it, data_size=10, test_acc=0.448, train_acc=0.438]Test 5: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.55s/it, data_size=11, test_acc=0.47, train_acc=0.45] Test 5: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.62s/it, data_size=11, test_acc=0.47, train_acc=0.45]Test 5: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.39s/it, data_size=11, test_acc=0.47, train_acc=0.45]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.91s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.91s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.91s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 20%|██ | 2/10 [00:11<00:47, 5.99s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:11<00:47, 5.99s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:17<00:47, 5.99s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.06s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.06s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.06s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.10s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.10s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.10s/it, data_size=6, test_acc=0.364, train_acc=nan]Test 6: Data size 6: : 50%|█████ | 5/10 [00:30<00:30, 6.14s/it, data_size=6, test_acc=0.364, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:30<00:30, 6.14s/it, data_size=6, test_acc=0.364, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:36<00:30, 6.14s/it, data_size=7, test_acc=0.444, train_acc=nan]Test 6: Data size 7: : 60%|██████ | 6/10 [00:36<00:24, 6.19s/it, data_size=7, test_acc=0.444, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:36<00:24, 6.19s/it, data_size=7, test_acc=0.444, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:43<00:24, 6.19s/it, data_size=8, test_acc=0.288, train_acc=nan]Test 6: Data size 8: : 70%|███████ | 7/10 [00:43<00:18, 6.28s/it, data_size=8, test_acc=0.288, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:43<00:18, 6.28s/it, data_size=8, test_acc=0.288, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:49<00:18, 6.28s/it, data_size=9, test_acc=0.47, train_acc=0.375]Test 6: Data size 9: : 80%|████████ | 8/10 [00:49<00:12, 6.36s/it, data_size=9, test_acc=0.47, train_acc=0.375]Test 6: Data size 10: : 80%|████████ | 8/10 [00:49<00:12, 6.36s/it, data_size=9, test_acc=0.47, train_acc=0.375]Test 6: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.36s/it, data_size=10, test_acc=0.32, train_acc=0.25]Test 6: Data size 10: : 90%|█████████ | 9/10 [00:56<00:06, 6.46s/it, data_size=10, test_acc=0.32, train_acc=0.25]Test 6: Data size 11: : 90%|█████████ | 9/10 [00:56<00:06, 6.46s/it, data_size=10, test_acc=0.32, train_acc=0.25]Test 6: Data size 11: : 90%|█████████ | 9/10 [01:02<00:06, 6.46s/it, data_size=11, test_acc=0.475, train_acc=0.417]Test 6: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.50s/it, data_size=11, test_acc=0.475, train_acc=0.417]Test 6: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.30s/it, data_size=11, test_acc=0.475, train_acc=0.417]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.98s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.98s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.98s/it, data_size=3, test_acc=0.255, train_acc=nan]Test 7: Data size 3: : 20%|██ | 2/10 [00:12<00:48, 6.01s/it, data_size=3, test_acc=0.255, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:12<00:48, 6.01s/it, data_size=3, test_acc=0.255, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:18<00:48, 6.01s/it, data_size=4, test_acc=0.25, train_acc=nan] Test 7: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.09s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.09s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.09s/it, data_size=5, test_acc=0.403, train_acc=nan]Test 7: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.14s/it, data_size=5, test_acc=0.403, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.14s/it, data_size=5, test_acc=0.403, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.14s/it, data_size=6, test_acc=0.371, train_acc=nan]Test 7: Data size 6: : 50%|█████ | 5/10 [00:30<00:30, 6.18s/it, data_size=6, test_acc=0.371, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [00:30<00:30, 6.18s/it, data_size=6, test_acc=0.371, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [00:36<00:30, 6.18s/it, data_size=7, test_acc=0.359, train_acc=nan]Test 7: Data size 7: : 60%|██████ | 6/10 [00:36<00:24, 6.23s/it, data_size=7, test_acc=0.359, train_acc=nan]Test 7: Data size 8: : 60%|██████ | 6/10 [00:36<00:24, 6.23s/it, data_size=7, test_acc=0.359, train_acc=nan]Test 7: Data size 8: : 60%|██████ | 6/10 [00:43<00:24, 6.23s/it, data_size=8, test_acc=0.398, train_acc=nan]Test 7: Data size 8: : 70%|███████ | 7/10 [00:43<00:18, 6.31s/it, data_size=8, test_acc=0.398, train_acc=nan]Test 7: Data size 9: : 70%|███████ | 7/10 [00:43<00:18, 6.31s/it, data_size=8, test_acc=0.398, train_acc=nan]Test 7: Data size 9: : 70%|███████ | 7/10 [00:50<00:18, 6.31s/it, data_size=9, test_acc=0.463, train_acc=nan]Test 7: Data size 9: : 80%|████████ | 8/10 [00:50<00:12, 6.43s/it, data_size=9, test_acc=0.463, train_acc=nan]Test 7: Data size 10: : 80%|████████ | 8/10 [00:50<00:12, 6.43s/it, data_size=9, test_acc=0.463, train_acc=nan]Test 7: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.43s/it, data_size=10, test_acc=0.354, train_acc=nan]Test 7: Data size 10: : 90%|█████████ | 9/10 [00:56<00:06, 6.53s/it, data_size=10, test_acc=0.354, train_acc=nan]Test 7: Data size 11: : 90%|█████████ | 9/10 [00:56<00:06, 6.53s/it, data_size=10, test_acc=0.354, train_acc=nan]Test 7: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.53s/it, data_size=11, test_acc=0.342, train_acc=nan]Test 7: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.61s/it, data_size=11, test_acc=0.342, train_acc=nan]Test 7: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.37s/it, data_size=11, test_acc=0.342, train_acc=nan]
working on model Multimodal-middle-fusion-model-based-on-AlexNet with MAX_ENTROPY
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.95s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.95s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.95s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 20%|██ | 2/10 [00:11<00:47, 5.94s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:11<00:47, 5.94s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:17<00:47, 5.94s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 30%|███ | 3/10 [00:17<00:42, 6.01s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:17<00:42, 6.01s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:23<00:42, 6.01s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.06s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.06s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.06s/it, data_size=6, test_acc=0.452, train_acc=nan]Test 0: Data size 6: : 50%|█████ | 5/10 [00:30<00:30, 6.12s/it, data_size=6, test_acc=0.452, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [00:30<00:30, 6.12s/it, data_size=6, test_acc=0.452, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [00:36<00:30, 6.12s/it, data_size=7, test_acc=0.281, train_acc=nan]Test 0: Data size 7: : 60%|██████ | 6/10 [00:36<00:24, 6.14s/it, data_size=7, test_acc=0.281, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [00:36<00:24, 6.14s/it, data_size=7, test_acc=0.281, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [00:42<00:24, 6.14s/it, data_size=8, test_acc=0.252, train_acc=nan]Test 0: Data size 8: : 70%|███████ | 7/10 [00:42<00:18, 6.24s/it, data_size=8, test_acc=0.252, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [00:42<00:18, 6.24s/it, data_size=8, test_acc=0.252, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [00:49<00:18, 6.24s/it, data_size=9, test_acc=0.267, train_acc=nan]Test 0: Data size 9: : 80%|████████ | 8/10 [00:49<00:12, 6.37s/it, data_size=9, test_acc=0.267, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [00:49<00:12, 6.37s/it, data_size=9, test_acc=0.267, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.37s/it, data_size=10, test_acc=0.482, train_acc=nan]Test 0: Data size 10: : 90%|█████████ | 9/10 [00:56<00:06, 6.48s/it, data_size=10, test_acc=0.482, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [00:56<00:06, 6.48s/it, data_size=10, test_acc=0.482, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [01:02<00:06, 6.48s/it, data_size=11, test_acc=0.457, train_acc=nan]Test 0: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.57s/it, data_size=11, test_acc=0.457, train_acc=nan]Test 0: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.31s/it, data_size=11, test_acc=0.457, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.99s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.99s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.99s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 20%|██ | 2/10 [00:12<00:48, 6.02s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:12<00:48, 6.02s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:18<00:48, 6.02s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.11s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.11s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.11s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 40%|████ | 4/10 [00:24<00:37, 6.18s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:24<00:37, 6.18s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:30<00:37, 6.18s/it, data_size=6, test_acc=0.394, train_acc=nan]Test 1: Data size 6: : 50%|█████ | 5/10 [00:30<00:31, 6.22s/it, data_size=6, test_acc=0.394, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:30<00:31, 6.22s/it, data_size=6, test_acc=0.394, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:37<00:31, 6.22s/it, data_size=7, test_acc=0.25, train_acc=nan] Test 1: Data size 7: : 60%|██████ | 6/10 [00:37<00:25, 6.25s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [00:37<00:25, 6.25s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [00:43<00:25, 6.25s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 70%|███████ | 7/10 [00:43<00:18, 6.31s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [00:43<00:18, 6.31s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [00:50<00:18, 6.31s/it, data_size=9, test_acc=0.448, train_acc=nan]Test 1: Data size 9: : 80%|████████ | 8/10 [00:50<00:12, 6.42s/it, data_size=9, test_acc=0.448, train_acc=nan]Test 1: Data size 10: : 80%|████████ | 8/10 [00:50<00:12, 6.42s/it, data_size=9, test_acc=0.448, train_acc=nan]Test 1: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.42s/it, data_size=10, test_acc=0.466, train_acc=nan]Test 1: Data size 10: : 90%|█████████ | 9/10 [00:56<00:06, 6.53s/it, data_size=10, test_acc=0.466, train_acc=nan]Test 1: Data size 11: : 90%|█████████ | 9/10 [00:56<00:06, 6.53s/it, data_size=10, test_acc=0.466, train_acc=nan]Test 1: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.53s/it, data_size=11, test_acc=0.439, train_acc=nan]Test 1: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.65s/it, data_size=11, test_acc=0.439, train_acc=nan]Test 1: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.39s/it, data_size=11, test_acc=0.439, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.94s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.94s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.94s/it, data_size=3, test_acc=0.295, train_acc=nan]Test 2: Data size 3: : 20%|██ | 2/10 [00:11<00:47, 5.99s/it, data_size=3, test_acc=0.295, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:11<00:47, 5.99s/it, data_size=3, test_acc=0.295, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:17<00:47, 5.99s/it, data_size=4, test_acc=0.31, train_acc=nan] Test 2: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.04s/it, data_size=4, test_acc=0.31, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.04s/it, data_size=4, test_acc=0.31, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.04s/it, data_size=5, test_acc=0.31, train_acc=nan]Test 2: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.12s/it, data_size=5, test_acc=0.31, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.12s/it, data_size=5, test_acc=0.31, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.12s/it, data_size=6, test_acc=0.327, train_acc=nan]Test 2: Data size 6: : 50%|█████ | 5/10 [00:30<00:30, 6.15s/it, data_size=6, test_acc=0.327, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [00:30<00:30, 6.15s/it, data_size=6, test_acc=0.327, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [00:36<00:30, 6.15s/it, data_size=7, test_acc=0.636, train_acc=nan]Test 2: Data size 7: : 60%|██████ | 6/10 [00:36<00:24, 6.22s/it, data_size=7, test_acc=0.636, train_acc=nan]Test 2: Data size 8: : 60%|██████ | 6/10 [00:36<00:24, 6.22s/it, data_size=7, test_acc=0.636, train_acc=nan]Test 2: Data size 8: : 60%|██████ | 6/10 [00:43<00:24, 6.22s/it, data_size=8, test_acc=0.515, train_acc=nan]Test 2: Data size 8: : 70%|███████ | 7/10 [00:43<00:18, 6.30s/it, data_size=8, test_acc=0.515, train_acc=nan]Test 2: Data size 9: : 70%|███████ | 7/10 [00:43<00:18, 6.30s/it, data_size=8, test_acc=0.515, train_acc=nan]Test 2: Data size 9: : 70%|███████ | 7/10 [00:49<00:18, 6.30s/it, data_size=9, test_acc=0.626, train_acc=nan]Test 2: Data size 9: : 80%|████████ | 8/10 [00:49<00:12, 6.39s/it, data_size=9, test_acc=0.626, train_acc=nan]Test 2: Data size 10: : 80%|████████ | 8/10 [00:49<00:12, 6.39s/it, data_size=9, test_acc=0.626, train_acc=nan]Test 2: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.39s/it, data_size=10, test_acc=0.515, train_acc=nan]Test 2: Data size 10: : 90%|█████████ | 9/10 [00:56<00:06, 6.51s/it, data_size=10, test_acc=0.515, train_acc=nan]Test 2: Data size 11: : 90%|█████████ | 9/10 [00:56<00:06, 6.51s/it, data_size=10, test_acc=0.515, train_acc=nan]Test 2: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.51s/it, data_size=11, test_acc=0.594, train_acc=nan]Test 2: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.58s/it, data_size=11, test_acc=0.594, train_acc=nan]Test 2: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.34s/it, data_size=11, test_acc=0.594, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.405, train_acc=nan]Test 3: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.95s/it, data_size=2, test_acc=0.405, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.95s/it, data_size=2, test_acc=0.405, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.95s/it, data_size=3, test_acc=0.331, train_acc=nan]Test 3: Data size 3: : 20%|██ | 2/10 [00:11<00:47, 5.99s/it, data_size=3, test_acc=0.331, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:11<00:47, 5.99s/it, data_size=3, test_acc=0.331, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:18<00:47, 5.99s/it, data_size=4, test_acc=0.46, train_acc=nan] Test 3: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.07s/it, data_size=4, test_acc=0.46, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.07s/it, data_size=4, test_acc=0.46, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.07s/it, data_size=5, test_acc=0.619, train_acc=nan]Test 3: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.14s/it, data_size=5, test_acc=0.619, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.14s/it, data_size=5, test_acc=0.619, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.14s/it, data_size=6, test_acc=0.653, train_acc=0.75]Test 3: Data size 6: : 50%|█████ | 5/10 [00:30<00:30, 6.19s/it, data_size=6, test_acc=0.653, train_acc=0.75]Test 3: Data size 7: : 50%|█████ | 5/10 [00:30<00:30, 6.19s/it, data_size=6, test_acc=0.653, train_acc=0.75]Test 3: Data size 7: : 50%|█████ | 5/10 [00:36<00:30, 6.19s/it, data_size=7, test_acc=0.566, train_acc=0.75]Test 3: Data size 7: : 60%|██████ | 6/10 [00:37<00:24, 6.25s/it, data_size=7, test_acc=0.566, train_acc=0.75]Test 3: Data size 8: : 60%|██████ | 6/10 [00:37<00:24, 6.25s/it, data_size=7, test_acc=0.566, train_acc=0.75]Test 3: Data size 8: : 60%|██████ | 6/10 [00:43<00:24, 6.25s/it, data_size=8, test_acc=0.519, train_acc=0.75]Test 3: Data size 8: : 70%|███████ | 7/10 [00:43<00:18, 6.31s/it, data_size=8, test_acc=0.519, train_acc=0.75]Test 3: Data size 9: : 70%|███████ | 7/10 [00:43<00:18, 6.31s/it, data_size=8, test_acc=0.519, train_acc=0.75]Test 3: Data size 9: : 70%|███████ | 7/10 [00:50<00:18, 6.31s/it, data_size=9, test_acc=0.542, train_acc=0.75]Test 3: Data size 9: : 80%|████████ | 8/10 [00:50<00:12, 6.45s/it, data_size=9, test_acc=0.542, train_acc=0.75]Test 3: Data size 10: : 80%|████████ | 8/10 [00:50<00:12, 6.45s/it, data_size=9, test_acc=0.542, train_acc=0.75]Test 3: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.45s/it, data_size=10, test_acc=0.61, train_acc=0.75]Test 3: Data size 10: : 90%|█████████ | 9/10 [00:56<00:06, 6.54s/it, data_size=10, test_acc=0.61, train_acc=0.75]Test 3: Data size 11: : 90%|█████████ | 9/10 [00:56<00:06, 6.54s/it, data_size=10, test_acc=0.61, train_acc=0.75]Test 3: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.54s/it, data_size=11, test_acc=0.436, train_acc=0.75]Test 3: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.64s/it, data_size=11, test_acc=0.436, train_acc=0.75]Test 3: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.38s/it, data_size=11, test_acc=0.436, train_acc=0.75]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.89s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.89s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.89s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 20%|██ | 2/10 [00:11<00:47, 5.94s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:11<00:47, 5.94s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:17<00:47, 5.94s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 30%|███ | 3/10 [00:17<00:42, 6.00s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:17<00:42, 6.00s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:23<00:42, 6.00s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.07s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.07s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.07s/it, data_size=6, test_acc=0.299, train_acc=nan]Test 4: Data size 6: : 50%|█████ | 5/10 [00:30<00:30, 6.16s/it, data_size=6, test_acc=0.299, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:30<00:30, 6.16s/it, data_size=6, test_acc=0.299, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:36<00:30, 6.16s/it, data_size=7, test_acc=0.407, train_acc=nan]Test 4: Data size 7: : 60%|██████ | 6/10 [00:36<00:24, 6.22s/it, data_size=7, test_acc=0.407, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:36<00:24, 6.22s/it, data_size=7, test_acc=0.407, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:42<00:24, 6.22s/it, data_size=8, test_acc=0.49, train_acc=nan] Test 4: Data size 8: : 70%|███████ | 7/10 [00:43<00:18, 6.25s/it, data_size=8, test_acc=0.49, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:43<00:18, 6.25s/it, data_size=8, test_acc=0.49, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:49<00:18, 6.25s/it, data_size=9, test_acc=0.495, train_acc=0.5]Test 4: Data size 9: : 80%|████████ | 8/10 [00:49<00:12, 6.36s/it, data_size=9, test_acc=0.495, train_acc=0.5]Test 4: Data size 10: : 80%|████████ | 8/10 [00:49<00:12, 6.36s/it, data_size=9, test_acc=0.495, train_acc=0.5]Test 4: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.36s/it, data_size=10, test_acc=0.495, train_acc=0.5]Test 4: Data size 10: : 90%|█████████ | 9/10 [00:56<00:06, 6.48s/it, data_size=10, test_acc=0.495, train_acc=0.5]Test 4: Data size 11: : 90%|█████████ | 9/10 [00:56<00:06, 6.48s/it, data_size=10, test_acc=0.495, train_acc=0.5]Test 4: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.48s/it, data_size=11, test_acc=0.475, train_acc=0.667]Test 4: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.59s/it, data_size=11, test_acc=0.475, train_acc=0.667]Test 4: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.32s/it, data_size=11, test_acc=0.475, train_acc=0.667]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.93s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.93s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.93s/it, data_size=3, test_acc=0.248, train_acc=nan]Test 5: Data size 3: : 20%|██ | 2/10 [00:11<00:47, 6.00s/it, data_size=3, test_acc=0.248, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:11<00:47, 6.00s/it, data_size=3, test_acc=0.248, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:17<00:47, 6.00s/it, data_size=4, test_acc=0.248, train_acc=nan]Test 5: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.04s/it, data_size=4, test_acc=0.248, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.04s/it, data_size=4, test_acc=0.248, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.04s/it, data_size=5, test_acc=0.463, train_acc=nan]Test 5: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.15s/it, data_size=5, test_acc=0.463, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.15s/it, data_size=5, test_acc=0.463, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.15s/it, data_size=6, test_acc=0.492, train_acc=nan]Test 5: Data size 6: : 50%|█████ | 5/10 [00:30<00:31, 6.22s/it, data_size=6, test_acc=0.492, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:30<00:31, 6.22s/it, data_size=6, test_acc=0.492, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:36<00:31, 6.22s/it, data_size=7, test_acc=0.481, train_acc=nan]Test 5: Data size 7: : 60%|██████ | 6/10 [00:37<00:25, 6.26s/it, data_size=7, test_acc=0.481, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [00:37<00:25, 6.26s/it, data_size=7, test_acc=0.481, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [00:43<00:25, 6.26s/it, data_size=8, test_acc=0.448, train_acc=nan]Test 5: Data size 8: : 70%|███████ | 7/10 [00:43<00:18, 6.30s/it, data_size=8, test_acc=0.448, train_acc=nan]Test 5: Data size 9: : 70%|███████ | 7/10 [00:43<00:18, 6.30s/it, data_size=8, test_acc=0.448, train_acc=nan]Test 5: Data size 9: : 70%|███████ | 7/10 [00:49<00:18, 6.30s/it, data_size=9, test_acc=0.434, train_acc=nan]Test 5: Data size 9: : 80%|████████ | 8/10 [00:50<00:12, 6.41s/it, data_size=9, test_acc=0.434, train_acc=nan]Test 5: Data size 10: : 80%|████████ | 8/10 [00:50<00:12, 6.41s/it, data_size=9, test_acc=0.434, train_acc=nan]Test 5: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.41s/it, data_size=10, test_acc=0.42, train_acc=nan]Test 5: Data size 10: : 90%|█████████ | 9/10 [00:56<00:06, 6.51s/it, data_size=10, test_acc=0.42, train_acc=nan]Test 5: Data size 11: : 90%|█████████ | 9/10 [00:56<00:06, 6.51s/it, data_size=10, test_acc=0.42, train_acc=nan]Test 5: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.51s/it, data_size=11, test_acc=0.413, train_acc=nan]Test 5: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.62s/it, data_size=11, test_acc=0.413, train_acc=nan]Test 5: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.37s/it, data_size=11, test_acc=0.413, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 2: : 10%|█ | 1/10 [00:05<00:53, 5.96s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:05<00:53, 5.96s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:11<00:53, 5.96s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 20%|██ | 2/10 [00:12<00:48, 6.03s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:12<00:48, 6.03s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:17<00:48, 6.03s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 30%|███ | 3/10 [00:18<00:42, 6.02s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:18<00:42, 6.02s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:24<00:42, 6.02s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 40%|████ | 4/10 [00:24<00:36, 6.07s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:24<00:36, 6.07s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.07s/it, data_size=6, test_acc=0.38, train_acc=nan]Test 6: Data size 6: : 50%|█████ | 5/10 [00:30<00:30, 6.13s/it, data_size=6, test_acc=0.38, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:30<00:30, 6.13s/it, data_size=6, test_acc=0.38, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:36<00:30, 6.13s/it, data_size=7, test_acc=0.488, train_acc=nan]Test 6: Data size 7: : 60%|██████ | 6/10 [00:36<00:24, 6.19s/it, data_size=7, test_acc=0.488, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:36<00:24, 6.19s/it, data_size=7, test_acc=0.488, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:42<00:24, 6.19s/it, data_size=8, test_acc=0.4, train_acc=nan] Test 6: Data size 8: : 70%|███████ | 7/10 [00:43<00:18, 6.22s/it, data_size=8, test_acc=0.4, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:43<00:18, 6.22s/it, data_size=8, test_acc=0.4, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:49<00:18, 6.22s/it, data_size=9, test_acc=0.433, train_acc=nan]Test 6: Data size 9: : 80%|████████ | 8/10 [00:49<00:12, 6.36s/it, data_size=9, test_acc=0.433, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [00:49<00:12, 6.36s/it, data_size=9, test_acc=0.433, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [00:56<00:12, 6.36s/it, data_size=10, test_acc=0.435, train_acc=nan]Test 6: Data size 10: : 90%|█████████ | 9/10 [00:56<00:06, 6.47s/it, data_size=10, test_acc=0.435, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [00:56<00:06, 6.47s/it, data_size=10, test_acc=0.435, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [01:03<00:06, 6.47s/it, data_size=11, test_acc=0.408, train_acc=nan]Test 6: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.57s/it, data_size=11, test_acc=0.408, train_acc=nan]Test 6: Data size 11: : 100%|██████████| 10/10 [01:03<00:00, 6.32s/it, data_size=11, test_acc=0.408, train_acc=nan]
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working on model Multimodal-middle-fusion-model-based-on-AlexNet with CLUSTER_MARGIN
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label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 0: Data size 2: : 0%| | 0/10 [01:05<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 10%|█ | 1/10 [01:06<09:54, 66.08s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [01:06<09:54, 66.08s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [01:11<09:54, 66.08s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 20%|██ | 2/10 [01:11<04:03, 30.39s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [01:11<04:03, 30.39s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [01:16<04:03, 30.39s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 30%|███ | 3/10 [01:16<02:13, 19.00s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [01:16<02:13, 19.00s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [01:22<02:13, 19.00s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 40%|████ | 4/10 [01:22<01:22, 13.67s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [01:22<01:22, 13.67s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [01:27<01:22, 13.67s/it, data_size=6, test_acc=0.457, train_acc=nan]Test 0: Data size 6: : 50%|█████ | 5/10 [01:28<00:53, 10.75s/it, data_size=6, test_acc=0.457, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [01:28<00:53, 10.75s/it, data_size=6, test_acc=0.457, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [01:33<00:53, 10.75s/it, data_size=7, test_acc=0.482, train_acc=nan]Test 0: Data size 7: : 60%|██████ | 6/10 [01:33<00:36, 9.03s/it, data_size=7, test_acc=0.482, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [01:33<00:36, 9.03s/it, data_size=7, test_acc=0.482, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [01:39<00:36, 9.03s/it, data_size=8, test_acc=0.25, train_acc=nan] Test 0: Data size 8: : 70%|███████ | 7/10 [01:39<00:23, 7.94s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [01:39<00:23, 7.94s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [01:45<00:23, 7.94s/it, data_size=9, test_acc=0.489, train_acc=nan]Test 0: Data size 9: : 80%|████████ | 8/10 [01:45<00:14, 7.33s/it, data_size=9, test_acc=0.489, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [01:45<00:14, 7.33s/it, data_size=9, test_acc=0.489, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [01:51<00:14, 7.33s/it, data_size=10, test_acc=0.457, train_acc=nan]Test 0: Data size 10: : 90%|█████████ | 9/10 [01:51<00:06, 6.95s/it, data_size=10, test_acc=0.457, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [01:51<00:06, 6.95s/it, data_size=10, test_acc=0.457, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [01:57<00:06, 6.95s/it, data_size=11, test_acc=0.47, train_acc=nan] Test 0: Data size 11: : 100%|██████████| 10/10 [01:57<00:00, 6.70s/it, data_size=11, test_acc=0.47, train_acc=nan]Test 0: Data size 11: : 100%|██████████| 10/10 [01:57<00:00, 11.77s/it, data_size=11, test_acc=0.47, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 1: Data size 2: : 0%| | 0/10 [01:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 2: : 10%|█ | 1/10 [01:06<09:56, 66.31s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [01:06<09:56, 66.31s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [01:11<09:56, 66.31s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 20%|██ | 2/10 [01:11<04:03, 30.47s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [01:11<04:03, 30.47s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [01:17<04:03, 30.47s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 30%|███ | 3/10 [01:17<02:13, 19.08s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [01:17<02:13, 19.08s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [01:22<02:13, 19.08s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 40%|████ | 4/10 [01:22<01:22, 13.70s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [01:22<01:22, 13.70s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [01:28<01:22, 13.70s/it, data_size=6, test_acc=0.394, train_acc=nan]Test 1: Data size 6: : 50%|█████ | 5/10 [01:28<00:53, 10.75s/it, data_size=6, test_acc=0.394, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [01:28<00:53, 10.75s/it, data_size=6, test_acc=0.394, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [01:33<00:53, 10.75s/it, data_size=7, test_acc=0.48, train_acc=nan] Test 1: Data size 7: : 60%|██████ | 6/10 [01:33<00:36, 9.00s/it, data_size=7, test_acc=0.48, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [01:33<00:36, 9.00s/it, data_size=7, test_acc=0.48, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [01:39<00:36, 9.00s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 70%|███████ | 7/10 [01:39<00:23, 7.97s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [01:39<00:23, 7.97s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [01:45<00:23, 7.97s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 1: Data size 9: : 80%|████████ | 8/10 [01:45<00:14, 7.36s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 1: Data size 10: : 80%|████████ | 8/10 [01:45<00:14, 7.36s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 1: Data size 10: : 80%|████████ | 8/10 [01:51<00:14, 7.36s/it, data_size=10, test_acc=0.5, train_acc=0.5] Test 1: Data size 10: : 90%|█████████ | 9/10 [01:51<00:06, 6.97s/it, data_size=10, test_acc=0.5, train_acc=0.5]Test 1: Data size 11: : 90%|█████████ | 9/10 [01:51<00:06, 6.97s/it, data_size=10, test_acc=0.5, train_acc=0.5]Test 1: Data size 11: : 90%|█████████ | 9/10 [01:57<00:06, 6.97s/it, data_size=11, test_acc=0.653, train_acc=0.667]Test 1: Data size 11: : 100%|██████████| 10/10 [01:57<00:00, 6.73s/it, data_size=11, test_acc=0.653, train_acc=0.667]Test 1: Data size 11: : 100%|██████████| 10/10 [01:57<00:00, 11.80s/it, data_size=11, test_acc=0.653, train_acc=0.667]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 2: Data size 2: : 0%| | 0/10 [01:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 2: : 10%|█ | 1/10 [01:06<09:57, 66.44s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [01:06<09:57, 66.44s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [01:11<09:57, 66.44s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 20%|██ | 2/10 [01:11<04:04, 30.53s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [01:11<04:04, 30.53s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [01:17<04:04, 30.53s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 30%|███ | 3/10 [01:17<02:13, 19.11s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [01:17<02:13, 19.11s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [01:22<02:13, 19.11s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 40%|████ | 4/10 [01:22<01:22, 13.79s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [01:22<01:22, 13.79s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [01:28<01:22, 13.79s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 50%|█████ | 5/10 [01:28<00:54, 10.85s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [01:28<00:54, 10.85s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [01:34<00:54, 10.85s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 2: Data size 7: : 60%|██████ | 6/10 [01:34<00:36, 9.09s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 2: Data size 8: : 60%|██████ | 6/10 [01:34<00:36, 9.09s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 2: Data size 8: : 60%|██████ | 6/10 [01:40<00:36, 9.09s/it, data_size=8, test_acc=0.341, train_acc=0.5]Test 2: Data size 8: : 70%|███████ | 7/10 [01:40<00:24, 8.03s/it, data_size=8, test_acc=0.341, train_acc=0.5]Test 2: Data size 9: : 70%|███████ | 7/10 [01:40<00:24, 8.03s/it, data_size=8, test_acc=0.341, train_acc=0.5]Test 2: Data size 9: : 70%|███████ | 7/10 [01:46<00:24, 8.03s/it, data_size=9, test_acc=0.324, train_acc=0.417]Test 2: Data size 9: : 80%|████████ | 8/10 [01:46<00:14, 7.41s/it, data_size=9, test_acc=0.324, train_acc=0.417]Test 2: Data size 10: : 80%|████████ | 8/10 [01:46<00:14, 7.41s/it, data_size=9, test_acc=0.324, train_acc=0.417]Test 2: Data size 10: : 80%|████████ | 8/10 [01:52<00:14, 7.41s/it, data_size=10, test_acc=0.302, train_acc=0.375]Test 2: Data size 10: : 90%|█████████ | 9/10 [01:52<00:07, 7.02s/it, data_size=10, test_acc=0.302, train_acc=0.375]Test 2: Data size 11: : 90%|█████████ | 9/10 [01:52<00:07, 7.02s/it, data_size=10, test_acc=0.302, train_acc=0.375]Test 2: Data size 11: : 90%|█████████ | 9/10 [01:58<00:07, 7.02s/it, data_size=11, test_acc=0.438, train_acc=0.438]Test 2: Data size 11: : 100%|██████████| 10/10 [01:58<00:00, 6.76s/it, data_size=11, test_acc=0.438, train_acc=0.438]Test 2: Data size 11: : 100%|██████████| 10/10 [01:58<00:00, 11.86s/it, data_size=11, test_acc=0.438, train_acc=0.438]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 3: Data size 2: : 0%| | 0/10 [01:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 2: : 10%|█ | 1/10 [01:06<09:57, 66.41s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [01:06<09:57, 66.41s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [01:11<09:57, 66.41s/it, data_size=3, test_acc=0.331, train_acc=nan]Test 3: Data size 3: : 20%|██ | 2/10 [01:11<04:04, 30.53s/it, data_size=3, test_acc=0.331, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [01:11<04:04, 30.53s/it, data_size=3, test_acc=0.331, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [01:17<04:04, 30.53s/it, data_size=4, test_acc=0.286, train_acc=nan]Test 3: Data size 4: : 30%|███ | 3/10 [01:17<02:13, 19.12s/it, data_size=4, test_acc=0.286, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [01:17<02:13, 19.12s/it, data_size=4, test_acc=0.286, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [01:22<02:13, 19.12s/it, data_size=5, test_acc=0.513, train_acc=nan]Test 3: Data size 5: : 40%|████ | 4/10 [01:23<01:22, 13.80s/it, data_size=5, test_acc=0.513, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [01:23<01:22, 13.80s/it, data_size=5, test_acc=0.513, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [01:28<01:22, 13.80s/it, data_size=6, test_acc=0.493, train_acc=nan]Test 3: Data size 6: : 50%|█████ | 5/10 [01:28<00:54, 10.86s/it, data_size=6, test_acc=0.493, train_acc=nan]Test 3: Data size 7: : 50%|█████ | 5/10 [01:28<00:54, 10.86s/it, data_size=6, test_acc=0.493, train_acc=nan]Test 3: Data size 7: : 50%|█████ | 5/10 [01:34<00:54, 10.86s/it, data_size=7, test_acc=0.654, train_acc=0.75]Test 3: Data size 7: : 60%|██████ | 6/10 [01:34<00:36, 9.11s/it, data_size=7, test_acc=0.654, train_acc=0.75]Test 3: Data size 8: : 60%|██████ | 6/10 [01:34<00:36, 9.11s/it, data_size=7, test_acc=0.654, train_acc=0.75]Test 3: Data size 8: : 60%|██████ | 6/10 [01:40<00:36, 9.11s/it, data_size=8, test_acc=0.563, train_acc=0.625]Test 3: Data size 8: : 70%|███████ | 7/10 [01:40<00:24, 8.02s/it, data_size=8, test_acc=0.563, train_acc=0.625]Test 3: Data size 9: : 70%|███████ | 7/10 [01:40<00:24, 8.02s/it, data_size=8, test_acc=0.563, train_acc=0.625]Test 3: Data size 9: : 70%|███████ | 7/10 [01:45<00:24, 8.02s/it, data_size=9, test_acc=0.528, train_acc=0.5] Test 3: Data size 9: : 80%|████████ | 8/10 [01:46<00:14, 7.35s/it, data_size=9, test_acc=0.528, train_acc=0.5]Test 3: Data size 10: : 80%|████████ | 8/10 [01:46<00:14, 7.35s/it, data_size=9, test_acc=0.528, train_acc=0.5]Test 3: Data size 10: : 80%|████████ | 8/10 [01:52<00:14, 7.35s/it, data_size=10, test_acc=0.618, train_acc=0.75]Test 3: Data size 10: : 90%|█████████ | 9/10 [01:52<00:06, 6.97s/it, data_size=10, test_acc=0.618, train_acc=0.75]Test 3: Data size 11: : 90%|█████████ | 9/10 [01:52<00:06, 6.97s/it, data_size=10, test_acc=0.618, train_acc=0.75]Test 3: Data size 11: : 90%|█████████ | 9/10 [01:58<00:06, 6.97s/it, data_size=11, test_acc=0.68, train_acc=0.708]Test 3: Data size 11: : 100%|██████████| 10/10 [01:58<00:00, 6.74s/it, data_size=11, test_acc=0.68, train_acc=0.708]Test 3: Data size 11: : 100%|██████████| 10/10 [01:58<00:00, 11.84s/it, data_size=11, test_acc=0.68, train_acc=0.708]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 4: Data size 2: : 0%| | 0/10 [01:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 10%|█ | 1/10 [01:06<09:56, 66.29s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [01:06<09:56, 66.29s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [01:11<09:56, 66.29s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 20%|██ | 2/10 [01:11<04:03, 30.49s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [01:11<04:03, 30.49s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [01:17<04:03, 30.49s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 30%|███ | 3/10 [01:17<02:13, 19.10s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [01:17<02:13, 19.10s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [01:22<02:13, 19.10s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 40%|████ | 4/10 [01:22<01:22, 13.74s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [01:22<01:22, 13.74s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [01:28<01:22, 13.74s/it, data_size=6, test_acc=0.299, train_acc=nan]Test 4: Data size 6: : 50%|█████ | 5/10 [01:28<00:54, 10.82s/it, data_size=6, test_acc=0.299, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [01:28<00:54, 10.82s/it, data_size=6, test_acc=0.299, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [01:34<00:54, 10.82s/it, data_size=7, test_acc=0.407, train_acc=nan]Test 4: Data size 7: : 60%|██████ | 6/10 [01:34<00:36, 9.12s/it, data_size=7, test_acc=0.407, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [01:34<00:36, 9.12s/it, data_size=7, test_acc=0.407, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [01:39<00:36, 9.12s/it, data_size=8, test_acc=0.446, train_acc=0.5]Test 4: Data size 8: : 70%|███████ | 7/10 [01:40<00:24, 8.04s/it, data_size=8, test_acc=0.446, train_acc=0.5]Test 4: Data size 9: : 70%|███████ | 7/10 [01:40<00:24, 8.04s/it, data_size=8, test_acc=0.446, train_acc=0.5]Test 4: Data size 9: : 70%|███████ | 7/10 [01:45<00:24, 8.04s/it, data_size=9, test_acc=0.447, train_acc=0.5]Test 4: Data size 9: : 80%|████████ | 8/10 [01:46<00:14, 7.38s/it, data_size=9, test_acc=0.447, train_acc=0.5]Test 4: Data size 10: : 80%|████████ | 8/10 [01:46<00:14, 7.38s/it, data_size=9, test_acc=0.447, train_acc=0.5]Test 4: Data size 10: : 80%|████████ | 8/10 [01:51<00:14, 7.38s/it, data_size=10, test_acc=0.489, train_acc=0.5]Test 4: Data size 10: : 90%|█████████ | 9/10 [01:52<00:06, 6.97s/it, data_size=10, test_acc=0.489, train_acc=0.5]Test 4: Data size 11: : 90%|█████████ | 9/10 [01:52<00:06, 6.97s/it, data_size=10, test_acc=0.489, train_acc=0.5]Test 4: Data size 11: : 90%|█████████ | 9/10 [01:58<00:06, 6.97s/it, data_size=11, test_acc=0.635, train_acc=0.583]Test 4: Data size 11: : 100%|██████████| 10/10 [01:58<00:00, 6.73s/it, data_size=11, test_acc=0.635, train_acc=0.583]Test 4: Data size 11: : 100%|██████████| 10/10 [01:58<00:00, 11.83s/it, data_size=11, test_acc=0.635, train_acc=0.583]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 5: Data size 2: : 0%| | 0/10 [01:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 2: : 10%|█ | 1/10 [01:06<09:57, 66.37s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [01:06<09:57, 66.37s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [01:11<09:57, 66.37s/it, data_size=3, test_acc=0.248, train_acc=nan]Test 5: Data size 3: : 20%|██ | 2/10 [01:11<04:04, 30.50s/it, data_size=3, test_acc=0.248, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [01:11<04:04, 30.50s/it, data_size=3, test_acc=0.248, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [01:17<04:04, 30.50s/it, data_size=4, test_acc=0.291, train_acc=nan]Test 5: Data size 4: : 30%|███ | 3/10 [01:17<02:13, 19.08s/it, data_size=4, test_acc=0.291, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [01:17<02:13, 19.08s/it, data_size=4, test_acc=0.291, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [01:22<02:13, 19.08s/it, data_size=5, test_acc=0.463, train_acc=nan]Test 5: Data size 5: : 40%|████ | 4/10 [01:22<01:22, 13.73s/it, data_size=5, test_acc=0.463, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [01:22<01:22, 13.73s/it, data_size=5, test_acc=0.463, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [01:28<01:22, 13.73s/it, data_size=6, test_acc=0.434, train_acc=nan]Test 5: Data size 6: : 50%|█████ | 5/10 [01:28<00:53, 10.78s/it, data_size=6, test_acc=0.434, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [01:28<00:53, 10.78s/it, data_size=6, test_acc=0.434, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [01:33<00:53, 10.78s/it, data_size=7, test_acc=0.441, train_acc=nan]Test 5: Data size 7: : 60%|██████ | 6/10 [01:34<00:36, 9.05s/it, data_size=7, test_acc=0.441, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [01:34<00:36, 9.05s/it, data_size=7, test_acc=0.441, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [01:39<00:36, 9.05s/it, data_size=8, test_acc=0.613, train_acc=nan]Test 5: Data size 8: : 70%|███████ | 7/10 [01:39<00:23, 7.98s/it, data_size=8, test_acc=0.613, train_acc=nan]Test 5: Data size 9: : 70%|███████ | 7/10 [01:39<00:23, 7.98s/it, data_size=8, test_acc=0.613, train_acc=nan]Test 5: Data size 9: : 70%|███████ | 7/10 [01:45<00:23, 7.98s/it, data_size=9, test_acc=0.472, train_acc=nan]Test 5: Data size 9: : 80%|████████ | 8/10 [01:45<00:14, 7.35s/it, data_size=9, test_acc=0.472, train_acc=nan]Test 5: Data size 10: : 80%|████████ | 8/10 [01:45<00:14, 7.35s/it, data_size=9, test_acc=0.472, train_acc=nan]Test 5: Data size 10: : 80%|████████ | 8/10 [01:51<00:14, 7.35s/it, data_size=10, test_acc=0.623, train_acc=nan]Test 5: Data size 10: : 90%|█████████ | 9/10 [01:51<00:06, 6.99s/it, data_size=10, test_acc=0.623, train_acc=nan]Test 5: Data size 11: : 90%|█████████ | 9/10 [01:51<00:06, 6.99s/it, data_size=10, test_acc=0.623, train_acc=nan]Test 5: Data size 11: : 90%|█████████ | 9/10 [01:58<00:06, 6.99s/it, data_size=11, test_acc=0.616, train_acc=nan]Test 5: Data size 11: : 100%|██████████| 10/10 [01:58<00:00, 6.74s/it, data_size=11, test_acc=0.616, train_acc=nan]Test 5: Data size 11: : 100%|██████████| 10/10 [01:58<00:00, 11.82s/it, data_size=11, test_acc=0.616, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 6: Data size 2: : 0%| | 0/10 [01:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 2: : 10%|█ | 1/10 [01:06<09:56, 66.25s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [01:06<09:56, 66.25s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [01:11<09:56, 66.25s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 20%|██ | 2/10 [01:11<04:03, 30.50s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [01:11<04:03, 30.50s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [01:17<04:03, 30.50s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 30%|███ | 3/10 [01:17<02:13, 19.11s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [01:17<02:13, 19.11s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [01:22<02:13, 19.11s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 40%|████ | 4/10 [01:22<01:22, 13.78s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [01:22<01:22, 13.78s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [01:28<01:22, 13.78s/it, data_size=6, test_acc=0.386, train_acc=nan]Test 6: Data size 6: : 50%|█████ | 5/10 [01:28<00:54, 10.86s/it, data_size=6, test_acc=0.386, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [01:28<00:54, 10.86s/it, data_size=6, test_acc=0.386, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [01:34<00:54, 10.86s/it, data_size=7, test_acc=0.433, train_acc=nan]Test 6: Data size 7: : 60%|██████ | 6/10 [01:34<00:36, 9.10s/it, data_size=7, test_acc=0.433, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [01:34<00:36, 9.10s/it, data_size=7, test_acc=0.433, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [01:39<00:36, 9.10s/it, data_size=8, test_acc=0.49, train_acc=nan] Test 6: Data size 8: : 70%|███████ | 7/10 [01:40<00:24, 8.02s/it, data_size=8, test_acc=0.49, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [01:40<00:24, 8.02s/it, data_size=8, test_acc=0.49, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [01:46<00:24, 8.02s/it, data_size=9, test_acc=0.475, train_acc=nan]Test 6: Data size 9: : 80%|████████ | 8/10 [01:46<00:14, 7.41s/it, data_size=9, test_acc=0.475, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [01:46<00:14, 7.41s/it, data_size=9, test_acc=0.475, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [01:52<00:14, 7.41s/it, data_size=10, test_acc=0.48, train_acc=nan]Test 6: Data size 10: : 90%|█████████ | 9/10 [01:52<00:07, 7.03s/it, data_size=10, test_acc=0.48, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [01:52<00:07, 7.03s/it, data_size=10, test_acc=0.48, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [01:58<00:07, 7.03s/it, data_size=11, test_acc=0.471, train_acc=nan]Test 6: Data size 11: : 100%|██████████| 10/10 [01:58<00:00, 6.77s/it, data_size=11, test_acc=0.471, train_acc=nan]Test 6: Data size 11: : 100%|██████████| 10/10 [01:58<00:00, 11.85s/it, data_size=11, test_acc=0.471, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 7: Data size 2: : 0%| | 0/10 [01:06<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 2: : 10%|█ | 1/10 [01:06<09:59, 66.59s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [01:06<09:59, 66.59s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [01:12<09:59, 66.59s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 20%|██ | 2/10 [01:12<04:05, 30.70s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [01:12<04:05, 30.70s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [01:17<04:05, 30.70s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 30%|███ | 3/10 [01:17<02:14, 19.25s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [01:17<02:14, 19.25s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [01:23<02:14, 19.25s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 40%|████ | 4/10 [01:23<01:23, 13.88s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [01:23<01:23, 13.88s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [01:29<01:23, 13.88s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 50%|█████ | 5/10 [01:29<00:54, 10.95s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [01:29<00:54, 10.95s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [01:34<00:54, 10.95s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 60%|██████ | 6/10 [01:35<00:36, 9.21s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 60%|██████ | 6/10 [01:35<00:36, 9.21s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 60%|██████ | 6/10 [01:40<00:36, 9.21s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 70%|███████ | 7/10 [01:40<00:24, 8.15s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 70%|███████ | 7/10 [01:40<00:24, 8.15s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 70%|███████ | 7/10 [01:46<00:24, 8.15s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 7: Data size 9: : 80%|████████ | 8/10 [01:47<00:15, 7.51s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 7: Data size 10: : 80%|████████ | 8/10 [01:47<00:15, 7.51s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 7: Data size 10: : 80%|████████ | 8/10 [01:53<00:15, 7.51s/it, data_size=10, test_acc=0.25, train_acc=0.25]Test 7: Data size 10: : 90%|█████████ | 9/10 [01:53<00:07, 7.11s/it, data_size=10, test_acc=0.25, train_acc=0.25]Test 7: Data size 11: : 90%|█████████ | 9/10 [01:53<00:07, 7.11s/it, data_size=10, test_acc=0.25, train_acc=0.25]Test 7: Data size 11: : 90%|█████████ | 9/10 [01:59<00:07, 7.11s/it, data_size=11, test_acc=0.387, train_acc=0.45]Test 7: Data size 11: : 100%|██████████| 10/10 [01:59<00:00, 6.86s/it, data_size=11, test_acc=0.387, train_acc=0.45]Test 7: Data size 11: : 100%|██████████| 10/10 [01:59<00:00, 11.97s/it, data_size=11, test_acc=0.387, train_acc=0.45]
working on model Multimodal-middle-fusion-model-based-on-AlexNet with BADGE
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 2: : 0%| | 0/10 [00:13<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 0%| | 0/10 [00:13<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]
Traceback (most recent call last):
File "/home/agaut/CS229-Project/experiments/experiment.py", line 168, in run_experiments
self.tester.test_model(curr_model)
File "/home/agaut/CS229-Project/test_framework/tester.py", line 165, in test_model
for mode_ind in range(len(train_x))
File "/home/agaut/CS229-Project/test_framework/tester.py", line 165, in <listcomp>
for mode_ind in range(len(train_x))
IndexError: arrays used as indices must be of integer (or boolean) type
Got exception arrays used as indices must be of integer (or boolean) type for model BADGE with stack trace:
None
working on model Multimodal-late-fusion-model-based-on-AlexNet with RANDOM
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 0: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 10%|█ | 1/10 [00:00<00:05, 1.79it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:00<00:05, 1.79it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:00<00:05, 1.79it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 20%|██ | 2/10 [00:01<00:04, 1.81it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:01<00:04, 1.81it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:01<00:04, 1.81it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 30%|███ | 3/10 [00:01<00:03, 1.82it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:01<00:03, 1.82it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:02<00:03, 1.82it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 40%|████ | 4/10 [00:02<00:03, 1.82it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:02<00:03, 1.82it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:02<00:03, 1.82it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 50%|█████ | 5/10 [00:02<00:02, 1.82it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [00:02<00:02, 1.82it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [00:03<00:02, 1.82it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 0: Data size 7: : 60%|██████ | 6/10 [00:03<00:02, 1.82it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [00:03<00:02, 1.82it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [00:03<00:02, 1.82it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 8: : 70%|███████ | 7/10 [00:03<00:01, 1.82it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [00:03<00:01, 1.82it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [00:04<00:01, 1.82it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 80%|████████ | 8/10 [00:04<00:01, 1.82it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [00:04<00:01, 1.82it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [00:04<00:01, 1.82it/s, data_size=10, test_acc=0.25, train_acc=nan]Test 0: Data size 10: : 90%|█████████ | 9/10 [00:04<00:00, 1.81it/s, data_size=10, test_acc=0.25, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [00:04<00:00, 1.81it/s, data_size=10, test_acc=0.25, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [00:05<00:00, 1.81it/s, data_size=11, test_acc=0.25, train_acc=nan]Test 0: Data size 11: : 100%|██████████| 10/10 [00:05<00:00, 1.80it/s, data_size=11, test_acc=0.25, train_acc=nan]Test 0: Data size 11: : 100%|██████████| 10/10 [00:05<00:00, 1.81it/s, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 2: : 10%|█ | 1/10 [00:00<00:04, 1.88it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:00<00:04, 1.88it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:00<00:04, 1.88it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 20%|██ | 2/10 [00:01<00:04, 1.86it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:01<00:04, 1.86it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:01<00:04, 1.86it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 30%|███ | 3/10 [00:01<00:03, 1.86it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:01<00:03, 1.86it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:02<00:03, 1.86it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 40%|████ | 4/10 [00:02<00:03, 1.85it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:02<00:03, 1.85it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:02<00:03, 1.85it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 50%|█████ | 5/10 [00:02<00:02, 1.85it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:02<00:02, 1.85it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:03<00:02, 1.85it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 60%|██████ | 6/10 [00:03<00:02, 1.85it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [00:03<00:02, 1.85it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [00:03<00:02, 1.85it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 70%|███████ | 7/10 [00:03<00:01, 1.85it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [00:03<00:01, 1.85it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [00:04<00:01, 1.85it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 80%|████████ | 8/10 [00:04<00:01, 1.85it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 80%|████████ | 8/10 [00:04<00:01, 1.85it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 80%|████████ | 8/10 [00:04<00:01, 1.85it/s, data_size=10, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 90%|█████████ | 9/10 [00:04<00:00, 1.85it/s, data_size=10, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 90%|█████████ | 9/10 [00:04<00:00, 1.85it/s, data_size=10, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 90%|█████████ | 9/10 [00:05<00:00, 1.85it/s, data_size=11, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 100%|██████████| 10/10 [00:05<00:00, 1.84it/s, data_size=11, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 100%|██████████| 10/10 [00:05<00:00, 1.85it/s, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 2: : 10%|█ | 1/10 [00:00<00:04, 1.87it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:00<00:04, 1.87it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:00<00:04, 1.87it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 20%|██ | 2/10 [00:01<00:04, 1.87it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:01<00:04, 1.87it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:01<00:04, 1.87it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 30%|███ | 3/10 [00:01<00:03, 1.87it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:01<00:03, 1.87it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:02<00:03, 1.87it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 40%|████ | 4/10 [00:02<00:03, 1.86it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:02<00:03, 1.86it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:02<00:03, 1.86it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 50%|█████ | 5/10 [00:02<00:02, 1.86it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [00:02<00:02, 1.86it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [00:03<00:02, 1.86it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 60%|██████ | 6/10 [00:03<00:02, 1.86it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 2: Data size 8: : 60%|██████ | 6/10 [00:03<00:02, 1.86it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 2: Data size 8: : 60%|██████ | 6/10 [00:03<00:02, 1.86it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 2: Data size 8: : 70%|███████ | 7/10 [00:03<00:01, 1.86it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 2: Data size 9: : 70%|███████ | 7/10 [00:03<00:01, 1.86it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 2: Data size 9: : 70%|███████ | 7/10 [00:04<00:01, 1.86it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 2: Data size 9: : 80%|████████ | 8/10 [00:04<00:01, 1.86it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 2: Data size 10: : 80%|████████ | 8/10 [00:04<00:01, 1.86it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 2: Data size 10: : 80%|████████ | 8/10 [00:04<00:01, 1.86it/s, data_size=10, test_acc=0.25, train_acc=nan]Test 2: Data size 10: : 90%|█████████ | 9/10 [00:04<00:00, 1.86it/s, data_size=10, test_acc=0.25, train_acc=nan]Test 2: Data size 11: : 90%|█████████ | 9/10 [00:04<00:00, 1.86it/s, data_size=10, test_acc=0.25, train_acc=nan]Test 2: Data size 11: : 90%|█████████ | 9/10 [00:05<00:00, 1.86it/s, data_size=11, test_acc=0.25, train_acc=0.25]Test 2: Data size 11: : 100%|██████████| 10/10 [00:05<00:00, 1.86it/s, data_size=11, test_acc=0.25, train_acc=0.25]Test 2: Data size 11: : 100%|██████████| 10/10 [00:05<00:00, 1.86it/s, data_size=11, test_acc=0.25, train_acc=0.25]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 2: : 10%|█ | 1/10 [00:00<00:04, 1.94it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:00<00:04, 1.94it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:00<00:04, 1.94it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 20%|██ | 2/10 [00:01<00:04, 1.93it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:01<00:04, 1.93it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:01<00:04, 1.93it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 30%|███ | 3/10 [00:01<00:03, 1.93it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:01<00:03, 1.93it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:01<00:03, 1.93it/s, data_size=5, test_acc=0.25, train_acc=0.25]Test 3: Data size 5: : 40%|████ | 4/10 [00:02<00:03, 1.92it/s, data_size=5, test_acc=0.25, train_acc=0.25]Test 3: Data size 6: : 40%|████ | 4/10 [00:02<00:03, 1.92it/s, data_size=5, test_acc=0.25, train_acc=0.25]Test 3: Data size 6: : 40%|████ | 4/10 [00:02<00:03, 1.92it/s, data_size=6, test_acc=0.25, train_acc=0.25]Test 3: Data size 6: : 50%|█████ | 5/10 [00:02<00:02, 1.91it/s, data_size=6, test_acc=0.25, train_acc=0.25]Test 3: Data size 7: : 50%|█████ | 5/10 [00:02<00:02, 1.91it/s, data_size=6, test_acc=0.25, train_acc=0.25]Test 3: Data size 7: : 50%|█████ | 5/10 [00:03<00:02, 1.91it/s, data_size=7, test_acc=0.25, train_acc=0.25]Test 3: Data size 7: : 60%|██████ | 6/10 [00:03<00:02, 1.91it/s, data_size=7, test_acc=0.25, train_acc=0.25]Test 3: Data size 8: : 60%|██████ | 6/10 [00:03<00:02, 1.91it/s, data_size=7, test_acc=0.25, train_acc=0.25]Test 3: Data size 8: : 60%|██████ | 6/10 [00:03<00:02, 1.91it/s, data_size=8, test_acc=0.25, train_acc=0.25]Test 3: Data size 8: : 70%|███████ | 7/10 [00:03<00:01, 1.90it/s, data_size=8, test_acc=0.25, train_acc=0.25]Test 3: Data size 9: : 70%|███████ | 7/10 [00:03<00:01, 1.90it/s, data_size=8, test_acc=0.25, train_acc=0.25]Test 3: Data size 9: : 70%|███████ | 7/10 [00:04<00:01, 1.90it/s, data_size=9, test_acc=0.25, train_acc=0.25]Test 3: Data size 9: : 80%|████████ | 8/10 [00:04<00:01, 1.90it/s, data_size=9, test_acc=0.25, train_acc=0.25]Test 3: Data size 10: : 80%|████████ | 8/10 [00:04<00:01, 1.90it/s, data_size=9, test_acc=0.25, train_acc=0.25]Test 3: Data size 10: : 80%|████████ | 8/10 [00:04<00:01, 1.90it/s, data_size=10, test_acc=0.25, train_acc=0.25]Test 3: Data size 10: : 90%|█████████ | 9/10 [00:04<00:00, 1.90it/s, data_size=10, test_acc=0.25, train_acc=0.25]Test 3: Data size 11: : 90%|█████████ | 9/10 [00:04<00:00, 1.90it/s, data_size=10, test_acc=0.25, train_acc=0.25]Test 3: Data size 11: : 90%|█████████ | 9/10 [00:05<00:00, 1.90it/s, data_size=11, test_acc=0.25, train_acc=0.25]Test 3: Data size 11: : 100%|██████████| 10/10 [00:05<00:00, 1.90it/s, data_size=11, test_acc=0.25, train_acc=0.25]Test 3: Data size 11: : 100%|██████████| 10/10 [00:05<00:00, 1.91it/s, data_size=11, test_acc=0.25, train_acc=0.25]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 10%|█ | 1/10 [00:00<00:04, 1.87it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:00<00:04, 1.87it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:00<00:04, 1.87it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 20%|██ | 2/10 [00:01<00:04, 1.87it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:01<00:04, 1.87it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:01<00:04, 1.87it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 30%|███ | 3/10 [00:01<00:03, 1.87it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:01<00:03, 1.87it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:02<00:03, 1.87it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 40%|████ | 4/10 [00:02<00:03, 1.87it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:02<00:03, 1.87it/s, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:02<00:03, 1.87it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 50%|█████ | 5/10 [00:02<00:02, 1.86it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:02<00:02, 1.86it/s, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:03<00:02, 1.86it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 60%|██████ | 6/10 [00:03<00:02, 1.86it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:03<00:02, 1.86it/s, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:03<00:02, 1.86it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 70%|███████ | 7/10 [00:03<00:01, 1.85it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:03<00:01, 1.85it/s, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:04<00:01, 1.85it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 80%|████████ | 8/10 [00:04<00:01, 1.85it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [00:04<00:01, 1.85it/s, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [00:04<00:01, 1.85it/s, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 90%|█████████ | 9/10 [00:04<00:00, 1.85it/s, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 90%|█████████ | 9/10 [00:04<00:00, 1.85it/s, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 90%|█████████ | 9/10 [00:05<00:00, 1.85it/s, data_size=11, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 100%|██████████| 10/10 [00:05<00:00, 1.84it/s, data_size=11, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 100%|██████████| 10/10 [00:05<00:00, 1.85it/s, data_size=11, test_acc=0.25, train_acc=nan]
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0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 2: : 10%|█ | 1/10 [00:00<00:04, 1.87it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:00<00:04, 1.87it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:00<00:04, 1.87it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 20%|██ | 2/10 [00:01<00:04, 1.87it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:01<00:04, 1.87it/s, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:01<00:04, 1.87it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 30%|███ | 3/10 [00:01<00:03, 1.87it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:01<00:03, 1.87it/s, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:02<00:03, 1.87it/s, data_size=5, test_acc=0.25, train_acc=0.25]Test 7: Data size 5: : 40%|████ | 4/10 [00:02<00:03, 1.86it/s, data_size=5, test_acc=0.25, train_acc=0.25]Test 7: Data size 6: : 40%|████ | 4/10 [00:02<00:03, 1.86it/s, data_size=5, test_acc=0.25, train_acc=0.25]Test 7: Data size 6: : 40%|████ | 4/10 [00:02<00:03, 1.86it/s, data_size=6, test_acc=0.25, train_acc=0.25]Test 7: Data size 6: : 50%|█████ | 5/10 [00:02<00:02, 1.86it/s, data_size=6, test_acc=0.25, train_acc=0.25]Test 7: Data size 7: : 50%|█████ | 5/10 [00:02<00:02, 1.86it/s, data_size=6, test_acc=0.25, train_acc=0.25]Test 7: Data size 7: : 50%|█████ | 5/10 [00:03<00:02, 1.86it/s, data_size=7, test_acc=0.25, train_acc=0.25]Test 7: Data size 7: : 60%|██████ | 6/10 [00:03<00:02, 1.86it/s, data_size=7, test_acc=0.25, train_acc=0.25]Test 7: Data size 8: : 60%|██████ | 6/10 [00:03<00:02, 1.86it/s, data_size=7, test_acc=0.25, train_acc=0.25]Test 7: Data size 8: : 60%|██████ | 6/10 [00:03<00:02, 1.86it/s, data_size=8, test_acc=0.25, train_acc=0.25]Test 7: Data size 8: : 70%|███████ | 7/10 [00:03<00:01, 1.86it/s, data_size=8, test_acc=0.25, train_acc=0.25]Test 7: Data size 9: : 70%|███████ | 7/10 [00:03<00:01, 1.86it/s, data_size=8, test_acc=0.25, train_acc=0.25]Test 7: Data size 9: : 70%|███████ | 7/10 [00:04<00:01, 1.86it/s, data_size=9, test_acc=0.25, train_acc=0.25]Test 7: Data size 9: : 80%|████████ | 8/10 [00:04<00:01, 1.85it/s, data_size=9, test_acc=0.25, train_acc=0.25]Test 7: Data size 10: : 80%|████████ | 8/10 [00:04<00:01, 1.85it/s, data_size=9, test_acc=0.25, train_acc=0.25]Test 7: Data size 10: : 80%|████████ | 8/10 [00:04<00:01, 1.85it/s, data_size=10, test_acc=0.25, train_acc=0.25]Test 7: Data size 10: : 90%|█████████ | 9/10 [00:04<00:00, 1.85it/s, data_size=10, test_acc=0.25, train_acc=0.25]Test 7: Data size 11: : 90%|█████████ | 9/10 [00:04<00:00, 1.85it/s, data_size=10, test_acc=0.25, train_acc=0.25]Test 7: Data size 11: : 90%|█████████ | 9/10 [00:05<00:00, 1.85it/s, data_size=11, test_acc=0.25, train_acc=0.25]Test 7: Data size 11: : 100%|██████████| 10/10 [00:05<00:00, 1.85it/s, data_size=11, test_acc=0.25, train_acc=0.25]Test 7: Data size 11: : 100%|██████████| 10/10 [00:05<00:00, 1.86it/s, data_size=11, test_acc=0.25, train_acc=0.25]
working on model Multimodal-late-fusion-model-based-on-AlexNet with MIN_MAX
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 2: : 0%| | 0/10 [00:04<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 10%|█ | 1/10 [00:04<00:38, 4.24s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:04<00:38, 4.24s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:08<00:38, 4.24s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 20%|██ | 2/10 [00:08<00:33, 4.24s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:08<00:33, 4.24s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:12<00:33, 4.24s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 30%|███ | 3/10 [00:12<00:29, 4.23s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:12<00:29, 4.23s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:16<00:29, 4.23s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 40%|████ | 4/10 [00:16<00:25, 4.24s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:16<00:25, 4.24s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:21<00:25, 4.24s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 50%|█████ | 5/10 [00:21<00:21, 4.24s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [00:21<00:21, 4.24s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [00:25<00:21, 4.24s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 0: Data size 7: : 60%|██████ | 6/10 [00:25<00:16, 4.24s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [00:25<00:16, 4.24s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [00:29<00:16, 4.24s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 8: : 70%|███████ | 7/10 [00:29<00:12, 4.24s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [00:29<00:12, 4.24s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [00:33<00:12, 4.24s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 80%|████████ | 8/10 [00:33<00:08, 4.24s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [00:33<00:08, 4.24s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [00:38<00:08, 4.24s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 0: Data size 10: : 90%|█████████ | 9/10 [00:38<00:04, 4.24s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [00:38<00:04, 4.24s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [00:42<00:04, 4.24s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 0: Data size 11: : 100%|██████████| 10/10 [00:42<00:00, 4.23s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 0: Data size 11: : 100%|██████████| 10/10 [00:42<00:00, 4.24s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:03<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 2: : 10%|█ | 1/10 [00:04<00:36, 4.06s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:04<00:36, 4.06s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:07<00:36, 4.06s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 20%|██ | 2/10 [00:08<00:32, 4.06s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:08<00:32, 4.06s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:12<00:32, 4.06s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 30%|███ | 3/10 [00:12<00:28, 4.06s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:12<00:28, 4.06s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:16<00:28, 4.06s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.06s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.06s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:20<00:24, 4.06s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.06s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.06s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:24<00:20, 4.06s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.08s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.08s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.08s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 70%|███████ | 7/10 [00:28<00:12, 4.08s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [00:28<00:12, 4.08s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [00:32<00:12, 4.08s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 80%|████████ | 8/10 [00:32<00:08, 4.07s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 80%|████████ | 8/10 [00:32<00:08, 4.07s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 80%|████████ | 8/10 [00:36<00:08, 4.07s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 90%|█████████ | 9/10 [00:36<00:04, 4.07s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 90%|█████████ | 9/10 [00:36<00:04, 4.07s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 90%|█████████ | 9/10 [00:40<00:04, 4.07s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.07s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.07s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:03<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 2: : 10%|█ | 1/10 [00:04<00:36, 4.03s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:04<00:36, 4.03s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:07<00:36, 4.03s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 20%|██ | 2/10 [00:08<00:32, 4.03s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:08<00:32, 4.03s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:11<00:32, 4.03s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 30%|███ | 3/10 [00:12<00:28, 4.03s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:12<00:28, 4.03s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:15<00:28, 4.03s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.02s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.02s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:19<00:24, 4.02s/it, data_size=6, test_acc=0.25, train_acc=0.25]Test 2: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.02s/it, data_size=6, test_acc=0.25, train_acc=0.25]Test 2: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.02s/it, data_size=6, test_acc=0.25, train_acc=0.25]Test 2: Data size 7: : 50%|█████ | 5/10 [00:23<00:20, 4.02s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 2: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.02s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 2: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.02s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 2: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.02s/it, data_size=8, test_acc=0.25, train_acc=0.25]Test 2: Data size 8: : 70%|███████ | 7/10 [00:28<00:12, 4.02s/it, data_size=8, test_acc=0.25, train_acc=0.25]Test 2: Data size 9: : 70%|███████ | 7/10 [00:28<00:12, 4.02s/it, data_size=8, test_acc=0.25, train_acc=0.25]Test 2: Data size 9: : 70%|███████ | 7/10 [00:32<00:12, 4.02s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 2: Data size 9: : 80%|████████ | 8/10 [00:32<00:08, 4.03s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 2: Data size 10: : 80%|████████ | 8/10 [00:32<00:08, 4.03s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 2: Data size 10: : 80%|████████ | 8/10 [00:36<00:08, 4.03s/it, data_size=10, test_acc=0.25, train_acc=0.25]Test 2: Data size 10: : 90%|█████████ | 9/10 [00:36<00:04, 4.03s/it, data_size=10, test_acc=0.25, train_acc=0.25]Test 2: Data size 11: : 90%|█████████ | 9/10 [00:36<00:04, 4.03s/it, data_size=10, test_acc=0.25, train_acc=0.25]Test 2: Data size 11: : 90%|█████████ | 9/10 [00:40<00:04, 4.03s/it, data_size=11, test_acc=0.25, train_acc=0.25]Test 2: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.03s/it, data_size=11, test_acc=0.25, train_acc=0.25]Test 2: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.03s/it, data_size=11, test_acc=0.25, train_acc=0.25]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:04<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 2: : 10%|█ | 1/10 [00:04<00:37, 4.14s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:04<00:37, 4.14s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:08<00:37, 4.14s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 20%|██ | 2/10 [00:08<00:33, 4.13s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:08<00:33, 4.13s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:12<00:33, 4.13s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 30%|███ | 3/10 [00:12<00:28, 4.14s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:12<00:28, 4.14s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:16<00:28, 4.14s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.15s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.15s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [00:20<00:24, 4.15s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.15s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 3: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.15s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 3: Data size 7: : 50%|█████ | 5/10 [00:24<00:20, 4.15s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 3: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.15s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 3: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.15s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 3: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.15s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 3: Data size 8: : 70%|███████ | 7/10 [00:29<00:12, 4.14s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 3: Data size 9: : 70%|███████ | 7/10 [00:29<00:12, 4.14s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 3: Data size 9: : 70%|███████ | 7/10 [00:33<00:12, 4.14s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 3: Data size 9: : 80%|████████ | 8/10 [00:33<00:08, 4.14s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 3: Data size 10: : 80%|████████ | 8/10 [00:33<00:08, 4.14s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 3: Data size 10: : 80%|████████ | 8/10 [00:37<00:08, 4.14s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 3: Data size 10: : 90%|█████████ | 9/10 [00:37<00:04, 4.15s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 3: Data size 11: : 90%|█████████ | 9/10 [00:37<00:04, 4.15s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 3: Data size 11: : 90%|█████████ | 9/10 [00:41<00:04, 4.15s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 3: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.14s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 3: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.14s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:03<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 10%|█ | 1/10 [00:04<00:36, 4.09s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:04<00:36, 4.09s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:08<00:36, 4.09s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 20%|██ | 2/10 [00:08<00:32, 4.10s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:08<00:32, 4.10s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:12<00:32, 4.10s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 30%|███ | 3/10 [00:12<00:28, 4.10s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:12<00:28, 4.10s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:16<00:28, 4.10s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.10s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.10s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:20<00:24, 4.10s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.09s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.09s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:24<00:20, 4.09s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.10s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.10s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.10s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 70%|███████ | 7/10 [00:28<00:12, 4.10s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:28<00:12, 4.10s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:32<00:12, 4.10s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 80%|████████ | 8/10 [00:32<00:08, 4.10s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [00:32<00:08, 4.10s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [00:36<00:08, 4.10s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 90%|█████████ | 9/10 [00:36<00:04, 4.10s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 90%|█████████ | 9/10 [00:36<00:04, 4.10s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 90%|█████████ | 9/10 [00:40<00:04, 4.10s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.10s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.10s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:04<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 2: : 10%|█ | 1/10 [00:04<00:37, 4.21s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:04<00:37, 4.21s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:08<00:37, 4.21s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 20%|██ | 2/10 [00:08<00:33, 4.21s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:08<00:33, 4.21s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:12<00:33, 4.21s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 30%|███ | 3/10 [00:12<00:29, 4.20s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:12<00:29, 4.20s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:16<00:29, 4.20s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 5: : 40%|████ | 4/10 [00:16<00:25, 4.21s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:16<00:25, 4.21s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:20<00:25, 4.21s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 50%|█████ | 5/10 [00:21<00:21, 4.21s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:21<00:21, 4.21s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:25<00:21, 4.21s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 60%|██████ | 6/10 [00:25<00:16, 4.20s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [00:25<00:16, 4.20s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [00:29<00:16, 4.20s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 5: Data size 8: : 70%|███████ | 7/10 [00:29<00:12, 4.20s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 5: Data size 9: : 70%|███████ | 7/10 [00:29<00:12, 4.20s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 5: Data size 9: : 70%|███████ | 7/10 [00:33<00:12, 4.20s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 5: Data size 9: : 80%|████████ | 8/10 [00:33<00:08, 4.20s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 5: Data size 10: : 80%|████████ | 8/10 [00:33<00:08, 4.20s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 5: Data size 10: : 80%|████████ | 8/10 [00:37<00:08, 4.20s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 5: Data size 10: : 90%|█████████ | 9/10 [00:37<00:04, 4.20s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 5: Data size 11: : 90%|█████████ | 9/10 [00:37<00:04, 4.20s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 5: Data size 11: : 90%|█████████ | 9/10 [00:41<00:04, 4.20s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 5: Data size 11: : 100%|██████████| 10/10 [00:42<00:00, 4.20s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 5: Data size 11: : 100%|██████████| 10/10 [00:42<00:00, 4.20s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:03<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 2: : 10%|█ | 1/10 [00:04<00:36, 4.09s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:04<00:36, 4.09s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:08<00:36, 4.09s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 20%|██ | 2/10 [00:08<00:32, 4.10s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:08<00:32, 4.10s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:12<00:32, 4.10s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 30%|███ | 3/10 [00:12<00:28, 4.10s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:12<00:28, 4.10s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:16<00:28, 4.10s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.10s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.10s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:20<00:24, 4.10s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.10s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.10s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:24<00:20, 4.10s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 6: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.10s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.10s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.10s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 6: Data size 8: : 70%|███████ | 7/10 [00:28<00:12, 4.10s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:28<00:12, 4.10s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:32<00:12, 4.10s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 6: Data size 9: : 80%|████████ | 8/10 [00:32<00:08, 4.10s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [00:32<00:08, 4.10s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [00:36<00:08, 4.10s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 6: Data size 10: : 90%|█████████ | 9/10 [00:36<00:04, 4.09s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [00:36<00:04, 4.09s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [00:40<00:04, 4.09s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.10s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.10s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:03<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 2: : 10%|█ | 1/10 [00:04<00:36, 4.10s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:04<00:36, 4.10s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:08<00:36, 4.10s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 20%|██ | 2/10 [00:08<00:32, 4.10s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:08<00:32, 4.10s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:12<00:32, 4.10s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 30%|███ | 3/10 [00:12<00:28, 4.10s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:12<00:28, 4.10s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:16<00:28, 4.10s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.11s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.11s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [00:20<00:24, 4.11s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.10s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.10s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [00:24<00:20, 4.10s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.10s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.10s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.10s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 70%|███████ | 7/10 [00:28<00:12, 4.10s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 70%|███████ | 7/10 [00:28<00:12, 4.10s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 70%|███████ | 7/10 [00:32<00:12, 4.10s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 80%|████████ | 8/10 [00:32<00:08, 4.10s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 10: : 80%|████████ | 8/10 [00:32<00:08, 4.10s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 10: : 80%|████████ | 8/10 [00:36<00:08, 4.10s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 7: Data size 10: : 90%|█████████ | 9/10 [00:36<00:04, 4.11s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 7: Data size 11: : 90%|█████████ | 9/10 [00:36<00:04, 4.11s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 7: Data size 11: : 90%|█████████ | 9/10 [00:40<00:04, 4.11s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 7: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.11s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 7: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.10s/it, data_size=11, test_acc=0.25, train_acc=nan]
working on model Multimodal-late-fusion-model-based-on-AlexNet with MIN_MARGIN
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0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:04<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 2: : 10%|█ | 1/10 [00:04<00:37, 4.20s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:04<00:37, 4.20s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:08<00:37, 4.20s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 20%|██ | 2/10 [00:08<00:33, 4.20s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:08<00:33, 4.20s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:12<00:33, 4.20s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 30%|███ | 3/10 [00:12<00:29, 4.20s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:12<00:29, 4.20s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:16<00:29, 4.20s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 40%|████ | 4/10 [00:16<00:25, 4.20s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:16<00:25, 4.20s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:20<00:25, 4.20s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.20s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.20s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [00:25<00:20, 4.20s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 60%|██████ | 6/10 [00:25<00:16, 4.19s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 2: Data size 8: : 60%|██████ | 6/10 [00:25<00:16, 4.19s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 2: Data size 8: : 60%|██████ | 6/10 [00:29<00:16, 4.19s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 2: Data size 8: : 70%|███████ | 7/10 [00:29<00:12, 4.19s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 2: Data size 9: : 70%|███████ | 7/10 [00:29<00:12, 4.19s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 2: Data size 9: : 70%|███████ | 7/10 [00:33<00:12, 4.19s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 2: Data size 9: : 80%|████████ | 8/10 [00:33<00:08, 4.19s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 2: Data size 10: : 80%|████████ | 8/10 [00:33<00:08, 4.19s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 2: Data size 10: : 80%|████████ | 8/10 [00:37<00:08, 4.19s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 2: Data size 10: : 90%|█████████ | 9/10 [00:37<00:04, 4.19s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 2: Data size 11: : 90%|█████████ | 9/10 [00:37<00:04, 4.19s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 2: Data size 11: : 90%|█████████ | 9/10 [00:41<00:04, 4.19s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 2: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.19s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 2: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.19s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:03<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 2: : 10%|█ | 1/10 [00:04<00:37, 4.12s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:04<00:37, 4.12s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:08<00:37, 4.12s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 20%|██ | 2/10 [00:08<00:32, 4.12s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:08<00:32, 4.12s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:12<00:32, 4.12s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 30%|███ | 3/10 [00:12<00:28, 4.12s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:12<00:28, 4.12s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:16<00:28, 4.12s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.13s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.13s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [00:20<00:24, 4.13s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.12s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 3: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.12s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 3: Data size 7: : 50%|█████ | 5/10 [00:24<00:20, 4.12s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 3: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.13s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 3: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.13s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 3: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.13s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 3: Data size 8: : 70%|███████ | 7/10 [00:28<00:12, 4.13s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 3: Data size 9: : 70%|███████ | 7/10 [00:28<00:12, 4.13s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 3: Data size 9: : 70%|███████ | 7/10 [00:32<00:12, 4.13s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 3: Data size 9: : 80%|████████ | 8/10 [00:33<00:08, 4.13s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 3: Data size 10: : 80%|████████ | 8/10 [00:33<00:08, 4.13s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 3: Data size 10: : 80%|████████ | 8/10 [00:37<00:08, 4.13s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 3: Data size 10: : 90%|█████████ | 9/10 [00:37<00:04, 4.13s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 3: Data size 11: : 90%|█████████ | 9/10 [00:37<00:04, 4.13s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 3: Data size 11: : 90%|█████████ | 9/10 [00:41<00:04, 4.13s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 3: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.13s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 3: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.13s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:03<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 10%|█ | 1/10 [00:04<00:36, 4.07s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:04<00:36, 4.07s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:08<00:36, 4.07s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 20%|██ | 2/10 [00:08<00:32, 4.06s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:08<00:32, 4.06s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:12<00:32, 4.06s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 30%|███ | 3/10 [00:12<00:28, 4.07s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:12<00:28, 4.07s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:16<00:28, 4.07s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.07s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.07s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:20<00:24, 4.07s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.07s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.07s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:24<00:20, 4.07s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.07s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.07s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.07s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 70%|███████ | 7/10 [00:28<00:12, 4.07s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:28<00:12, 4.07s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:32<00:12, 4.07s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 80%|████████ | 8/10 [00:32<00:08, 4.07s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [00:32<00:08, 4.07s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [00:36<00:08, 4.07s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 90%|█████████ | 9/10 [00:36<00:04, 4.07s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 90%|█████████ | 9/10 [00:36<00:04, 4.07s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 90%|█████████ | 9/10 [00:40<00:04, 4.07s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.07s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.07s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:03<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 2: : 10%|█ | 1/10 [00:04<00:36, 4.03s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:04<00:36, 4.03s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:07<00:36, 4.03s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 20%|██ | 2/10 [00:08<00:32, 4.03s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:08<00:32, 4.03s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:11<00:32, 4.03s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 30%|███ | 3/10 [00:12<00:28, 4.03s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:12<00:28, 4.03s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:15<00:28, 4.03s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.03s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.03s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:19<00:24, 4.03s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.02s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.02s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:24<00:20, 4.02s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.03s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.03s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.03s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 5: Data size 8: : 70%|███████ | 7/10 [00:28<00:12, 4.03s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 5: Data size 9: : 70%|███████ | 7/10 [00:28<00:12, 4.03s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 5: Data size 9: : 70%|███████ | 7/10 [00:32<00:12, 4.03s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 5: Data size 9: : 80%|████████ | 8/10 [00:32<00:08, 4.03s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 5: Data size 10: : 80%|████████ | 8/10 [00:32<00:08, 4.03s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 5: Data size 10: : 80%|████████ | 8/10 [00:36<00:08, 4.03s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 5: Data size 10: : 90%|█████████ | 9/10 [00:36<00:04, 4.03s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 5: Data size 11: : 90%|█████████ | 9/10 [00:36<00:04, 4.03s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 5: Data size 11: : 90%|█████████ | 9/10 [00:40<00:04, 4.03s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 5: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.03s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 5: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.03s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:04<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 2: : 10%|█ | 1/10 [00:04<00:37, 4.16s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:04<00:37, 4.16s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:08<00:37, 4.16s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 20%|██ | 2/10 [00:08<00:33, 4.16s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:08<00:33, 4.16s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:12<00:33, 4.16s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 30%|███ | 3/10 [00:12<00:29, 4.16s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:12<00:29, 4.16s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:16<00:29, 4.16s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.15s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.15s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:20<00:24, 4.15s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.15s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.15s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:24<00:20, 4.15s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 6: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.15s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.15s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.15s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 6: Data size 8: : 70%|███████ | 7/10 [00:29<00:12, 4.16s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:29<00:12, 4.16s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:33<00:12, 4.16s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 6: Data size 9: : 80%|████████ | 8/10 [00:33<00:08, 4.16s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [00:33<00:08, 4.16s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [00:37<00:08, 4.16s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 6: Data size 10: : 90%|█████████ | 9/10 [00:37<00:04, 4.16s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [00:37<00:04, 4.16s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [00:41<00:04, 4.16s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.16s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.16s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:03<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 2: : 10%|█ | 1/10 [00:04<00:36, 4.07s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:04<00:36, 4.07s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:08<00:36, 4.07s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 20%|██ | 2/10 [00:08<00:32, 4.06s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:08<00:32, 4.06s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:12<00:32, 4.06s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 30%|███ | 3/10 [00:12<00:28, 4.06s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:12<00:28, 4.06s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:16<00:28, 4.06s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.06s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.06s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [00:20<00:24, 4.06s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.07s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.07s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [00:24<00:20, 4.07s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.07s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.07s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.07s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 70%|███████ | 7/10 [00:28<00:12, 4.07s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 70%|███████ | 7/10 [00:28<00:12, 4.07s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 70%|███████ | 7/10 [00:32<00:12, 4.07s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 80%|████████ | 8/10 [00:32<00:08, 4.08s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 10: : 80%|████████ | 8/10 [00:32<00:08, 4.08s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 10: : 80%|████████ | 8/10 [00:36<00:08, 4.08s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 7: Data size 10: : 90%|█████████ | 9/10 [00:36<00:04, 4.08s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 7: Data size 11: : 90%|█████████ | 9/10 [00:36<00:04, 4.08s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 7: Data size 11: : 90%|█████████ | 9/10 [00:40<00:04, 4.08s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 7: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.07s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 7: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.07s/it, data_size=11, test_acc=0.25, train_acc=nan]
working on model Multimodal-late-fusion-model-based-on-AlexNet with MAX_ENTROPY
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0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:03<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 2: : 10%|█ | 1/10 [00:04<00:36, 4.01s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:04<00:36, 4.01s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:07<00:36, 4.01s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 20%|██ | 2/10 [00:08<00:32, 4.01s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:08<00:32, 4.01s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:11<00:32, 4.01s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 30%|███ | 3/10 [00:12<00:28, 4.01s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:12<00:28, 4.01s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:15<00:28, 4.01s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.01s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.01s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:19<00:24, 4.01s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.01s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.01s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:23<00:20, 4.01s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.01s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.01s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [00:27<00:16, 4.01s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 70%|███████ | 7/10 [00:28<00:12, 4.01s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [00:28<00:12, 4.01s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [00:31<00:12, 4.01s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 80%|████████ | 8/10 [00:32<00:08, 4.01s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 80%|████████ | 8/10 [00:32<00:08, 4.01s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 80%|████████ | 8/10 [00:35<00:08, 4.01s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 90%|█████████ | 9/10 [00:36<00:04, 4.01s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 90%|█████████ | 9/10 [00:36<00:04, 4.01s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 90%|█████████ | 9/10 [00:40<00:04, 4.01s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.01s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 100%|██████████| 10/10 [00:40<00:00, 4.01s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:04<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 2: : 10%|█ | 1/10 [00:04<00:37, 4.21s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:04<00:37, 4.21s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:08<00:37, 4.21s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 20%|██ | 2/10 [00:08<00:33, 4.22s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:08<00:33, 4.22s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:12<00:33, 4.22s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 30%|███ | 3/10 [00:12<00:29, 4.21s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:12<00:29, 4.21s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 30%|███ | 3/10 [00:16<00:29, 4.21s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 5: : 40%|████ | 4/10 [00:16<00:25, 4.21s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:16<00:25, 4.21s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 40%|████ | 4/10 [00:20<00:25, 4.21s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 6: : 50%|█████ | 5/10 [00:21<00:21, 4.21s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [00:21<00:21, 4.21s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 50%|█████ | 5/10 [00:25<00:21, 4.21s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 2: Data size 7: : 60%|██████ | 6/10 [00:25<00:16, 4.21s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 2: Data size 8: : 60%|██████ | 6/10 [00:25<00:16, 4.21s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 2: Data size 8: : 60%|██████ | 6/10 [00:29<00:16, 4.21s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 2: Data size 8: : 70%|███████ | 7/10 [00:29<00:12, 4.21s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 2: Data size 9: : 70%|███████ | 7/10 [00:29<00:12, 4.21s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 2: Data size 9: : 70%|███████ | 7/10 [00:33<00:12, 4.21s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 2: Data size 9: : 80%|████████ | 8/10 [00:33<00:08, 4.20s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 2: Data size 10: : 80%|████████ | 8/10 [00:33<00:08, 4.20s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 2: Data size 10: : 80%|████████ | 8/10 [00:37<00:08, 4.20s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 2: Data size 10: : 90%|█████████ | 9/10 [00:37<00:04, 4.20s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 2: Data size 11: : 90%|█████████ | 9/10 [00:37<00:04, 4.20s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 2: Data size 11: : 90%|█████████ | 9/10 [00:41<00:04, 4.20s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 2: Data size 11: : 100%|██████████| 10/10 [00:42<00:00, 4.21s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 2: Data size 11: : 100%|██████████| 10/10 [00:42<00:00, 4.21s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:04<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 2: : 10%|█ | 1/10 [00:04<00:37, 4.13s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:04<00:37, 4.13s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:08<00:37, 4.13s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 20%|██ | 2/10 [00:08<00:33, 4.14s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:08<00:33, 4.14s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:12<00:33, 4.14s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 30%|███ | 3/10 [00:12<00:29, 4.14s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:12<00:29, 4.14s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 30%|███ | 3/10 [00:16<00:29, 4.14s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.14s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.14s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 40%|████ | 4/10 [00:20<00:24, 4.14s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 3: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.15s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 3: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.15s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 3: Data size 7: : 50%|█████ | 5/10 [00:24<00:20, 4.15s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 3: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.15s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 3: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.15s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 3: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.15s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 3: Data size 8: : 70%|███████ | 7/10 [00:29<00:12, 4.14s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 3: Data size 9: : 70%|███████ | 7/10 [00:29<00:12, 4.14s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 3: Data size 9: : 70%|███████ | 7/10 [00:33<00:12, 4.14s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 3: Data size 9: : 80%|████████ | 8/10 [00:33<00:08, 4.14s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 3: Data size 10: : 80%|████████ | 8/10 [00:33<00:08, 4.14s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 3: Data size 10: : 80%|████████ | 8/10 [00:37<00:08, 4.14s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 3: Data size 10: : 90%|█████████ | 9/10 [00:37<00:04, 4.14s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 3: Data size 11: : 90%|█████████ | 9/10 [00:37<00:04, 4.14s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 3: Data size 11: : 90%|█████████ | 9/10 [00:41<00:04, 4.14s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 3: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.14s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 3: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.14s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:03<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 10%|█ | 1/10 [00:04<00:37, 4.11s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:04<00:37, 4.11s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:08<00:37, 4.11s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 20%|██ | 2/10 [00:08<00:32, 4.11s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:08<00:32, 4.11s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:12<00:32, 4.11s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 30%|███ | 3/10 [00:12<00:28, 4.11s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:12<00:28, 4.11s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:16<00:28, 4.11s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.11s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.11s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:20<00:24, 4.11s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.15s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.15s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:24<00:20, 4.15s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.13s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.13s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.13s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 70%|███████ | 7/10 [00:28<00:12, 4.12s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:28<00:12, 4.12s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:32<00:12, 4.12s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 80%|████████ | 8/10 [00:32<00:08, 4.12s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [00:32<00:08, 4.12s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [00:36<00:08, 4.12s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 90%|█████████ | 9/10 [00:37<00:04, 4.12s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 90%|█████████ | 9/10 [00:37<00:04, 4.12s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 90%|█████████ | 9/10 [00:41<00:04, 4.12s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.11s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.12s/it, data_size=11, test_acc=0.25, train_acc=nan]
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0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:04<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 2: : 10%|█ | 1/10 [00:04<00:37, 4.14s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:04<00:37, 4.14s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:08<00:37, 4.14s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 20%|██ | 2/10 [00:08<00:33, 4.15s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:08<00:33, 4.15s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:12<00:33, 4.15s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 30%|███ | 3/10 [00:12<00:29, 4.15s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:12<00:29, 4.15s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:16<00:29, 4.15s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 40%|████ | 4/10 [00:16<00:24, 4.15s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:16<00:24, 4.15s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:20<00:24, 4.15s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 50%|█████ | 5/10 [00:20<00:20, 4.15s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:20<00:20, 4.15s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:24<00:20, 4.15s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 6: Data size 7: : 60%|██████ | 6/10 [00:24<00:16, 4.15s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:24<00:16, 4.15s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:28<00:16, 4.15s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 6: Data size 8: : 70%|███████ | 7/10 [00:29<00:12, 4.17s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:29<00:12, 4.17s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:33<00:12, 4.17s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 6: Data size 9: : 80%|████████ | 8/10 [00:33<00:08, 4.16s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [00:33<00:08, 4.16s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [00:37<00:08, 4.16s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 6: Data size 10: : 90%|█████████ | 9/10 [00:37<00:04, 4.16s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [00:37<00:04, 4.16s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [00:41<00:04, 4.16s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.15s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 100%|██████████| 10/10 [00:41<00:00, 4.15s/it, data_size=11, test_acc=0.25, train_acc=nan]
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working on model Multimodal-late-fusion-model-based-on-AlexNet with CLUSTER_MARGIN
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label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 0: Data size 2: : 0%| | 0/10 [00:16<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 10%|█ | 1/10 [00:16<02:25, 16.13s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:16<02:25, 16.13s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 10%|█ | 1/10 [00:20<02:25, 16.13s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 3: : 20%|██ | 2/10 [00:20<01:13, 9.15s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:20<01:13, 9.15s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 20%|██ | 2/10 [00:24<01:13, 9.15s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 4: : 30%|███ | 3/10 [00:24<00:48, 6.93s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:24<00:48, 6.93s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 30%|███ | 3/10 [00:28<00:48, 6.93s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 5: : 40%|████ | 4/10 [00:28<00:35, 5.88s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:28<00:35, 5.88s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 40%|████ | 4/10 [00:33<00:35, 5.88s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 0: Data size 6: : 50%|█████ | 5/10 [00:33<00:26, 5.30s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [00:33<00:26, 5.30s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 0: Data size 7: : 50%|█████ | 5/10 [00:37<00:26, 5.30s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 0: Data size 7: : 60%|██████ | 6/10 [00:37<00:19, 4.96s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [00:37<00:19, 4.96s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 0: Data size 8: : 60%|██████ | 6/10 [00:41<00:19, 4.96s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 8: : 70%|███████ | 7/10 [00:41<00:14, 4.75s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [00:41<00:14, 4.75s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 70%|███████ | 7/10 [00:46<00:14, 4.75s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 0: Data size 9: : 80%|████████ | 8/10 [00:46<00:09, 4.61s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [00:46<00:09, 4.61s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 0: Data size 10: : 80%|████████ | 8/10 [00:50<00:09, 4.61s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 0: Data size 10: : 90%|█████████ | 9/10 [00:50<00:04, 4.54s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [00:50<00:04, 4.54s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 0: Data size 11: : 90%|█████████ | 9/10 [00:54<00:04, 4.54s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 0: Data size 11: : 100%|██████████| 10/10 [00:54<00:00, 4.47s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 0: Data size 11: : 100%|██████████| 10/10 [00:54<00:00, 5.48s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 1: Data size 2: : 0%| | 0/10 [00:16<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 2: : 10%|█ | 1/10 [00:16<02:26, 16.32s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:16<02:26, 16.32s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 10%|█ | 1/10 [00:20<02:26, 16.32s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 3: : 20%|██ | 2/10 [00:20<01:14, 9.28s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:20<01:14, 9.28s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 20%|██ | 2/10 [00:24<01:14, 9.28s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 4: : 30%|███ | 3/10 [00:25<00:49, 7.03s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:25<00:49, 7.03s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 30%|███ | 3/10 [00:29<00:49, 7.03s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 5: : 40%|████ | 4/10 [00:29<00:35, 5.97s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:29<00:35, 5.97s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 40%|████ | 4/10 [00:33<00:35, 5.97s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 6: : 50%|█████ | 5/10 [00:33<00:26, 5.39s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:33<00:26, 5.39s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 50%|█████ | 5/10 [00:37<00:26, 5.39s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 7: : 60%|██████ | 6/10 [00:38<00:20, 5.04s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [00:38<00:20, 5.04s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 60%|██████ | 6/10 [00:42<00:20, 5.04s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 8: : 70%|███████ | 7/10 [00:42<00:14, 4.82s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [00:42<00:14, 4.82s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 70%|███████ | 7/10 [00:46<00:14, 4.82s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 9: : 80%|████████ | 8/10 [00:46<00:09, 4.67s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 80%|████████ | 8/10 [00:46<00:09, 4.67s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 80%|████████ | 8/10 [00:51<00:09, 4.67s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 1: Data size 10: : 90%|█████████ | 9/10 [00:51<00:04, 4.57s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 90%|█████████ | 9/10 [00:51<00:04, 4.57s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 90%|█████████ | 9/10 [00:55<00:04, 4.57s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 100%|██████████| 10/10 [00:55<00:00, 4.51s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 1: Data size 11: : 100%|██████████| 10/10 [00:55<00:00, 5.55s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 2: Data size 2: : 0%| | 0/10 [00:16<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 2: : 10%|█ | 1/10 [00:16<02:29, 16.64s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:16<02:29, 16.64s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 10%|█ | 1/10 [00:20<02:29, 16.64s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 3: : 20%|██ | 2/10 [00:21<01:15, 9.46s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:21<01:15, 9.46s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 2: Data size 4: : 20%|██ | 2/10 [00:25<01:15, 9.46s/it, data_size=4, test_acc=0.25, train_acc=0.25]Test 2: Data size 4: : 30%|███ | 3/10 [00:25<00:50, 7.19s/it, data_size=4, test_acc=0.25, train_acc=0.25]Test 2: Data size 5: : 30%|███ | 3/10 [00:25<00:50, 7.19s/it, data_size=4, test_acc=0.25, train_acc=0.25]Test 2: Data size 5: : 30%|███ | 3/10 [00:29<00:50, 7.19s/it, data_size=5, test_acc=0.25, train_acc=0.25]Test 2: Data size 5: : 40%|████ | 4/10 [00:30<00:36, 6.10s/it, data_size=5, test_acc=0.25, train_acc=0.25]Test 2: Data size 6: : 40%|████ | 4/10 [00:30<00:36, 6.10s/it, data_size=5, test_acc=0.25, train_acc=0.25]Test 2: Data size 6: : 40%|████ | 4/10 [00:34<00:36, 6.10s/it, data_size=6, test_acc=0.25, train_acc=0.25]Test 2: Data size 6: : 50%|█████ | 5/10 [00:34<00:27, 5.50s/it, data_size=6, test_acc=0.25, train_acc=0.25]Test 2: Data size 7: : 50%|█████ | 5/10 [00:34<00:27, 5.50s/it, data_size=6, test_acc=0.25, train_acc=0.25]Test 2: Data size 7: : 50%|█████ | 5/10 [00:38<00:27, 5.50s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 2: Data size 7: : 60%|██████ | 6/10 [00:38<00:20, 5.13s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 2: Data size 8: : 60%|██████ | 6/10 [00:38<00:20, 5.13s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 2: Data size 8: : 60%|██████ | 6/10 [00:43<00:20, 5.13s/it, data_size=8, test_acc=0.25, train_acc=0.25]Test 2: Data size 8: : 70%|███████ | 7/10 [00:43<00:14, 4.90s/it, data_size=8, test_acc=0.25, train_acc=0.25]Test 2: Data size 9: : 70%|███████ | 7/10 [00:43<00:14, 4.90s/it, data_size=8, test_acc=0.25, train_acc=0.25]Test 2: Data size 9: : 70%|███████ | 7/10 [00:47<00:14, 4.90s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 2: Data size 9: : 80%|████████ | 8/10 [00:47<00:09, 4.75s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 2: Data size 10: : 80%|████████ | 8/10 [00:47<00:09, 4.75s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 2: Data size 10: : 80%|████████ | 8/10 [00:52<00:09, 4.75s/it, data_size=10, test_acc=0.25, train_acc=0.25]Test 2: Data size 10: : 90%|█████████ | 9/10 [00:52<00:04, 4.65s/it, data_size=10, test_acc=0.25, train_acc=0.25]Test 2: Data size 11: : 90%|█████████ | 9/10 [00:52<00:04, 4.65s/it, data_size=10, test_acc=0.25, train_acc=0.25]Test 2: Data size 11: : 90%|█████████ | 9/10 [00:56<00:04, 4.65s/it, data_size=11, test_acc=0.25, train_acc=0.25]Test 2: Data size 11: : 100%|██████████| 10/10 [00:56<00:00, 4.57s/it, data_size=11, test_acc=0.25, train_acc=0.25]Test 2: Data size 11: : 100%|██████████| 10/10 [00:56<00:00, 5.65s/it, data_size=11, test_acc=0.25, train_acc=0.25]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 3: Data size 2: : 0%| | 0/10 [00:16<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 2: : 10%|█ | 1/10 [00:16<02:25, 16.13s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:16<02:25, 16.13s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 10%|█ | 1/10 [00:20<02:25, 16.13s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 3: : 20%|██ | 2/10 [00:20<01:13, 9.15s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:20<01:13, 9.15s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 3: Data size 4: : 20%|██ | 2/10 [00:24<01:13, 9.15s/it, data_size=4, test_acc=0.25, train_acc=0.25]Test 3: Data size 4: : 30%|███ | 3/10 [00:24<00:48, 6.93s/it, data_size=4, test_acc=0.25, train_acc=0.25]Test 3: Data size 5: : 30%|███ | 3/10 [00:24<00:48, 6.93s/it, data_size=4, test_acc=0.25, train_acc=0.25]Test 3: Data size 5: : 30%|███ | 3/10 [00:28<00:48, 6.93s/it, data_size=5, test_acc=0.25, train_acc=0.25]Test 3: Data size 5: : 40%|████ | 4/10 [00:28<00:35, 5.87s/it, data_size=5, test_acc=0.25, train_acc=0.25]Test 3: Data size 6: : 40%|████ | 4/10 [00:28<00:35, 5.87s/it, data_size=5, test_acc=0.25, train_acc=0.25]Test 3: Data size 6: : 40%|████ | 4/10 [00:33<00:35, 5.87s/it, data_size=6, test_acc=0.25, train_acc=0.25]Test 3: Data size 6: : 50%|█████ | 5/10 [00:33<00:26, 5.29s/it, data_size=6, test_acc=0.25, train_acc=0.25]Test 3: Data size 7: : 50%|█████ | 5/10 [00:33<00:26, 5.29s/it, data_size=6, test_acc=0.25, train_acc=0.25]Test 3: Data size 7: : 50%|█████ | 5/10 [00:37<00:26, 5.29s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 3: Data size 7: : 60%|██████ | 6/10 [00:37<00:19, 4.94s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 3: Data size 8: : 60%|██████ | 6/10 [00:37<00:19, 4.94s/it, data_size=7, test_acc=0.25, train_acc=0.25]Test 3: Data size 8: : 60%|██████ | 6/10 [00:41<00:19, 4.94s/it, data_size=8, test_acc=0.25, train_acc=0.25]Test 3: Data size 8: : 70%|███████ | 7/10 [00:41<00:14, 4.72s/it, data_size=8, test_acc=0.25, train_acc=0.25]Test 3: Data size 9: : 70%|███████ | 7/10 [00:41<00:14, 4.72s/it, data_size=8, test_acc=0.25, train_acc=0.25]Test 3: Data size 9: : 70%|███████ | 7/10 [00:45<00:14, 4.72s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 3: Data size 9: : 80%|████████ | 8/10 [00:45<00:09, 4.57s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 3: Data size 10: : 80%|████████ | 8/10 [00:45<00:09, 4.57s/it, data_size=9, test_acc=0.25, train_acc=0.25]Test 3: Data size 10: : 80%|████████ | 8/10 [00:50<00:09, 4.57s/it, data_size=10, test_acc=0.25, train_acc=0.25]Test 3: Data size 10: : 90%|█████████ | 9/10 [00:50<00:04, 4.47s/it, data_size=10, test_acc=0.25, train_acc=0.25]Test 3: Data size 11: : 90%|█████████ | 9/10 [00:50<00:04, 4.47s/it, data_size=10, test_acc=0.25, train_acc=0.25]Test 3: Data size 11: : 90%|█████████ | 9/10 [00:54<00:04, 4.47s/it, data_size=11, test_acc=0.25, train_acc=0.25]Test 3: Data size 11: : 100%|██████████| 10/10 [00:54<00:00, 4.41s/it, data_size=11, test_acc=0.25, train_acc=0.25]Test 3: Data size 11: : 100%|██████████| 10/10 [00:54<00:00, 5.45s/it, data_size=11, test_acc=0.25, train_acc=0.25]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 4: Data size 2: : 0%| | 0/10 [00:16<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 2: : 10%|█ | 1/10 [00:16<02:27, 16.34s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:16<02:27, 16.34s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 10%|█ | 1/10 [00:20<02:27, 16.34s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 3: : 20%|██ | 2/10 [00:20<01:14, 9.29s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:20<01:14, 9.29s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 20%|██ | 2/10 [00:24<01:14, 9.29s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 4: : 30%|███ | 3/10 [00:25<00:49, 7.03s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:25<00:49, 7.03s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 30%|███ | 3/10 [00:29<00:49, 7.03s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 5: : 40%|████ | 4/10 [00:29<00:35, 5.98s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:29<00:35, 5.98s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 40%|████ | 4/10 [00:33<00:35, 5.98s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 6: : 50%|█████ | 5/10 [00:33<00:26, 5.40s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:33<00:26, 5.40s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 50%|█████ | 5/10 [00:37<00:26, 5.40s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 7: : 60%|██████ | 6/10 [00:38<00:20, 5.04s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:38<00:20, 5.04s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 60%|██████ | 6/10 [00:42<00:20, 5.04s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 8: : 70%|███████ | 7/10 [00:42<00:14, 4.81s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:42<00:14, 4.81s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 70%|███████ | 7/10 [00:46<00:14, 4.81s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 9: : 80%|████████ | 8/10 [00:46<00:09, 4.67s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [00:46<00:09, 4.67s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 80%|████████ | 8/10 [00:51<00:09, 4.67s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 10: : 90%|█████████ | 9/10 [00:51<00:04, 4.57s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 90%|█████████ | 9/10 [00:51<00:04, 4.57s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 90%|█████████ | 9/10 [00:55<00:04, 4.57s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 100%|██████████| 10/10 [00:55<00:00, 4.51s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 4: Data size 11: : 100%|██████████| 10/10 [00:55<00:00, 5.56s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 5: Data size 2: : 0%| | 0/10 [00:16<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 2: : 10%|█ | 1/10 [00:16<02:27, 16.40s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:16<02:27, 16.40s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 10%|█ | 1/10 [00:20<02:27, 16.40s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 3: : 20%|██ | 2/10 [00:20<01:14, 9.29s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:20<01:14, 9.29s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 20%|██ | 2/10 [00:24<01:14, 9.29s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 5: Data size 4: : 30%|███ | 3/10 [00:25<00:49, 7.02s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:25<00:49, 7.02s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 5: Data size 5: : 30%|███ | 3/10 [00:29<00:49, 7.02s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 5: : 40%|████ | 4/10 [00:29<00:35, 5.95s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:29<00:35, 5.95s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 40%|████ | 4/10 [00:33<00:35, 5.95s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 6: : 50%|█████ | 5/10 [00:33<00:26, 5.36s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:33<00:26, 5.36s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 50%|█████ | 5/10 [00:37<00:26, 5.36s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 5: Data size 7: : 60%|██████ | 6/10 [00:38<00:20, 5.02s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [00:38<00:20, 5.02s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 5: Data size 8: : 60%|██████ | 6/10 [00:42<00:20, 5.02s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 5: Data size 8: : 70%|███████ | 7/10 [00:42<00:14, 4.79s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 5: Data size 9: : 70%|███████ | 7/10 [00:42<00:14, 4.79s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 5: Data size 9: : 70%|███████ | 7/10 [00:46<00:14, 4.79s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 5: Data size 9: : 80%|████████ | 8/10 [00:46<00:09, 4.64s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 5: Data size 10: : 80%|████████ | 8/10 [00:46<00:09, 4.64s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 5: Data size 10: : 80%|████████ | 8/10 [00:50<00:09, 4.64s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 5: Data size 10: : 90%|█████████ | 9/10 [00:50<00:04, 4.54s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 5: Data size 11: : 90%|█████████ | 9/10 [00:50<00:04, 4.54s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 5: Data size 11: : 90%|█████████ | 9/10 [00:55<00:04, 4.54s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 5: Data size 11: : 100%|██████████| 10/10 [00:55<00:00, 4.47s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 5: Data size 11: : 100%|██████████| 10/10 [00:55<00:00, 5.53s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 6: Data size 2: : 0%| | 0/10 [00:16<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 2: : 10%|█ | 1/10 [00:16<02:28, 16.54s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:16<02:28, 16.54s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 10%|█ | 1/10 [00:20<02:28, 16.54s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 3: : 20%|██ | 2/10 [00:20<01:15, 9.41s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:20<01:15, 9.41s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 20%|██ | 2/10 [00:25<01:15, 9.41s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 4: : 30%|███ | 3/10 [00:25<00:49, 7.13s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:25<00:49, 7.13s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 30%|███ | 3/10 [00:29<00:49, 7.13s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 5: : 40%|████ | 4/10 [00:29<00:36, 6.07s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:29<00:36, 6.07s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 40%|████ | 4/10 [00:34<00:36, 6.07s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 6: Data size 6: : 50%|█████ | 5/10 [00:34<00:27, 5.48s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:34<00:27, 5.48s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 6: Data size 7: : 50%|█████ | 5/10 [00:38<00:27, 5.48s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 6: Data size 7: : 60%|██████ | 6/10 [00:38<00:20, 5.13s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:38<00:20, 5.13s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 6: Data size 8: : 60%|██████ | 6/10 [00:43<00:20, 5.13s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 6: Data size 8: : 70%|███████ | 7/10 [00:43<00:14, 4.90s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:43<00:14, 4.90s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 6: Data size 9: : 70%|███████ | 7/10 [00:47<00:14, 4.90s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 6: Data size 9: : 80%|████████ | 8/10 [00:47<00:09, 4.75s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [00:47<00:09, 4.75s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 6: Data size 10: : 80%|████████ | 8/10 [00:51<00:09, 4.75s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 6: Data size 10: : 90%|█████████ | 9/10 [00:51<00:04, 4.65s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [00:51<00:04, 4.65s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 90%|█████████ | 9/10 [00:56<00:04, 4.65s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 100%|██████████| 10/10 [00:56<00:00, 4.58s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 6: Data size 11: : 100%|██████████| 10/10 [00:56<00:00, 5.64s/it, data_size=11, test_acc=0.25, train_acc=nan]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]/home/agaut/CS229-Project/test_framework/metrics.py:41: RuntimeWarning: invalid value encountered in true_divide
label_accuracies = np.sum(correct_predictions, axis=0) / np.sum(y_actual, axis=0)
Test 7: Data size 2: : 0%| | 0/10 [00:16<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 2: : 10%|█ | 1/10 [00:16<02:28, 16.49s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:16<02:28, 16.49s/it, data_size=2, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 10%|█ | 1/10 [00:20<02:28, 16.49s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 3: : 20%|██ | 2/10 [00:20<01:15, 9.40s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:20<01:15, 9.40s/it, data_size=3, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 20%|██ | 2/10 [00:25<01:15, 9.40s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 4: : 30%|███ | 3/10 [00:25<00:49, 7.14s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:25<00:49, 7.14s/it, data_size=4, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 30%|███ | 3/10 [00:29<00:49, 7.14s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 5: : 40%|████ | 4/10 [00:29<00:36, 6.08s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [00:29<00:36, 6.08s/it, data_size=5, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 40%|████ | 4/10 [00:34<00:36, 6.08s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 6: : 50%|█████ | 5/10 [00:34<00:27, 5.49s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [00:34<00:27, 5.49s/it, data_size=6, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 50%|█████ | 5/10 [00:38<00:27, 5.49s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 7: : 60%|██████ | 6/10 [00:38<00:20, 5.14s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 60%|██████ | 6/10 [00:38<00:20, 5.14s/it, data_size=7, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 60%|██████ | 6/10 [00:43<00:20, 5.14s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 8: : 70%|███████ | 7/10 [00:43<00:14, 4.92s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 70%|███████ | 7/10 [00:43<00:14, 4.92s/it, data_size=8, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 70%|███████ | 7/10 [00:47<00:14, 4.92s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 9: : 80%|████████ | 8/10 [00:47<00:09, 4.76s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 10: : 80%|████████ | 8/10 [00:47<00:09, 4.76s/it, data_size=9, test_acc=0.25, train_acc=nan]Test 7: Data size 10: : 80%|████████ | 8/10 [00:51<00:09, 4.76s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 7: Data size 10: : 90%|█████████ | 9/10 [00:52<00:04, 4.67s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 7: Data size 11: : 90%|█████████ | 9/10 [00:52<00:04, 4.67s/it, data_size=10, test_acc=0.25, train_acc=nan]Test 7: Data size 11: : 90%|█████████ | 9/10 [00:56<00:04, 4.67s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 7: Data size 11: : 100%|██████████| 10/10 [00:56<00:00, 4.60s/it, data_size=11, test_acc=0.25, train_acc=nan]Test 7: Data size 11: : 100%|██████████| 10/10 [00:56<00:00, 5.66s/it, data_size=11, test_acc=0.25, train_acc=nan]
working on model Multimodal-late-fusion-model-based-on-AlexNet with BADGE
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 2: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 2: : 0%| | 0/10 [00:11<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]Test 0: Data size 2: : 0%| | 0/10 [00:11<?, ?it/s, data_size=2, test_acc=0.25, train_acc=nan]
Traceback (most recent call last):
File "/home/agaut/CS229-Project/experiments/experiment.py", line 168, in run_experiments
self.tester.test_model(curr_model)
File "/home/agaut/CS229-Project/test_framework/tester.py", line 165, in test_model
for mode_ind in range(len(train_x))
File "/home/agaut/CS229-Project/test_framework/tester.py", line 165, in <listcomp>
for mode_ind in range(len(train_x))
IndexError: arrays used as indices must be of integer (or boolean) type
Got exception arrays used as indices must be of integer (or boolean) type for model BADGE with stack trace:
None
working on model Multimodal-middle-fusion-model-based-on-AlexNet with RANDOM
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.636, train_acc=0.645]Test 0: Data size 208: : 10%|█ | 1/10 [00:26<03:55, 26.16s/it, data_size=208, test_acc=0.636, train_acc=0.645]Test 0: Data size 240: : 10%|█ | 1/10 [00:26<03:55, 26.16s/it, data_size=208, test_acc=0.636, train_acc=0.645]Test 0: Data size 240: : 10%|█ | 1/10 [00:55<03:55, 26.16s/it, data_size=240, test_acc=0.701, train_acc=0.729]Test 0: Data size 240: : 20%|██ | 2/10 [00:55<03:44, 28.10s/it, data_size=240, test_acc=0.701, train_acc=0.729]Test 0: Data size 272: : 20%|██ | 2/10 [00:55<03:44, 28.10s/it, data_size=240, test_acc=0.701, train_acc=0.729]Test 0: Data size 272: : 20%|██ | 2/10 [01:27<03:44, 28.10s/it, data_size=272, test_acc=0.716, train_acc=0.754]Test 0: Data size 272: : 30%|███ | 3/10 [01:28<03:30, 30.07s/it, data_size=272, test_acc=0.716, train_acc=0.754]Test 0: Data size 304: : 30%|███ | 3/10 [01:28<03:30, 30.07s/it, data_size=272, test_acc=0.716, train_acc=0.754]Test 0: Data size 304: : 30%|███ | 3/10 [02:03<03:30, 30.07s/it, data_size=304, test_acc=0.752, train_acc=0.778]Test 0: Data size 304: : 40%|████ | 4/10 [02:03<03:13, 32.17s/it, data_size=304, test_acc=0.752, train_acc=0.778]Test 0: Data size 336: : 40%|████ | 4/10 [02:03<03:13, 32.17s/it, data_size=304, test_acc=0.752, train_acc=0.778]Test 0: Data size 336: : 40%|████ | 4/10 [02:41<03:13, 32.17s/it, data_size=336, test_acc=0.735, train_acc=0.765]Test 0: Data size 336: : 50%|█████ | 5/10 [02:42<02:52, 34.52s/it, data_size=336, test_acc=0.735, train_acc=0.765]Test 0: Data size 368: : 50%|█████ | 5/10 [02:42<02:52, 34.52s/it, data_size=336, test_acc=0.735, train_acc=0.765]Test 0: Data size 368: : 50%|█████ | 5/10 [03:23<02:52, 34.52s/it, data_size=368, test_acc=0.777, train_acc=0.805]Test 0: Data size 368: : 60%|██████ | 6/10 [03:23<02:27, 36.94s/it, data_size=368, test_acc=0.777, train_acc=0.805]Test 0: Data size 400: : 60%|██████ | 6/10 [03:23<02:27, 36.94s/it, data_size=368, test_acc=0.777, train_acc=0.805]Test 0: Data size 400: : 60%|██████ | 6/10 [04:08<02:27, 36.94s/it, data_size=400, test_acc=0.848, train_acc=0.869]Test 0: Data size 400: : 70%|███████ | 7/10 [04:08<01:58, 39.61s/it, data_size=400, test_acc=0.848, train_acc=0.869]Test 0: Data size 432: : 70%|███████ | 7/10 [04:08<01:58, 39.61s/it, data_size=400, test_acc=0.848, train_acc=0.869]Test 0: Data size 432: : 70%|███████ | 7/10 [04:57<01:58, 39.61s/it, data_size=432, test_acc=0.779, train_acc=0.819]Test 0: Data size 432: : 80%|████████ | 8/10 [04:57<01:24, 42.45s/it, data_size=432, test_acc=0.779, train_acc=0.819]Test 0: Data size 464: : 80%|████████ | 8/10 [04:57<01:24, 42.45s/it, data_size=432, test_acc=0.779, train_acc=0.819]Test 0: Data size 464: : 80%|████████ | 8/10 [05:48<01:24, 42.45s/it, data_size=464, test_acc=0.83, train_acc=0.847] Test 0: Data size 464: : 90%|█████████ | 9/10 [05:49<00:45, 45.33s/it, data_size=464, test_acc=0.83, train_acc=0.847]Test 0: Data size 496: : 90%|█████████ | 9/10 [05:49<00:45, 45.33s/it, data_size=464, test_acc=0.83, train_acc=0.847]Test 0: Data size 496: : 90%|█████████ | 9/10 [06:43<00:45, 45.33s/it, data_size=496, test_acc=0.815, train_acc=0.837]Test 0: Data size 496: : 100%|██████████| 10/10 [06:43<00:00, 48.21s/it, data_size=496, test_acc=0.815, train_acc=0.837]Test 0: Data size 496: : 100%|██████████| 10/10 [06:43<00:00, 40.37s/it, data_size=496, test_acc=0.815, train_acc=0.837]
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0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.684, train_acc=0.718]Test 2: Data size 208: : 10%|█ | 1/10 [00:26<03:59, 26.64s/it, data_size=208, test_acc=0.684, train_acc=0.718]Test 2: Data size 240: : 10%|█ | 1/10 [00:26<03:59, 26.64s/it, data_size=208, test_acc=0.684, train_acc=0.718]Test 2: Data size 240: : 10%|█ | 1/10 [00:55<03:59, 26.64s/it, data_size=240, test_acc=0.707, train_acc=0.728]Test 2: Data size 240: : 20%|██ | 2/10 [00:56<03:46, 28.28s/it, data_size=240, test_acc=0.707, train_acc=0.728]Test 2: Data size 272: : 20%|██ | 2/10 [00:56<03:46, 28.28s/it, data_size=240, test_acc=0.707, train_acc=0.728]Test 2: Data size 272: : 20%|██ | 2/10 [01:28<03:46, 28.28s/it, data_size=272, test_acc=0.728, train_acc=0.759]Test 2: Data size 272: : 30%|███ | 3/10 [01:28<03:32, 30.39s/it, data_size=272, test_acc=0.728, train_acc=0.759]Test 2: Data size 304: : 30%|███ | 3/10 [01:28<03:32, 30.39s/it, data_size=272, test_acc=0.728, train_acc=0.759]Test 2: Data size 304: : 30%|███ | 3/10 [02:05<03:32, 30.39s/it, data_size=304, test_acc=0.728, train_acc=0.752]Test 2: Data size 304: : 40%|████ | 4/10 [02:05<03:16, 32.69s/it, data_size=304, test_acc=0.728, train_acc=0.752]Test 2: Data size 336: : 40%|████ | 4/10 [02:05<03:16, 32.69s/it, data_size=304, test_acc=0.728, train_acc=0.752]Test 2: Data size 336: : 40%|████ | 4/10 [02:44<03:16, 32.69s/it, data_size=336, test_acc=0.665, train_acc=0.71] Test 2: Data size 336: : 50%|█████ | 5/10 [02:44<02:55, 35.13s/it, data_size=336, test_acc=0.665, train_acc=0.71]Test 2: Data size 368: : 50%|█████ | 5/10 [02:44<02:55, 35.13s/it, data_size=336, test_acc=0.665, train_acc=0.71]Test 2: Data size 368: : 50%|█████ | 5/10 [03:27<02:55, 35.13s/it, data_size=368, test_acc=0.806, train_acc=0.82]Test 2: Data size 368: : 60%|██████ | 6/10 [03:27<02:31, 37.91s/it, data_size=368, test_acc=0.806, train_acc=0.82]Test 2: Data size 400: : 60%|██████ | 6/10 [03:27<02:31, 37.91s/it, data_size=368, test_acc=0.806, train_acc=0.82]Test 2: Data size 400: : 60%|██████ | 6/10 [04:14<02:31, 37.91s/it, data_size=400, test_acc=0.813, train_acc=0.843]Test 2: Data size 400: : 70%|███████ | 7/10 [04:14<02:02, 40.85s/it, data_size=400, test_acc=0.813, train_acc=0.843]Test 2: Data size 432: : 70%|███████ | 7/10 [04:14<02:02, 40.85s/it, data_size=400, test_acc=0.813, train_acc=0.843]Test 2: Data size 432: : 70%|███████ | 7/10 [05:04<02:02, 40.85s/it, data_size=432, test_acc=0.801, train_acc=0.875]Test 2: Data size 432: : 80%|████████ | 8/10 [05:05<01:27, 43.81s/it, data_size=432, test_acc=0.801, train_acc=0.875]Test 2: Data size 464: : 80%|████████ | 8/10 [05:05<01:27, 43.81s/it, data_size=432, test_acc=0.801, train_acc=0.875]Test 2: Data size 464: : 80%|████████ | 8/10 [05:58<01:27, 43.81s/it, data_size=464, test_acc=0.886, train_acc=0.906]Test 2: Data size 464: : 90%|█████████ | 9/10 [05:58<00:46, 46.88s/it, data_size=464, test_acc=0.886, train_acc=0.906]Test 2: Data size 496: : 90%|█████████ | 9/10 [05:58<00:46, 46.88s/it, data_size=464, test_acc=0.886, train_acc=0.906]Test 2: Data size 496: : 90%|█████████ | 9/10 [06:55<00:46, 46.88s/it, data_size=496, test_acc=0.818, train_acc=0.835]Test 2: Data size 496: : 100%|██████████| 10/10 [06:55<00:00, 50.07s/it, data_size=496, test_acc=0.818, train_acc=0.835]Test 2: Data size 496: : 100%|██████████| 10/10 [06:55<00:00, 41.58s/it, data_size=496, test_acc=0.818, train_acc=0.835]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.72, train_acc=0.726]Test 3: Data size 208: : 10%|█ | 1/10 [00:26<04:00, 26.71s/it, data_size=208, test_acc=0.72, train_acc=0.726]Test 3: Data size 240: : 10%|█ | 1/10 [00:26<04:00, 26.71s/it, data_size=208, test_acc=0.72, train_acc=0.726]Test 3: Data size 240: : 10%|█ | 1/10 [00:56<04:00, 26.71s/it, data_size=240, test_acc=0.749, train_acc=0.747]Test 3: Data size 240: : 20%|██ | 2/10 [00:56<03:47, 28.49s/it, data_size=240, test_acc=0.749, train_acc=0.747]Test 3: Data size 272: : 20%|██ | 2/10 [00:56<03:47, 28.49s/it, data_size=240, test_acc=0.749, train_acc=0.747]Test 3: Data size 272: : 20%|██ | 2/10 [01:29<03:47, 28.49s/it, data_size=272, test_acc=0.739, train_acc=0.749]Test 3: Data size 272: : 30%|███ | 3/10 [01:29<03:33, 30.47s/it, data_size=272, test_acc=0.739, train_acc=0.749]Test 3: Data size 304: : 30%|███ | 3/10 [01:29<03:33, 30.47s/it, data_size=272, test_acc=0.739, train_acc=0.749]Test 3: Data size 304: : 30%|███ | 3/10 [02:05<03:33, 30.47s/it, data_size=304, test_acc=0.753, train_acc=0.755]Test 3: Data size 304: : 40%|████ | 4/10 [02:05<03:16, 32.82s/it, data_size=304, test_acc=0.753, train_acc=0.755]Test 3: Data size 336: : 40%|████ | 4/10 [02:05<03:16, 32.82s/it, data_size=304, test_acc=0.753, train_acc=0.755]Test 3: Data size 336: : 40%|████ | 4/10 [02:44<03:16, 32.82s/it, data_size=336, test_acc=0.837, train_acc=0.848]Test 3: Data size 336: : 50%|█████ | 5/10 [02:44<02:55, 35.14s/it, data_size=336, test_acc=0.837, train_acc=0.848]Test 3: Data size 368: : 50%|█████ | 5/10 [02:44<02:55, 35.14s/it, data_size=336, test_acc=0.837, train_acc=0.848]Test 3: Data size 368: : 50%|█████ | 5/10 [03:27<02:55, 35.14s/it, data_size=368, test_acc=0.823, train_acc=0.825]Test 3: Data size 368: : 60%|██████ | 6/10 [03:27<02:31, 37.76s/it, data_size=368, test_acc=0.823, train_acc=0.825]Test 3: Data size 400: : 60%|██████ | 6/10 [03:27<02:31, 37.76s/it, data_size=368, test_acc=0.823, train_acc=0.825]Test 3: Data size 400: : 60%|██████ | 6/10 [04:13<02:31, 37.76s/it, data_size=400, test_acc=0.844, train_acc=0.847]Test 3: Data size 400: : 70%|███████ | 7/10 [04:14<02:01, 40.53s/it, data_size=400, test_acc=0.844, train_acc=0.847]Test 3: Data size 432: : 70%|███████ | 7/10 [04:14<02:01, 40.53s/it, data_size=400, test_acc=0.844, train_acc=0.847]Test 3: Data size 432: : 70%|███████ | 7/10 [05:03<02:01, 40.53s/it, data_size=432, test_acc=0.815, train_acc=0.824]Test 3: Data size 432: : 80%|████████ | 8/10 [05:03<01:26, 43.37s/it, data_size=432, test_acc=0.815, train_acc=0.824]Test 3: Data size 464: : 80%|████████ | 8/10 [05:03<01:26, 43.37s/it, data_size=432, test_acc=0.815, train_acc=0.824]Test 3: Data size 464: : 80%|████████ | 8/10 [05:56<01:26, 43.37s/it, data_size=464, test_acc=0.831, train_acc=0.832]Test 3: Data size 464: : 90%|█████████ | 9/10 [05:56<00:46, 46.30s/it, data_size=464, test_acc=0.831, train_acc=0.832]Test 3: Data size 496: : 90%|█████████ | 9/10 [05:56<00:46, 46.30s/it, data_size=464, test_acc=0.831, train_acc=0.832]Test 3: Data size 496: : 90%|█████████ | 9/10 [06:52<00:46, 46.30s/it, data_size=496, test_acc=0.867, train_acc=0.858]Test 3: Data size 496: : 100%|██████████| 10/10 [06:52<00:00, 49.35s/it, data_size=496, test_acc=0.867, train_acc=0.858]Test 3: Data size 496: : 100%|██████████| 10/10 [06:52<00:00, 41.24s/it, data_size=496, test_acc=0.867, train_acc=0.858]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.704, train_acc=0.701]Test 4: Data size 208: : 10%|█ | 1/10 [00:26<03:58, 26.55s/it, data_size=208, test_acc=0.704, train_acc=0.701]Test 4: Data size 240: : 10%|█ | 1/10 [00:26<03:58, 26.55s/it, data_size=208, test_acc=0.704, train_acc=0.701]Test 4: Data size 240: : 10%|█ | 1/10 [00:56<03:58, 26.55s/it, data_size=240, test_acc=0.74, train_acc=0.733] Test 4: Data size 240: : 20%|██ | 2/10 [00:56<03:49, 28.66s/it, data_size=240, test_acc=0.74, train_acc=0.733]Test 4: Data size 272: : 20%|██ | 2/10 [00:56<03:49, 28.66s/it, data_size=240, test_acc=0.74, train_acc=0.733]Test 4: Data size 272: : 20%|██ | 2/10 [01:29<03:49, 28.66s/it, data_size=272, test_acc=0.7, train_acc=0.693] Test 4: Data size 272: : 30%|███ | 3/10 [01:29<03:35, 30.74s/it, data_size=272, test_acc=0.7, train_acc=0.693]Test 4: Data size 304: : 30%|███ | 3/10 [01:29<03:35, 30.74s/it, data_size=272, test_acc=0.7, train_acc=0.693]Test 4: Data size 304: : 30%|███ | 3/10 [02:06<03:35, 30.74s/it, data_size=304, test_acc=0.741, train_acc=0.762]Test 4: Data size 304: : 40%|████ | 4/10 [02:06<03:17, 32.93s/it, data_size=304, test_acc=0.741, train_acc=0.762]Test 4: Data size 336: : 40%|████ | 4/10 [02:06<03:17, 32.93s/it, data_size=304, test_acc=0.741, train_acc=0.762]Test 4: Data size 336: : 40%|████ | 4/10 [02:46<03:17, 32.93s/it, data_size=336, test_acc=0.807, train_acc=0.831]Test 4: Data size 336: : 50%|█████ | 5/10 [02:46<02:57, 35.48s/it, data_size=336, test_acc=0.807, train_acc=0.831]Test 4: Data size 368: : 50%|█████ | 5/10 [02:46<02:57, 35.48s/it, data_size=336, test_acc=0.807, train_acc=0.831]Test 4: Data size 368: : 50%|█████ | 5/10 [03:29<02:57, 35.48s/it, data_size=368, test_acc=0.794, train_acc=0.827]Test 4: Data size 368: : 60%|██████ | 6/10 [03:29<02:32, 38.05s/it, data_size=368, test_acc=0.794, train_acc=0.827]Test 4: Data size 400: : 60%|██████ | 6/10 [03:29<02:32, 38.05s/it, data_size=368, test_acc=0.794, train_acc=0.827]Test 4: Data size 400: : 60%|██████ | 6/10 [04:15<02:32, 38.05s/it, data_size=400, test_acc=0.871, train_acc=0.884]Test 4: Data size 400: : 70%|███████ | 7/10 [04:15<02:02, 40.73s/it, data_size=400, test_acc=0.871, train_acc=0.884]Test 4: Data size 432: : 70%|███████ | 7/10 [04:15<02:02, 40.73s/it, data_size=400, test_acc=0.871, train_acc=0.884]Test 4: Data size 432: : 70%|███████ | 7/10 [05:04<02:02, 40.73s/it, data_size=432, test_acc=0.835, train_acc=0.875]Test 4: Data size 432: : 80%|████████ | 8/10 [05:04<01:27, 43.51s/it, data_size=432, test_acc=0.835, train_acc=0.875]Test 4: Data size 464: : 80%|████████ | 8/10 [05:04<01:27, 43.51s/it, data_size=432, test_acc=0.835, train_acc=0.875]Test 4: Data size 464: : 80%|████████ | 8/10 [05:57<01:27, 43.51s/it, data_size=464, test_acc=0.822, train_acc=0.86] Test 4: Data size 464: : 90%|█████████ | 9/10 [05:57<00:46, 46.47s/it, data_size=464, test_acc=0.822, train_acc=0.86]Test 4: Data size 496: : 90%|█████████ | 9/10 [05:57<00:46, 46.47s/it, data_size=464, test_acc=0.822, train_acc=0.86]Test 4: Data size 496: : 90%|█████████ | 9/10 [06:54<00:46, 46.47s/it, data_size=496, test_acc=0.869, train_acc=0.891]Test 4: Data size 496: : 100%|██████████| 10/10 [06:54<00:00, 49.57s/it, data_size=496, test_acc=0.869, train_acc=0.891]Test 4: Data size 496: : 100%|██████████| 10/10 [06:54<00:00, 41.44s/it, data_size=496, test_acc=0.869, train_acc=0.891]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:27<?, ?it/s, data_size=208, test_acc=0.714, train_acc=0.725]Test 5: Data size 208: : 10%|█ | 1/10 [00:27<04:05, 27.29s/it, data_size=208, test_acc=0.714, train_acc=0.725]Test 5: Data size 240: : 10%|█ | 1/10 [00:27<04:05, 27.29s/it, data_size=208, test_acc=0.714, train_acc=0.725]Test 5: Data size 240: : 10%|█ | 1/10 [00:57<04:05, 27.29s/it, data_size=240, test_acc=0.72, train_acc=0.76] Test 5: Data size 240: : 20%|██ | 2/10 [00:57<03:53, 29.16s/it, data_size=240, test_acc=0.72, train_acc=0.76]Test 5: Data size 272: : 20%|██ | 2/10 [00:57<03:53, 29.16s/it, data_size=240, test_acc=0.72, train_acc=0.76]Test 5: Data size 272: : 20%|██ | 2/10 [01:31<03:53, 29.16s/it, data_size=272, test_acc=0.757, train_acc=0.772]Test 5: Data size 272: : 30%|███ | 3/10 [01:31<03:37, 31.13s/it, data_size=272, test_acc=0.757, train_acc=0.772]Test 5: Data size 304: : 30%|███ | 3/10 [01:31<03:37, 31.13s/it, data_size=272, test_acc=0.757, train_acc=0.772]Test 5: Data size 304: : 30%|███ | 3/10 [02:07<03:37, 31.13s/it, data_size=304, test_acc=0.757, train_acc=0.77] Test 5: Data size 304: : 40%|████ | 4/10 [02:07<03:19, 33.26s/it, data_size=304, test_acc=0.757, train_acc=0.77]Test 5: Data size 336: : 40%|████ | 4/10 [02:07<03:19, 33.26s/it, data_size=304, test_acc=0.757, train_acc=0.77]Test 5: Data size 336: : 40%|████ | 4/10 [02:47<03:19, 33.26s/it, data_size=336, test_acc=0.733, train_acc=0.734]Test 5: Data size 336: : 50%|█████ | 5/10 [02:47<02:57, 35.59s/it, data_size=336, test_acc=0.733, train_acc=0.734]Test 5: Data size 368: : 50%|█████ | 5/10 [02:47<02:57, 35.59s/it, data_size=336, test_acc=0.733, train_acc=0.734]Test 5: Data size 368: : 50%|█████ | 5/10 [03:30<02:57, 35.59s/it, data_size=368, test_acc=0.753, train_acc=0.748]Test 5: Data size 368: : 60%|██████ | 6/10 [03:30<02:32, 38.12s/it, data_size=368, test_acc=0.753, train_acc=0.748]Test 5: Data size 400: : 60%|██████ | 6/10 [03:30<02:32, 38.12s/it, data_size=368, test_acc=0.753, train_acc=0.748]Test 5: Data size 400: : 60%|██████ | 6/10 [04:16<02:32, 38.12s/it, data_size=400, test_acc=0.843, train_acc=0.906]Test 5: Data size 400: : 70%|███████ | 7/10 [04:16<02:02, 40.80s/it, data_size=400, test_acc=0.843, train_acc=0.906]Test 5: Data size 432: : 70%|███████ | 7/10 [04:16<02:02, 40.80s/it, data_size=400, test_acc=0.843, train_acc=0.906]Test 5: Data size 432: : 70%|███████ | 7/10 [05:06<02:02, 40.80s/it, data_size=432, test_acc=0.863, train_acc=0.897]Test 5: Data size 432: : 80%|████████ | 8/10 [05:06<01:27, 43.66s/it, data_size=432, test_acc=0.863, train_acc=0.897]Test 5: Data size 464: : 80%|████████ | 8/10 [05:06<01:27, 43.66s/it, data_size=432, test_acc=0.863, train_acc=0.897]Test 5: Data size 464: : 80%|████████ | 8/10 [05:59<01:27, 43.66s/it, data_size=464, test_acc=0.872, train_acc=0.915]Test 5: Data size 464: : 90%|█████████ | 9/10 [05:59<00:46, 46.52s/it, data_size=464, test_acc=0.872, train_acc=0.915]Test 5: Data size 496: : 90%|█████████ | 9/10 [05:59<00:46, 46.52s/it, data_size=464, test_acc=0.872, train_acc=0.915]Test 5: Data size 496: : 90%|█████████ | 9/10 [06:55<00:46, 46.52s/it, data_size=496, test_acc=0.845, train_acc=0.898]Test 5: Data size 496: : 100%|██████████| 10/10 [06:55<00:00, 49.55s/it, data_size=496, test_acc=0.845, train_acc=0.898]Test 5: Data size 496: : 100%|██████████| 10/10 [06:55<00:00, 41.58s/it, data_size=496, test_acc=0.845, train_acc=0.898]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.702, train_acc=0.685]Test 6: Data size 208: : 10%|█ | 1/10 [00:26<03:57, 26.40s/it, data_size=208, test_acc=0.702, train_acc=0.685]Test 6: Data size 240: : 10%|█ | 1/10 [00:26<03:57, 26.40s/it, data_size=208, test_acc=0.702, train_acc=0.685]Test 6: Data size 240: : 10%|█ | 1/10 [00:55<03:57, 26.40s/it, data_size=240, test_acc=0.683, train_acc=0.693]Test 6: Data size 240: : 20%|██ | 2/10 [00:55<03:43, 27.96s/it, data_size=240, test_acc=0.683, train_acc=0.693]Test 6: Data size 272: : 20%|██ | 2/10 [00:55<03:43, 27.96s/it, data_size=240, test_acc=0.683, train_acc=0.693]Test 6: Data size 272: : 20%|██ | 2/10 [01:27<03:43, 27.96s/it, data_size=272, test_acc=0.704, train_acc=0.698]Test 6: Data size 272: : 30%|███ | 3/10 [01:27<03:29, 29.91s/it, data_size=272, test_acc=0.704, train_acc=0.698]Test 6: Data size 304: : 30%|███ | 3/10 [01:27<03:29, 29.91s/it, data_size=272, test_acc=0.704, train_acc=0.698]Test 6: Data size 304: : 30%|███ | 3/10 [02:03<03:29, 29.91s/it, data_size=304, test_acc=0.675, train_acc=0.688]Test 6: Data size 304: : 40%|████ | 4/10 [02:03<03:12, 32.12s/it, data_size=304, test_acc=0.675, train_acc=0.688]Test 6: Data size 336: : 40%|████ | 4/10 [02:03<03:12, 32.12s/it, data_size=304, test_acc=0.675, train_acc=0.688]Test 6: Data size 336: : 40%|████ | 4/10 [02:41<03:12, 32.12s/it, data_size=336, test_acc=0.724, train_acc=0.73] Test 6: Data size 336: : 50%|█████ | 5/10 [02:41<02:52, 34.43s/it, data_size=336, test_acc=0.724, train_acc=0.73]Test 6: Data size 368: : 50%|█████ | 5/10 [02:41<02:52, 34.43s/it, data_size=336, test_acc=0.724, train_acc=0.73]Test 6: Data size 368: : 50%|█████ | 5/10 [03:23<02:52, 34.43s/it, data_size=368, test_acc=0.785, train_acc=0.818]Test 6: Data size 368: : 60%|██████ | 6/10 [03:23<02:27, 36.96s/it, data_size=368, test_acc=0.785, train_acc=0.818]Test 6: Data size 400: : 60%|██████ | 6/10 [03:23<02:27, 36.96s/it, data_size=368, test_acc=0.785, train_acc=0.818]Test 6: Data size 400: : 60%|██████ | 6/10 [04:08<02:27, 36.96s/it, data_size=400, test_acc=0.827, train_acc=0.827]Test 6: Data size 400: : 70%|███████ | 7/10 [04:08<01:58, 39.65s/it, data_size=400, test_acc=0.827, train_acc=0.827]Test 6: Data size 432: : 70%|███████ | 7/10 [04:08<01:58, 39.65s/it, data_size=400, test_acc=0.827, train_acc=0.827]Test 6: Data size 432: : 70%|███████ | 7/10 [04:57<01:58, 39.65s/it, data_size=432, test_acc=0.839, train_acc=0.834]Test 6: Data size 432: : 80%|████████ | 8/10 [04:57<01:25, 42.52s/it, data_size=432, test_acc=0.839, train_acc=0.834]Test 6: Data size 464: : 80%|████████ | 8/10 [04:57<01:25, 42.52s/it, data_size=432, test_acc=0.839, train_acc=0.834]Test 6: Data size 464: : 80%|████████ | 8/10 [05:48<01:25, 42.52s/it, data_size=464, test_acc=0.821, train_acc=0.865]Test 6: Data size 464: : 90%|█████████ | 9/10 [05:49<00:45, 45.37s/it, data_size=464, test_acc=0.821, train_acc=0.865]Test 6: Data size 496: : 90%|█████████ | 9/10 [05:49<00:45, 45.37s/it, data_size=464, test_acc=0.821, train_acc=0.865]Test 6: Data size 496: : 90%|█████████ | 9/10 [06:43<00:45, 45.37s/it, data_size=496, test_acc=0.819, train_acc=0.863]Test 6: Data size 496: : 100%|██████████| 10/10 [06:43<00:00, 48.25s/it, data_size=496, test_acc=0.819, train_acc=0.863]Test 6: Data size 496: : 100%|██████████| 10/10 [06:43<00:00, 40.38s/it, data_size=496, test_acc=0.819, train_acc=0.863]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.715, train_acc=0.713]Test 7: Data size 208: : 10%|█ | 1/10 [00:26<04:00, 26.73s/it, data_size=208, test_acc=0.715, train_acc=0.713]Test 7: Data size 240: : 10%|█ | 1/10 [00:26<04:00, 26.73s/it, data_size=208, test_acc=0.715, train_acc=0.713]Test 7: Data size 240: : 10%|█ | 1/10 [00:56<04:00, 26.73s/it, data_size=240, test_acc=0.693, train_acc=0.701]Test 7: Data size 240: : 20%|██ | 2/10 [00:56<03:47, 28.38s/it, data_size=240, test_acc=0.693, train_acc=0.701]Test 7: Data size 272: : 20%|██ | 2/10 [00:56<03:47, 28.38s/it, data_size=240, test_acc=0.693, train_acc=0.701]Test 7: Data size 272: : 20%|██ | 2/10 [01:29<03:47, 28.38s/it, data_size=272, test_acc=0.713, train_acc=0.717]Test 7: Data size 272: : 30%|███ | 3/10 [01:29<03:33, 30.48s/it, data_size=272, test_acc=0.713, train_acc=0.717]Test 7: Data size 304: : 30%|███ | 3/10 [01:29<03:33, 30.48s/it, data_size=272, test_acc=0.713, train_acc=0.717]Test 7: Data size 304: : 30%|███ | 3/10 [02:04<03:33, 30.48s/it, data_size=304, test_acc=0.712, train_acc=0.731]Test 7: Data size 304: : 40%|████ | 4/10 [02:05<03:15, 32.61s/it, data_size=304, test_acc=0.712, train_acc=0.731]Test 7: Data size 336: : 40%|████ | 4/10 [02:05<03:15, 32.61s/it, data_size=304, test_acc=0.712, train_acc=0.731]Test 7: Data size 336: : 40%|████ | 4/10 [02:44<03:15, 32.61s/it, data_size=336, test_acc=0.735, train_acc=0.765]Test 7: Data size 336: : 50%|█████ | 5/10 [02:44<02:55, 35.02s/it, data_size=336, test_acc=0.735, train_acc=0.765]Test 7: Data size 368: : 50%|█████ | 5/10 [02:44<02:55, 35.02s/it, data_size=336, test_acc=0.735, train_acc=0.765]Test 7: Data size 368: : 50%|█████ | 5/10 [03:26<02:55, 35.02s/it, data_size=368, test_acc=0.756, train_acc=0.718]Test 7: Data size 368: : 60%|██████ | 6/10 [03:26<02:30, 37.56s/it, data_size=368, test_acc=0.756, train_acc=0.718]Test 7: Data size 400: : 60%|██████ | 6/10 [03:26<02:30, 37.56s/it, data_size=368, test_acc=0.756, train_acc=0.718]Test 7: Data size 400: : 60%|██████ | 6/10 [04:12<02:30, 37.56s/it, data_size=400, test_acc=0.835, train_acc=0.804]Test 7: Data size 400: : 70%|███████ | 7/10 [04:12<02:00, 40.26s/it, data_size=400, test_acc=0.835, train_acc=0.804]Test 7: Data size 432: : 70%|███████ | 7/10 [04:12<02:00, 40.26s/it, data_size=400, test_acc=0.835, train_acc=0.804]Test 7: Data size 432: : 70%|███████ | 7/10 [05:01<02:00, 40.26s/it, data_size=432, test_acc=0.812, train_acc=0.788]Test 7: Data size 432: : 80%|████████ | 8/10 [05:01<01:26, 43.04s/it, data_size=432, test_acc=0.812, train_acc=0.788]Test 7: Data size 464: : 80%|████████ | 8/10 [05:01<01:26, 43.04s/it, data_size=432, test_acc=0.812, train_acc=0.788]Test 7: Data size 464: : 80%|████████ | 8/10 [05:53<01:26, 43.04s/it, data_size=464, test_acc=0.851, train_acc=0.848]Test 7: Data size 464: : 90%|█████████ | 9/10 [05:53<00:45, 45.81s/it, data_size=464, test_acc=0.851, train_acc=0.848]Test 7: Data size 496: : 90%|█████████ | 9/10 [05:53<00:45, 45.81s/it, data_size=464, test_acc=0.851, train_acc=0.848]Test 7: Data size 496: : 90%|█████████ | 9/10 [06:48<00:45, 45.81s/it, data_size=496, test_acc=0.86, train_acc=0.864] Test 7: Data size 496: : 100%|██████████| 10/10 [06:48<00:00, 48.69s/it, data_size=496, test_acc=0.86, train_acc=0.864]Test 7: Data size 496: : 100%|██████████| 10/10 [06:48<00:00, 40.87s/it, data_size=496, test_acc=0.86, train_acc=0.864]
working on model Multimodal-middle-fusion-model-based-on-AlexNet with MIN_MAX
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.705, train_acc=0.724]Test 0: Data size 208: : 10%|█ | 1/10 [00:26<03:59, 26.62s/it, data_size=208, test_acc=0.705, train_acc=0.724]Test 0: Data size 240: : 10%|█ | 1/10 [00:26<03:59, 26.62s/it, data_size=208, test_acc=0.705, train_acc=0.724]Test 0: Data size 240: : 10%|█ | 1/10 [00:56<03:59, 26.62s/it, data_size=240, test_acc=0.721, train_acc=0.825]Test 0: Data size 240: : 20%|██ | 2/10 [00:56<03:47, 28.50s/it, data_size=240, test_acc=0.721, train_acc=0.825]Test 0: Data size 272: : 20%|██ | 2/10 [00:56<03:47, 28.50s/it, data_size=240, test_acc=0.721, train_acc=0.825]Test 0: Data size 272: : 20%|██ | 2/10 [01:28<03:47, 28.50s/it, data_size=272, test_acc=0.705, train_acc=0.753]Test 0: Data size 272: : 30%|███ | 3/10 [01:28<03:32, 30.36s/it, data_size=272, test_acc=0.705, train_acc=0.753]Test 0: Data size 304: : 30%|███ | 3/10 [01:28<03:32, 30.36s/it, data_size=272, test_acc=0.705, train_acc=0.753]Test 0: Data size 304: : 30%|███ | 3/10 [02:04<03:32, 30.36s/it, data_size=304, test_acc=0.759, train_acc=0.849]Test 0: Data size 304: : 40%|████ | 4/10 [02:04<03:15, 32.56s/it, data_size=304, test_acc=0.759, train_acc=0.849]Test 0: Data size 336: : 40%|████ | 4/10 [02:04<03:15, 32.56s/it, data_size=304, test_acc=0.759, train_acc=0.849]Test 0: Data size 336: : 40%|████ | 4/10 [02:43<03:15, 32.56s/it, data_size=336, test_acc=0.77, train_acc=0.84] Test 0: Data size 336: : 50%|█████ | 5/10 [02:43<02:54, 34.84s/it, data_size=336, test_acc=0.77, train_acc=0.84]Test 0: Data size 368: : 50%|█████ | 5/10 [02:43<02:54, 34.84s/it, data_size=336, test_acc=0.77, train_acc=0.84]Test 0: Data size 368: : 50%|█████ | 5/10 [03:25<02:54, 34.84s/it, data_size=368, test_acc=0.782, train_acc=0.824]Test 0: Data size 368: : 60%|██████ | 6/10 [03:25<02:29, 37.30s/it, data_size=368, test_acc=0.782, train_acc=0.824]Test 0: Data size 400: : 60%|██████ | 6/10 [03:25<02:29, 37.30s/it, data_size=368, test_acc=0.782, train_acc=0.824]Test 0: Data size 400: : 60%|██████ | 6/10 [04:11<02:29, 37.30s/it, data_size=400, test_acc=0.83, train_acc=0.869] Test 0: Data size 400: : 70%|███████ | 7/10 [04:11<01:59, 39.99s/it, data_size=400, test_acc=0.83, train_acc=0.869]Test 0: Data size 432: : 70%|███████ | 7/10 [04:11<01:59, 39.99s/it, data_size=400, test_acc=0.83, train_acc=0.869]Test 0: Data size 432: : 70%|███████ | 7/10 [05:00<01:59, 39.99s/it, data_size=432, test_acc=0.872, train_acc=0.81]Test 0: Data size 432: : 80%|████████ | 8/10 [05:00<01:25, 42.84s/it, data_size=432, test_acc=0.872, train_acc=0.81]Test 0: Data size 464: : 80%|████████ | 8/10 [05:00<01:25, 42.84s/it, data_size=432, test_acc=0.872, train_acc=0.81]Test 0: Data size 464: : 80%|████████ | 8/10 [05:52<01:25, 42.84s/it, data_size=464, test_acc=0.855, train_acc=0.892]Test 0: Data size 464: : 90%|█████████ | 9/10 [05:52<00:45, 45.78s/it, data_size=464, test_acc=0.855, train_acc=0.892]Test 0: Data size 496: : 90%|█████████ | 9/10 [05:52<00:45, 45.78s/it, data_size=464, test_acc=0.855, train_acc=0.892]Test 0: Data size 496: : 90%|█████████ | 9/10 [06:48<00:45, 45.78s/it, data_size=496, test_acc=0.842, train_acc=0.871]Test 0: Data size 496: : 100%|██████████| 10/10 [06:48<00:00, 48.89s/it, data_size=496, test_acc=0.842, train_acc=0.871]Test 0: Data size 496: : 100%|██████████| 10/10 [06:48<00:00, 40.85s/it, data_size=496, test_acc=0.842, train_acc=0.871]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.661, train_acc=0.655]Test 1: Data size 208: : 10%|█ | 1/10 [00:26<04:00, 26.72s/it, data_size=208, test_acc=0.661, train_acc=0.655]Test 1: Data size 240: : 10%|█ | 1/10 [00:26<04:00, 26.72s/it, data_size=208, test_acc=0.661, train_acc=0.655]Test 1: Data size 240: : 10%|█ | 1/10 [00:56<04:00, 26.72s/it, data_size=240, test_acc=0.768, train_acc=0.767]Test 1: Data size 240: : 20%|██ | 2/10 [00:56<03:47, 28.43s/it, data_size=240, test_acc=0.768, train_acc=0.767]Test 1: Data size 272: : 20%|██ | 2/10 [00:56<03:47, 28.43s/it, data_size=240, test_acc=0.768, train_acc=0.767]Test 1: Data size 272: : 20%|██ | 2/10 [01:29<03:47, 28.43s/it, data_size=272, test_acc=0.717, train_acc=0.711]Test 1: Data size 272: : 30%|███ | 3/10 [01:29<03:33, 30.53s/it, data_size=272, test_acc=0.717, train_acc=0.711]Test 1: Data size 304: : 30%|███ | 3/10 [01:29<03:33, 30.53s/it, data_size=272, test_acc=0.717, train_acc=0.711]Test 1: Data size 304: : 30%|███ | 3/10 [02:05<03:33, 30.53s/it, data_size=304, test_acc=0.733, train_acc=0.743]Test 1: Data size 304: : 40%|████ | 4/10 [02:05<03:15, 32.66s/it, data_size=304, test_acc=0.733, train_acc=0.743]Test 1: Data size 336: : 40%|████ | 4/10 [02:05<03:15, 32.66s/it, data_size=304, test_acc=0.733, train_acc=0.743]Test 1: Data size 336: : 40%|████ | 4/10 [02:44<03:15, 32.66s/it, data_size=336, test_acc=0.76, train_acc=0.774] Test 1: Data size 336: : 50%|█████ | 5/10 [02:44<02:55, 35.10s/it, data_size=336, test_acc=0.76, train_acc=0.774]Test 1: Data size 368: : 50%|█████ | 5/10 [02:44<02:55, 35.10s/it, data_size=336, test_acc=0.76, train_acc=0.774]Test 1: Data size 368: : 50%|█████ | 5/10 [03:27<02:55, 35.10s/it, data_size=368, test_acc=0.821, train_acc=0.846]Test 1: Data size 368: : 60%|██████ | 6/10 [03:27<02:30, 37.71s/it, data_size=368, test_acc=0.821, train_acc=0.846]Test 1: Data size 400: : 60%|██████ | 6/10 [03:27<02:30, 37.71s/it, data_size=368, test_acc=0.821, train_acc=0.846]Test 1: Data size 400: : 60%|██████ | 6/10 [04:13<02:30, 37.71s/it, data_size=400, test_acc=0.771, train_acc=0.793]Test 1: Data size 400: : 70%|███████ | 7/10 [04:13<02:01, 40.48s/it, data_size=400, test_acc=0.771, train_acc=0.793]Test 1: Data size 432: : 70%|███████ | 7/10 [04:13<02:01, 40.48s/it, data_size=400, test_acc=0.771, train_acc=0.793]Test 1: Data size 432: : 70%|███████ | 7/10 [05:03<02:01, 40.48s/it, data_size=432, test_acc=0.861, train_acc=0.85] Test 1: Data size 432: : 80%|████████ | 8/10 [05:03<01:26, 43.39s/it, data_size=432, test_acc=0.861, train_acc=0.85]Test 1: Data size 464: : 80%|████████ | 8/10 [05:03<01:26, 43.39s/it, data_size=432, test_acc=0.861, train_acc=0.85]Test 1: Data size 464: : 80%|████████ | 8/10 [05:55<01:26, 43.39s/it, data_size=464, test_acc=0.885, train_acc=0.874]Test 1: Data size 464: : 90%|█████████ | 9/10 [05:55<00:46, 46.20s/it, data_size=464, test_acc=0.885, train_acc=0.874]Test 1: Data size 496: : 90%|█████████ | 9/10 [05:55<00:46, 46.20s/it, data_size=464, test_acc=0.885, train_acc=0.874]Test 1: Data size 496: : 90%|█████████ | 9/10 [06:52<00:46, 46.20s/it, data_size=496, test_acc=0.83, train_acc=0.735] Test 1: Data size 496: : 100%|██████████| 10/10 [06:52<00:00, 49.41s/it, data_size=496, test_acc=0.83, train_acc=0.735]Test 1: Data size 496: : 100%|██████████| 10/10 [06:52<00:00, 41.23s/it, data_size=496, test_acc=0.83, train_acc=0.735]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.639, train_acc=0.665]Test 2: Data size 208: : 10%|█ | 1/10 [00:26<04:01, 26.82s/it, data_size=208, test_acc=0.639, train_acc=0.665]Test 2: Data size 240: : 10%|█ | 1/10 [00:26<04:01, 26.82s/it, data_size=208, test_acc=0.639, train_acc=0.665]Test 2: Data size 240: : 10%|█ | 1/10 [00:56<04:01, 26.82s/it, data_size=240, test_acc=0.725, train_acc=0.771]Test 2: Data size 240: : 20%|██ | 2/10 [00:56<03:48, 28.54s/it, data_size=240, test_acc=0.725, train_acc=0.771]Test 2: Data size 272: : 20%|██ | 2/10 [00:56<03:48, 28.54s/it, data_size=240, test_acc=0.725, train_acc=0.771]Test 2: Data size 272: : 20%|██ | 2/10 [01:29<03:48, 28.54s/it, data_size=272, test_acc=0.677, train_acc=0.707]Test 2: Data size 272: : 30%|███ | 3/10 [01:29<03:34, 30.65s/it, data_size=272, test_acc=0.677, train_acc=0.707]Test 2: Data size 304: : 30%|███ | 3/10 [01:29<03:34, 30.65s/it, data_size=272, test_acc=0.677, train_acc=0.707]Test 2: Data size 304: : 30%|███ | 3/10 [02:06<03:34, 30.65s/it, data_size=304, test_acc=0.627, train_acc=0.663]Test 2: Data size 304: : 40%|████ | 4/10 [02:06<03:17, 32.93s/it, data_size=304, test_acc=0.627, train_acc=0.663]Test 2: Data size 336: : 40%|████ | 4/10 [02:06<03:17, 32.93s/it, data_size=304, test_acc=0.627, train_acc=0.663]Test 2: Data size 336: : 40%|████ | 4/10 [02:45<03:17, 32.93s/it, data_size=336, test_acc=0.743, train_acc=0.774]Test 2: Data size 336: : 50%|█████ | 5/10 [02:45<02:56, 35.31s/it, data_size=336, test_acc=0.743, train_acc=0.774]Test 2: Data size 368: : 50%|█████ | 5/10 [02:45<02:56, 35.31s/it, data_size=336, test_acc=0.743, train_acc=0.774]Test 2: Data size 368: : 50%|█████ | 5/10 [03:28<02:56, 35.31s/it, data_size=368, test_acc=0.766, train_acc=0.861]Test 2: Data size 368: : 60%|██████ | 6/10 [03:28<02:31, 37.82s/it, data_size=368, test_acc=0.766, train_acc=0.861]Test 2: Data size 400: : 60%|██████ | 6/10 [03:28<02:31, 37.82s/it, data_size=368, test_acc=0.766, train_acc=0.861]Test 2: Data size 400: : 60%|██████ | 6/10 [04:14<02:31, 37.82s/it, data_size=400, test_acc=0.751, train_acc=0.82] Test 2: Data size 400: : 70%|███████ | 7/10 [04:14<02:01, 40.46s/it, data_size=400, test_acc=0.751, train_acc=0.82]Test 2: Data size 432: : 70%|███████ | 7/10 [04:14<02:01, 40.46s/it, data_size=400, test_acc=0.751, train_acc=0.82]Test 2: Data size 432: : 70%|███████ | 7/10 [05:03<02:01, 40.46s/it, data_size=432, test_acc=0.875, train_acc=0.923]Test 2: Data size 432: : 80%|████████ | 8/10 [05:03<01:26, 43.25s/it, data_size=432, test_acc=0.875, train_acc=0.923]Test 2: Data size 464: : 80%|████████ | 8/10 [05:03<01:26, 43.25s/it, data_size=432, test_acc=0.875, train_acc=0.923]Test 2: Data size 464: : 80%|████████ | 8/10 [05:56<01:26, 43.25s/it, data_size=464, test_acc=0.906, train_acc=0.906]Test 2: Data size 464: : 90%|█████████ | 9/10 [05:56<00:46, 46.22s/it, data_size=464, test_acc=0.906, train_acc=0.906]Test 2: Data size 496: : 90%|█████████ | 9/10 [05:56<00:46, 46.22s/it, data_size=464, test_acc=0.906, train_acc=0.906]Test 2: Data size 496: : 90%|█████████ | 9/10 [06:51<00:46, 46.22s/it, data_size=496, test_acc=0.908, train_acc=0.857]Test 2: Data size 496: : 100%|██████████| 10/10 [06:51<00:00, 49.12s/it, data_size=496, test_acc=0.908, train_acc=0.857]Test 2: Data size 496: : 100%|██████████| 10/10 [06:51<00:00, 41.19s/it, data_size=496, test_acc=0.908, train_acc=0.857]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.657, train_acc=0.696]Test 3: Data size 208: : 10%|█ | 1/10 [00:27<04:03, 27.09s/it, data_size=208, test_acc=0.657, train_acc=0.696]Test 3: Data size 240: : 10%|█ | 1/10 [00:27<04:03, 27.09s/it, data_size=208, test_acc=0.657, train_acc=0.696]Test 3: Data size 240: : 10%|█ | 1/10 [00:57<04:03, 27.09s/it, data_size=240, test_acc=0.725, train_acc=0.812]Test 3: Data size 240: : 20%|██ | 2/10 [00:57<03:51, 28.91s/it, data_size=240, test_acc=0.725, train_acc=0.812]Test 3: Data size 272: : 20%|██ | 2/10 [00:57<03:51, 28.91s/it, data_size=240, test_acc=0.725, train_acc=0.812]Test 3: Data size 272: : 20%|██ | 2/10 [01:30<03:51, 28.91s/it, data_size=272, test_acc=0.767, train_acc=0.832]Test 3: Data size 272: : 30%|███ | 3/10 [01:30<03:36, 30.93s/it, data_size=272, test_acc=0.767, train_acc=0.832]Test 3: Data size 304: : 30%|███ | 3/10 [01:30<03:36, 30.93s/it, data_size=272, test_acc=0.767, train_acc=0.832]Test 3: Data size 304: : 30%|███ | 3/10 [02:07<03:36, 30.93s/it, data_size=304, test_acc=0.771, train_acc=0.872]Test 3: Data size 304: : 40%|████ | 4/10 [02:07<03:18, 33.16s/it, data_size=304, test_acc=0.771, train_acc=0.872]Test 3: Data size 336: : 40%|████ | 4/10 [02:07<03:18, 33.16s/it, data_size=304, test_acc=0.771, train_acc=0.872]Test 3: Data size 336: : 40%|████ | 4/10 [02:47<03:18, 33.16s/it, data_size=336, test_acc=0.885, train_acc=0.897]Test 3: Data size 336: : 50%|█████ | 5/10 [02:47<02:58, 35.62s/it, data_size=336, test_acc=0.885, train_acc=0.897]Test 3: Data size 368: : 50%|█████ | 5/10 [02:47<02:58, 35.62s/it, data_size=336, test_acc=0.885, train_acc=0.897]Test 3: Data size 368: : 50%|█████ | 5/10 [03:30<02:58, 35.62s/it, data_size=368, test_acc=0.843, train_acc=0.871]Test 3: Data size 368: : 60%|██████ | 6/10 [03:30<02:32, 38.20s/it, data_size=368, test_acc=0.843, train_acc=0.871]Test 3: Data size 400: : 60%|██████ | 6/10 [03:30<02:32, 38.20s/it, data_size=368, test_acc=0.843, train_acc=0.871]Test 3: Data size 400: : 60%|██████ | 6/10 [04:17<02:32, 38.20s/it, data_size=400, test_acc=0.876, train_acc=0.874]Test 3: Data size 400: : 70%|███████ | 7/10 [04:17<02:03, 41.16s/it, data_size=400, test_acc=0.876, train_acc=0.874]Test 3: Data size 432: : 70%|███████ | 7/10 [04:17<02:03, 41.16s/it, data_size=400, test_acc=0.876, train_acc=0.874]Test 3: Data size 432: : 70%|███████ | 7/10 [05:07<02:03, 41.16s/it, data_size=432, test_acc=0.891, train_acc=0.906]Test 3: Data size 432: : 80%|████████ | 8/10 [05:07<01:27, 43.96s/it, data_size=432, test_acc=0.891, train_acc=0.906]Test 3: Data size 464: : 80%|████████ | 8/10 [05:07<01:27, 43.96s/it, data_size=432, test_acc=0.891, train_acc=0.906]Test 3: Data size 464: : 80%|████████ | 8/10 [06:00<01:27, 43.96s/it, data_size=464, test_acc=0.888, train_acc=0.876]Test 3: Data size 464: : 90%|█████████ | 9/10 [06:01<00:46, 46.92s/it, data_size=464, test_acc=0.888, train_acc=0.876]Test 3: Data size 496: : 90%|█████████ | 9/10 [06:01<00:46, 46.92s/it, data_size=464, test_acc=0.888, train_acc=0.876]Test 3: Data size 496: : 90%|█████████ | 9/10 [06:57<00:46, 46.92s/it, data_size=496, test_acc=0.783, train_acc=0.771]Test 3: Data size 496: : 100%|██████████| 10/10 [06:58<00:00, 50.06s/it, data_size=496, test_acc=0.783, train_acc=0.771]Test 3: Data size 496: : 100%|██████████| 10/10 [06:58<00:00, 41.81s/it, data_size=496, test_acc=0.783, train_acc=0.771]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.598, train_acc=0.629]Test 4: Data size 208: : 10%|█ | 1/10 [00:26<04:00, 26.68s/it, data_size=208, test_acc=0.598, train_acc=0.629]Test 4: Data size 240: : 10%|█ | 1/10 [00:26<04:00, 26.68s/it, data_size=208, test_acc=0.598, train_acc=0.629]Test 4: Data size 240: : 10%|█ | 1/10 [00:56<04:00, 26.68s/it, data_size=240, test_acc=0.719, train_acc=0.801]Test 4: Data size 240: : 20%|██ | 2/10 [00:56<03:49, 28.67s/it, data_size=240, test_acc=0.719, train_acc=0.801]Test 4: Data size 272: : 20%|██ | 2/10 [00:56<03:49, 28.67s/it, data_size=240, test_acc=0.719, train_acc=0.801]Test 4: Data size 272: : 20%|██ | 2/10 [01:29<03:49, 28.67s/it, data_size=272, test_acc=0.659, train_acc=0.67] Test 4: Data size 272: : 30%|███ | 3/10 [01:29<03:35, 30.75s/it, data_size=272, test_acc=0.659, train_acc=0.67]Test 4: Data size 304: : 30%|███ | 3/10 [01:29<03:35, 30.75s/it, data_size=272, test_acc=0.659, train_acc=0.67]Test 4: Data size 304: : 30%|███ | 3/10 [02:05<03:35, 30.75s/it, data_size=304, test_acc=0.755, train_acc=0.816]Test 4: Data size 304: : 40%|████ | 4/10 [02:05<03:16, 32.80s/it, data_size=304, test_acc=0.755, train_acc=0.816]Test 4: Data size 336: : 40%|████ | 4/10 [02:05<03:16, 32.80s/it, data_size=304, test_acc=0.755, train_acc=0.816]Test 4: Data size 336: : 40%|████ | 4/10 [02:45<03:16, 32.80s/it, data_size=336, test_acc=0.713, train_acc=0.758]Test 4: Data size 336: : 50%|█████ | 5/10 [02:45<02:57, 35.40s/it, data_size=336, test_acc=0.713, train_acc=0.758]Test 4: Data size 368: : 50%|█████ | 5/10 [02:45<02:57, 35.40s/it, data_size=336, test_acc=0.713, train_acc=0.758]Test 4: Data size 368: : 50%|█████ | 5/10 [03:28<02:57, 35.40s/it, data_size=368, test_acc=0.813, train_acc=0.84] Test 4: Data size 368: : 60%|██████ | 6/10 [03:28<02:31, 37.94s/it, data_size=368, test_acc=0.813, train_acc=0.84]Test 4: Data size 400: : 60%|██████ | 6/10 [03:28<02:31, 37.94s/it, data_size=368, test_acc=0.813, train_acc=0.84]Test 4: Data size 400: : 60%|██████ | 6/10 [04:15<02:31, 37.94s/it, data_size=400, test_acc=0.837, train_acc=0.873]Test 4: Data size 400: : 70%|███████ | 7/10 [04:15<02:02, 40.81s/it, data_size=400, test_acc=0.837, train_acc=0.873]Test 4: Data size 432: : 70%|███████ | 7/10 [04:15<02:02, 40.81s/it, data_size=400, test_acc=0.837, train_acc=0.873]Test 4: Data size 432: : 70%|███████ | 7/10 [05:05<02:02, 40.81s/it, data_size=432, test_acc=0.884, train_acc=0.872]Test 4: Data size 432: : 80%|████████ | 8/10 [05:05<01:27, 43.62s/it, data_size=432, test_acc=0.884, train_acc=0.872]Test 4: Data size 464: : 80%|████████ | 8/10 [05:05<01:27, 43.62s/it, data_size=432, test_acc=0.884, train_acc=0.872]Test 4: Data size 464: : 80%|████████ | 8/10 [05:58<01:27, 43.62s/it, data_size=464, test_acc=0.869, train_acc=0.881]Test 4: Data size 464: : 90%|█████████ | 9/10 [05:58<00:46, 46.70s/it, data_size=464, test_acc=0.869, train_acc=0.881]Test 4: Data size 496: : 90%|█████████ | 9/10 [05:58<00:46, 46.70s/it, data_size=464, test_acc=0.869, train_acc=0.881]Test 4: Data size 496: : 90%|█████████ | 9/10 [06:55<00:46, 46.70s/it, data_size=496, test_acc=0.801, train_acc=0.729]Test 4: Data size 496: : 100%|██████████| 10/10 [06:55<00:00, 49.74s/it, data_size=496, test_acc=0.801, train_acc=0.729]Test 4: Data size 496: : 100%|██████████| 10/10 [06:55<00:00, 41.52s/it, data_size=496, test_acc=0.801, train_acc=0.729]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:27<?, ?it/s, data_size=208, test_acc=0.701, train_acc=0.697]Test 5: Data size 208: : 10%|█ | 1/10 [00:27<04:04, 27.17s/it, data_size=208, test_acc=0.701, train_acc=0.697]Test 5: Data size 240: : 10%|█ | 1/10 [00:27<04:04, 27.17s/it, data_size=208, test_acc=0.701, train_acc=0.697]Test 5: Data size 240: : 10%|█ | 1/10 [00:57<04:04, 27.17s/it, data_size=240, test_acc=0.719, train_acc=0.794]Test 5: Data size 240: : 20%|██ | 2/10 [00:57<03:52, 29.06s/it, data_size=240, test_acc=0.719, train_acc=0.794]Test 5: Data size 272: : 20%|██ | 2/10 [00:57<03:52, 29.06s/it, data_size=240, test_acc=0.719, train_acc=0.794]Test 5: Data size 272: : 20%|██ | 2/10 [01:30<03:52, 29.06s/it, data_size=272, test_acc=0.713, train_acc=0.776]Test 5: Data size 272: : 30%|███ | 3/10 [01:30<03:37, 31.03s/it, data_size=272, test_acc=0.713, train_acc=0.776]Test 5: Data size 304: : 30%|███ | 3/10 [01:30<03:37, 31.03s/it, data_size=272, test_acc=0.713, train_acc=0.776]Test 5: Data size 304: : 30%|███ | 3/10 [02:07<03:37, 31.03s/it, data_size=304, test_acc=0.76, train_acc=0.839] Test 5: Data size 304: : 40%|████ | 4/10 [02:07<03:19, 33.21s/it, data_size=304, test_acc=0.76, train_acc=0.839]Test 5: Data size 336: : 40%|████ | 4/10 [02:07<03:19, 33.21s/it, data_size=304, test_acc=0.76, train_acc=0.839]Test 5: Data size 336: : 40%|████ | 4/10 [02:46<03:19, 33.21s/it, data_size=336, test_acc=0.78, train_acc=0.835]Test 5: Data size 336: : 50%|█████ | 5/10 [02:47<02:57, 35.52s/it, data_size=336, test_acc=0.78, train_acc=0.835]Test 5: Data size 368: : 50%|█████ | 5/10 [02:47<02:57, 35.52s/it, data_size=336, test_acc=0.78, train_acc=0.835]Test 5: Data size 368: : 50%|█████ | 5/10 [03:30<02:57, 35.52s/it, data_size=368, test_acc=0.76, train_acc=0.767]Test 5: Data size 368: : 60%|██████ | 6/10 [03:30<02:32, 38.09s/it, data_size=368, test_acc=0.76, train_acc=0.767]Test 5: Data size 400: : 60%|██████ | 6/10 [03:30<02:32, 38.09s/it, data_size=368, test_acc=0.76, train_acc=0.767]Test 5: Data size 400: : 60%|██████ | 6/10 [04:16<02:32, 38.09s/it, data_size=400, test_acc=0.739, train_acc=0.799]Test 5: Data size 400: : 70%|███████ | 7/10 [04:16<02:02, 40.76s/it, data_size=400, test_acc=0.739, train_acc=0.799]Test 5: Data size 432: : 70%|███████ | 7/10 [04:16<02:02, 40.76s/it, data_size=400, test_acc=0.739, train_acc=0.799]Test 5: Data size 432: : 70%|███████ | 7/10 [05:06<02:02, 40.76s/it, data_size=432, test_acc=0.777, train_acc=0.882]Test 5: Data size 432: : 80%|████████ | 8/10 [05:06<01:27, 43.71s/it, data_size=432, test_acc=0.777, train_acc=0.882]Test 5: Data size 464: : 80%|████████ | 8/10 [05:06<01:27, 43.71s/it, data_size=432, test_acc=0.777, train_acc=0.882]Test 5: Data size 464: : 80%|████████ | 8/10 [05:59<01:27, 43.71s/it, data_size=464, test_acc=0.791, train_acc=0.85] Test 5: Data size 464: : 90%|█████████ | 9/10 [05:59<00:46, 46.73s/it, data_size=464, test_acc=0.791, train_acc=0.85]Test 5: Data size 496: : 90%|█████████ | 9/10 [05:59<00:46, 46.73s/it, data_size=464, test_acc=0.791, train_acc=0.85]Test 5: Data size 496: : 90%|█████████ | 9/10 [06:56<00:46, 46.73s/it, data_size=496, test_acc=0.817, train_acc=0.778]Test 5: Data size 496: : 100%|██████████| 10/10 [06:56<00:00, 49.79s/it, data_size=496, test_acc=0.817, train_acc=0.778]Test 5: Data size 496: : 100%|██████████| 10/10 [06:56<00:00, 41.65s/it, data_size=496, test_acc=0.817, train_acc=0.778]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.699, train_acc=0.685]Test 6: Data size 208: : 10%|█ | 1/10 [00:26<03:57, 26.36s/it, data_size=208, test_acc=0.699, train_acc=0.685]Test 6: Data size 240: : 10%|█ | 1/10 [00:26<03:57, 26.36s/it, data_size=208, test_acc=0.699, train_acc=0.685]Test 6: Data size 240: : 10%|█ | 1/10 [00:56<03:57, 26.36s/it, data_size=240, test_acc=0.727, train_acc=0.724]Test 6: Data size 240: : 20%|██ | 2/10 [00:56<03:46, 28.37s/it, data_size=240, test_acc=0.727, train_acc=0.724]Test 6: Data size 272: : 20%|██ | 2/10 [00:56<03:46, 28.37s/it, data_size=240, test_acc=0.727, train_acc=0.724]Test 6: Data size 272: : 20%|██ | 2/10 [01:28<03:46, 28.37s/it, data_size=272, test_acc=0.704, train_acc=0.722]Test 6: Data size 272: : 30%|███ | 3/10 [01:28<03:31, 30.18s/it, data_size=272, test_acc=0.704, train_acc=0.722]Test 6: Data size 304: : 30%|███ | 3/10 [01:28<03:31, 30.18s/it, data_size=272, test_acc=0.704, train_acc=0.722]Test 6: Data size 304: : 30%|███ | 3/10 [02:03<03:31, 30.18s/it, data_size=304, test_acc=0.612, train_acc=0.701]Test 6: Data size 304: : 40%|████ | 4/10 [02:03<03:13, 32.19s/it, data_size=304, test_acc=0.612, train_acc=0.701]Test 6: Data size 336: : 40%|████ | 4/10 [02:03<03:13, 32.19s/it, data_size=304, test_acc=0.612, train_acc=0.701]Test 6: Data size 336: : 40%|████ | 4/10 [02:42<03:13, 32.19s/it, data_size=336, test_acc=0.696, train_acc=0.779]Test 6: Data size 336: : 50%|█████ | 5/10 [02:42<02:52, 34.48s/it, data_size=336, test_acc=0.696, train_acc=0.779]Test 6: Data size 368: : 50%|█████ | 5/10 [02:42<02:52, 34.48s/it, data_size=336, test_acc=0.696, train_acc=0.779]Test 6: Data size 368: : 50%|█████ | 5/10 [03:23<02:52, 34.48s/it, data_size=368, test_acc=0.683, train_acc=0.776]Test 6: Data size 368: : 60%|██████ | 6/10 [03:24<02:27, 36.98s/it, data_size=368, test_acc=0.683, train_acc=0.776]Test 6: Data size 400: : 60%|██████ | 6/10 [03:24<02:27, 36.98s/it, data_size=368, test_acc=0.683, train_acc=0.776]Test 6: Data size 400: : 60%|██████ | 6/10 [04:08<02:27, 36.98s/it, data_size=400, test_acc=0.79, train_acc=0.823] Test 6: Data size 400: : 70%|███████ | 7/10 [04:09<01:58, 39.58s/it, data_size=400, test_acc=0.79, train_acc=0.823]Test 6: Data size 432: : 70%|███████ | 7/10 [04:09<01:58, 39.58s/it, data_size=400, test_acc=0.79, train_acc=0.823]Test 6: Data size 432: : 70%|███████ | 7/10 [04:57<01:58, 39.58s/it, data_size=432, test_acc=0.881, train_acc=0.908]Test 6: Data size 432: : 80%|████████ | 8/10 [04:57<01:24, 42.31s/it, data_size=432, test_acc=0.881, train_acc=0.908]Test 6: Data size 464: : 80%|████████ | 8/10 [04:57<01:24, 42.31s/it, data_size=432, test_acc=0.881, train_acc=0.908]Test 6: Data size 464: : 80%|████████ | 8/10 [05:48<01:24, 42.31s/it, data_size=464, test_acc=0.825, train_acc=0.86] Test 6: Data size 464: : 90%|█████████ | 9/10 [05:49<00:45, 45.28s/it, data_size=464, test_acc=0.825, train_acc=0.86]Test 6: Data size 496: : 90%|█████████ | 9/10 [05:49<00:45, 45.28s/it, data_size=464, test_acc=0.825, train_acc=0.86]Test 6: Data size 496: : 90%|█████████ | 9/10 [06:43<00:45, 45.28s/it, data_size=496, test_acc=0.862, train_acc=0.866]Test 6: Data size 496: : 100%|██████████| 10/10 [06:43<00:00, 48.21s/it, data_size=496, test_acc=0.862, train_acc=0.866]Test 6: Data size 496: : 100%|██████████| 10/10 [06:43<00:00, 40.38s/it, data_size=496, test_acc=0.862, train_acc=0.866]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.637, train_acc=0.659]Test 7: Data size 208: : 10%|█ | 1/10 [00:26<04:01, 26.83s/it, data_size=208, test_acc=0.637, train_acc=0.659]Test 7: Data size 240: : 10%|█ | 1/10 [00:26<04:01, 26.83s/it, data_size=208, test_acc=0.637, train_acc=0.659]Test 7: Data size 240: : 10%|█ | 1/10 [00:56<04:01, 26.83s/it, data_size=240, test_acc=0.739, train_acc=0.802]Test 7: Data size 240: : 20%|██ | 2/10 [00:56<03:48, 28.52s/it, data_size=240, test_acc=0.739, train_acc=0.802]Test 7: Data size 272: : 20%|██ | 2/10 [00:56<03:48, 28.52s/it, data_size=240, test_acc=0.739, train_acc=0.802]Test 7: Data size 272: : 20%|██ | 2/10 [01:29<03:48, 28.52s/it, data_size=272, test_acc=0.737, train_acc=0.797]Test 7: Data size 272: : 30%|███ | 3/10 [01:29<03:33, 30.53s/it, data_size=272, test_acc=0.737, train_acc=0.797]Test 7: Data size 304: : 30%|███ | 3/10 [01:29<03:33, 30.53s/it, data_size=272, test_acc=0.737, train_acc=0.797]Test 7: Data size 304: : 30%|███ | 3/10 [02:05<03:33, 30.53s/it, data_size=304, test_acc=0.744, train_acc=0.837]Test 7: Data size 304: : 40%|████ | 4/10 [02:05<03:16, 32.69s/it, data_size=304, test_acc=0.744, train_acc=0.837]Test 7: Data size 336: : 40%|████ | 4/10 [02:05<03:16, 32.69s/it, data_size=304, test_acc=0.744, train_acc=0.837]Test 7: Data size 336: : 40%|████ | 4/10 [02:44<03:16, 32.69s/it, data_size=336, test_acc=0.636, train_acc=0.72] Test 7: Data size 336: : 50%|█████ | 5/10 [02:44<02:55, 35.07s/it, data_size=336, test_acc=0.636, train_acc=0.72]Test 7: Data size 368: : 50%|█████ | 5/10 [02:44<02:55, 35.07s/it, data_size=336, test_acc=0.636, train_acc=0.72]Test 7: Data size 368: : 50%|█████ | 5/10 [03:27<02:55, 35.07s/it, data_size=368, test_acc=0.725, train_acc=0.814]Test 7: Data size 368: : 60%|██████ | 6/10 [03:27<02:30, 37.62s/it, data_size=368, test_acc=0.725, train_acc=0.814]Test 7: Data size 400: : 60%|██████ | 6/10 [03:27<02:30, 37.62s/it, data_size=368, test_acc=0.725, train_acc=0.814]Test 7: Data size 400: : 60%|██████ | 6/10 [04:12<02:30, 37.62s/it, data_size=400, test_acc=0.853, train_acc=0.814]Test 7: Data size 400: : 70%|███████ | 7/10 [04:13<02:00, 40.29s/it, data_size=400, test_acc=0.853, train_acc=0.814]Test 7: Data size 432: : 70%|███████ | 7/10 [04:13<02:00, 40.29s/it, data_size=400, test_acc=0.853, train_acc=0.814]Test 7: Data size 432: : 70%|███████ | 7/10 [05:02<02:00, 40.29s/it, data_size=432, test_acc=0.797, train_acc=0.811]Test 7: Data size 432: : 80%|████████ | 8/10 [05:02<01:26, 43.20s/it, data_size=432, test_acc=0.797, train_acc=0.811]Test 7: Data size 464: : 80%|████████ | 8/10 [05:02<01:26, 43.20s/it, data_size=432, test_acc=0.797, train_acc=0.811]Test 7: Data size 464: : 80%|████████ | 8/10 [05:54<01:26, 43.20s/it, data_size=464, test_acc=0.885, train_acc=0.811]Test 7: Data size 464: : 90%|█████████ | 9/10 [05:54<00:46, 46.01s/it, data_size=464, test_acc=0.885, train_acc=0.811]Test 7: Data size 496: : 90%|█████████ | 9/10 [05:54<00:46, 46.01s/it, data_size=464, test_acc=0.885, train_acc=0.811]Test 7: Data size 496: : 90%|█████████ | 9/10 [06:50<00:46, 46.01s/it, data_size=496, test_acc=0.909, train_acc=0.908]Test 7: Data size 496: : 100%|██████████| 10/10 [06:50<00:00, 49.05s/it, data_size=496, test_acc=0.909, train_acc=0.908]Test 7: Data size 496: : 100%|██████████| 10/10 [06:50<00:00, 41.06s/it, data_size=496, test_acc=0.909, train_acc=0.908]
working on model Multimodal-middle-fusion-model-based-on-AlexNet with MIN_MARGIN
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.704, train_acc=0.72]Test 0: Data size 208: : 10%|█ | 1/10 [00:26<03:58, 26.51s/it, data_size=208, test_acc=0.704, train_acc=0.72]Test 0: Data size 240: : 10%|█ | 1/10 [00:26<03:58, 26.51s/it, data_size=208, test_acc=0.704, train_acc=0.72]Test 0: Data size 240: : 10%|█ | 1/10 [00:56<03:58, 26.51s/it, data_size=240, test_acc=0.694, train_acc=0.719]Test 0: Data size 240: : 20%|██ | 2/10 [00:56<03:47, 28.47s/it, data_size=240, test_acc=0.694, train_acc=0.719]Test 0: Data size 272: : 20%|██ | 2/10 [00:56<03:47, 28.47s/it, data_size=240, test_acc=0.694, train_acc=0.719]Test 0: Data size 272: : 20%|██ | 2/10 [01:28<03:47, 28.47s/it, data_size=272, test_acc=0.738, train_acc=0.777]Test 0: Data size 272: : 30%|███ | 3/10 [01:28<03:32, 30.37s/it, data_size=272, test_acc=0.738, train_acc=0.777]Test 0: Data size 304: : 30%|███ | 3/10 [01:28<03:32, 30.37s/it, data_size=272, test_acc=0.738, train_acc=0.777]Test 0: Data size 304: : 30%|███ | 3/10 [02:04<03:32, 30.37s/it, data_size=304, test_acc=0.766, train_acc=0.773]Test 0: Data size 304: : 40%|████ | 4/10 [02:04<03:15, 32.53s/it, data_size=304, test_acc=0.766, train_acc=0.773]Test 0: Data size 336: : 40%|████ | 4/10 [02:04<03:15, 32.53s/it, data_size=304, test_acc=0.766, train_acc=0.773]Test 0: Data size 336: : 40%|████ | 4/10 [02:43<03:15, 32.53s/it, data_size=336, test_acc=0.705, train_acc=0.683]Test 0: Data size 336: : 50%|█████ | 5/10 [02:43<02:53, 34.80s/it, data_size=336, test_acc=0.705, train_acc=0.683]Test 0: Data size 368: : 50%|█████ | 5/10 [02:43<02:53, 34.80s/it, data_size=336, test_acc=0.705, train_acc=0.683]Test 0: Data size 368: : 50%|█████ | 5/10 [03:25<02:53, 34.80s/it, data_size=368, test_acc=0.712, train_acc=0.696]Test 0: Data size 368: : 60%|██████ | 6/10 [03:25<02:29, 37.27s/it, data_size=368, test_acc=0.712, train_acc=0.696]Test 0: Data size 400: : 60%|██████ | 6/10 [03:25<02:29, 37.27s/it, data_size=368, test_acc=0.712, train_acc=0.696]Test 0: Data size 400: : 60%|██████ | 6/10 [04:11<02:29, 37.27s/it, data_size=400, test_acc=0.883, train_acc=0.855]Test 0: Data size 400: : 70%|███████ | 7/10 [04:11<01:59, 40.00s/it, data_size=400, test_acc=0.883, train_acc=0.855]Test 0: Data size 432: : 70%|███████ | 7/10 [04:11<01:59, 40.00s/it, data_size=400, test_acc=0.883, train_acc=0.855]Test 0: Data size 432: : 70%|███████ | 7/10 [05:00<01:59, 40.00s/it, data_size=432, test_acc=0.814, train_acc=0.8] Test 0: Data size 432: : 80%|████████ | 8/10 [05:00<01:25, 42.84s/it, data_size=432, test_acc=0.814, train_acc=0.8]Test 0: Data size 464: : 80%|████████ | 8/10 [05:00<01:25, 42.84s/it, data_size=432, test_acc=0.814, train_acc=0.8]Test 0: Data size 464: : 80%|████████ | 8/10 [05:52<01:25, 42.84s/it, data_size=464, test_acc=0.818, train_acc=0.781]Test 0: Data size 464: : 90%|█████████ | 9/10 [05:52<00:45, 45.77s/it, data_size=464, test_acc=0.818, train_acc=0.781]Test 0: Data size 496: : 90%|█████████ | 9/10 [05:52<00:45, 45.77s/it, data_size=464, test_acc=0.818, train_acc=0.781]Test 0: Data size 496: : 90%|█████████ | 9/10 [06:48<00:45, 45.77s/it, data_size=496, test_acc=0.81, train_acc=0.818] Test 0: Data size 496: : 100%|██████████| 10/10 [06:48<00:00, 48.85s/it, data_size=496, test_acc=0.81, train_acc=0.818]Test 0: Data size 496: : 100%|██████████| 10/10 [06:48<00:00, 40.82s/it, data_size=496, test_acc=0.81, train_acc=0.818]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.566, train_acc=0.558]Test 1: Data size 208: : 10%|█ | 1/10 [00:26<04:00, 26.77s/it, data_size=208, test_acc=0.566, train_acc=0.558]Test 1: Data size 240: : 10%|█ | 1/10 [00:26<04:00, 26.77s/it, data_size=208, test_acc=0.566, train_acc=0.558]Test 1: Data size 240: : 10%|█ | 1/10 [00:56<04:00, 26.77s/it, data_size=240, test_acc=0.691, train_acc=0.709]Test 1: Data size 240: : 20%|██ | 2/10 [00:56<03:48, 28.51s/it, data_size=240, test_acc=0.691, train_acc=0.709]Test 1: Data size 272: : 20%|██ | 2/10 [00:56<03:48, 28.51s/it, data_size=240, test_acc=0.691, train_acc=0.709]Test 1: Data size 272: : 20%|██ | 2/10 [01:29<03:48, 28.51s/it, data_size=272, test_acc=0.716, train_acc=0.729]Test 1: Data size 272: : 30%|███ | 3/10 [01:29<03:34, 30.60s/it, data_size=272, test_acc=0.716, train_acc=0.729]Test 1: Data size 304: : 30%|███ | 3/10 [01:29<03:34, 30.60s/it, data_size=272, test_acc=0.716, train_acc=0.729]Test 1: Data size 304: : 30%|███ | 3/10 [02:05<03:34, 30.60s/it, data_size=304, test_acc=0.654, train_acc=0.65] Test 1: Data size 304: : 40%|████ | 4/10 [02:05<03:16, 32.74s/it, data_size=304, test_acc=0.654, train_acc=0.65]Test 1: Data size 336: : 40%|████ | 4/10 [02:05<03:16, 32.74s/it, data_size=304, test_acc=0.654, train_acc=0.65]Test 1: Data size 336: : 40%|████ | 4/10 [02:44<03:16, 32.74s/it, data_size=336, test_acc=0.713, train_acc=0.758]Test 1: Data size 336: : 50%|█████ | 5/10 [02:45<02:55, 35.18s/it, data_size=336, test_acc=0.713, train_acc=0.758]Test 1: Data size 368: : 50%|█████ | 5/10 [02:45<02:55, 35.18s/it, data_size=336, test_acc=0.713, train_acc=0.758]Test 1: Data size 368: : 50%|█████ | 5/10 [03:27<02:55, 35.18s/it, data_size=368, test_acc=0.777, train_acc=0.801]Test 1: Data size 368: : 60%|██████ | 6/10 [03:27<02:30, 37.72s/it, data_size=368, test_acc=0.777, train_acc=0.801]Test 1: Data size 400: : 60%|██████ | 6/10 [03:27<02:30, 37.72s/it, data_size=368, test_acc=0.777, train_acc=0.801]Test 1: Data size 400: : 60%|██████ | 6/10 [04:13<02:30, 37.72s/it, data_size=400, test_acc=0.766, train_acc=0.781]Test 1: Data size 400: : 70%|███████ | 7/10 [04:13<02:01, 40.42s/it, data_size=400, test_acc=0.766, train_acc=0.781]Test 1: Data size 432: : 70%|███████ | 7/10 [04:13<02:01, 40.42s/it, data_size=400, test_acc=0.766, train_acc=0.781]Test 1: Data size 432: : 70%|███████ | 7/10 [05:03<02:01, 40.42s/it, data_size=432, test_acc=0.807, train_acc=0.834]Test 1: Data size 432: : 80%|████████ | 8/10 [05:03<01:26, 43.40s/it, data_size=432, test_acc=0.807, train_acc=0.834]Test 1: Data size 464: : 80%|████████ | 8/10 [05:03<01:26, 43.40s/it, data_size=432, test_acc=0.807, train_acc=0.834]Test 1: Data size 464: : 80%|████████ | 8/10 [05:56<01:26, 43.40s/it, data_size=464, test_acc=0.877, train_acc=0.882]Test 1: Data size 464: : 90%|█████████ | 9/10 [05:56<00:46, 46.28s/it, data_size=464, test_acc=0.877, train_acc=0.882]Test 1: Data size 496: : 90%|█████████ | 9/10 [05:56<00:46, 46.28s/it, data_size=464, test_acc=0.877, train_acc=0.882]Test 1: Data size 496: : 90%|█████████ | 9/10 [06:52<00:46, 46.28s/it, data_size=496, test_acc=0.878, train_acc=0.866]Test 1: Data size 496: : 100%|██████████| 10/10 [06:52<00:00, 49.42s/it, data_size=496, test_acc=0.878, train_acc=0.866]Test 1: Data size 496: : 100%|██████████| 10/10 [06:52<00:00, 41.26s/it, data_size=496, test_acc=0.878, train_acc=0.866]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.641, train_acc=0.665]Test 2: Data size 208: : 10%|█ | 1/10 [00:26<03:59, 26.61s/it, data_size=208, test_acc=0.641, train_acc=0.665]Test 2: Data size 240: : 10%|█ | 1/10 [00:26<03:59, 26.61s/it, data_size=208, test_acc=0.641, train_acc=0.665]Test 2: Data size 240: : 10%|█ | 1/10 [00:56<03:59, 26.61s/it, data_size=240, test_acc=0.589, train_acc=0.599]Test 2: Data size 240: : 20%|██ | 2/10 [00:56<03:48, 28.51s/it, data_size=240, test_acc=0.589, train_acc=0.599]Test 2: Data size 272: : 20%|██ | 2/10 [00:56<03:48, 28.51s/it, data_size=240, test_acc=0.589, train_acc=0.599]Test 2: Data size 272: : 20%|██ | 2/10 [01:28<03:48, 28.51s/it, data_size=272, test_acc=0.737, train_acc=0.802]Test 2: Data size 272: : 30%|███ | 3/10 [01:28<03:32, 30.34s/it, data_size=272, test_acc=0.737, train_acc=0.802]Test 2: Data size 304: : 30%|███ | 3/10 [01:28<03:32, 30.34s/it, data_size=272, test_acc=0.737, train_acc=0.802]Test 2: Data size 304: : 30%|███ | 3/10 [02:05<03:32, 30.34s/it, data_size=304, test_acc=0.749, train_acc=0.77] Test 2: Data size 304: : 40%|████ | 4/10 [02:05<03:16, 32.67s/it, data_size=304, test_acc=0.749, train_acc=0.77]Test 2: Data size 336: : 40%|████ | 4/10 [02:05<03:16, 32.67s/it, data_size=304, test_acc=0.749, train_acc=0.77]Test 2: Data size 336: : 40%|████ | 4/10 [02:44<03:16, 32.67s/it, data_size=336, test_acc=0.57, train_acc=0.543]Test 2: Data size 336: : 50%|█████ | 5/10 [02:44<02:55, 35.00s/it, data_size=336, test_acc=0.57, train_acc=0.543]Test 2: Data size 368: : 50%|█████ | 5/10 [02:44<02:55, 35.00s/it, data_size=336, test_acc=0.57, train_acc=0.543]Test 2: Data size 368: : 50%|█████ | 5/10 [03:26<02:55, 35.00s/it, data_size=368, test_acc=0.806, train_acc=0.829]Test 2: Data size 368: : 60%|██████ | 6/10 [03:26<02:30, 37.51s/it, data_size=368, test_acc=0.806, train_acc=0.829]Test 2: Data size 400: : 60%|██████ | 6/10 [03:26<02:30, 37.51s/it, data_size=368, test_acc=0.806, train_acc=0.829]Test 2: Data size 400: : 60%|██████ | 6/10 [04:12<02:30, 37.51s/it, data_size=400, test_acc=0.841, train_acc=0.859]Test 2: Data size 400: : 70%|███████ | 7/10 [04:13<02:01, 40.41s/it, data_size=400, test_acc=0.841, train_acc=0.859]Test 2: Data size 432: : 70%|███████ | 7/10 [04:13<02:01, 40.41s/it, data_size=400, test_acc=0.841, train_acc=0.859]Test 2: Data size 432: : 70%|███████ | 7/10 [05:02<02:01, 40.41s/it, data_size=432, test_acc=0.847, train_acc=0.868]Test 2: Data size 432: : 80%|████████ | 8/10 [05:02<01:26, 43.33s/it, data_size=432, test_acc=0.847, train_acc=0.868]Test 2: Data size 464: : 80%|████████ | 8/10 [05:02<01:26, 43.33s/it, data_size=432, test_acc=0.847, train_acc=0.868]Test 2: Data size 464: : 80%|████████ | 8/10 [05:55<01:26, 43.33s/it, data_size=464, test_acc=0.868, train_acc=0.898]Test 2: Data size 464: : 90%|█████████ | 9/10 [05:55<00:46, 46.38s/it, data_size=464, test_acc=0.868, train_acc=0.898]Test 2: Data size 496: : 90%|█████████ | 9/10 [05:55<00:46, 46.38s/it, data_size=464, test_acc=0.868, train_acc=0.898]Test 2: Data size 496: : 90%|█████████ | 9/10 [06:51<00:46, 46.38s/it, data_size=496, test_acc=0.851, train_acc=0.837]Test 2: Data size 496: : 100%|██████████| 10/10 [06:51<00:00, 49.40s/it, data_size=496, test_acc=0.851, train_acc=0.837]Test 2: Data size 496: : 100%|██████████| 10/10 [06:51<00:00, 41.19s/it, data_size=496, test_acc=0.851, train_acc=0.837]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.734, train_acc=0.755]Test 3: Data size 208: : 10%|█ | 1/10 [00:26<04:01, 26.78s/it, data_size=208, test_acc=0.734, train_acc=0.755]Test 3: Data size 240: : 10%|█ | 1/10 [00:26<04:01, 26.78s/it, data_size=208, test_acc=0.734, train_acc=0.755]Test 3: Data size 240: : 10%|█ | 1/10 [00:56<04:01, 26.78s/it, data_size=240, test_acc=0.761, train_acc=0.774]Test 3: Data size 240: : 20%|██ | 2/10 [00:56<03:48, 28.52s/it, data_size=240, test_acc=0.761, train_acc=0.774]Test 3: Data size 272: : 20%|██ | 2/10 [00:56<03:48, 28.52s/it, data_size=240, test_acc=0.761, train_acc=0.774]Test 3: Data size 272: : 20%|██ | 2/10 [01:29<03:48, 28.52s/it, data_size=272, test_acc=0.761, train_acc=0.768]Test 3: Data size 272: : 30%|███ | 3/10 [01:29<03:33, 30.49s/it, data_size=272, test_acc=0.761, train_acc=0.768]Test 3: Data size 304: : 30%|███ | 3/10 [01:29<03:33, 30.49s/it, data_size=272, test_acc=0.761, train_acc=0.768]Test 3: Data size 304: : 30%|███ | 3/10 [02:05<03:33, 30.49s/it, data_size=304, test_acc=0.752, train_acc=0.745]Test 3: Data size 304: : 40%|████ | 4/10 [02:05<03:15, 32.64s/it, data_size=304, test_acc=0.752, train_acc=0.745]Test 3: Data size 336: : 40%|████ | 4/10 [02:05<03:15, 32.64s/it, data_size=304, test_acc=0.752, train_acc=0.745]Test 3: Data size 336: : 40%|████ | 4/10 [02:44<03:15, 32.64s/it, data_size=336, test_acc=0.733, train_acc=0.691]Test 3: Data size 336: : 50%|█████ | 5/10 [02:44<02:55, 35.04s/it, data_size=336, test_acc=0.733, train_acc=0.691]Test 3: Data size 368: : 50%|█████ | 5/10 [02:44<02:55, 35.04s/it, data_size=336, test_acc=0.733, train_acc=0.691]Test 3: Data size 368: : 50%|█████ | 5/10 [03:27<02:55, 35.04s/it, data_size=368, test_acc=0.899, train_acc=0.86] Test 3: Data size 368: : 60%|██████ | 6/10 [03:27<02:30, 37.67s/it, data_size=368, test_acc=0.899, train_acc=0.86]Test 3: Data size 400: : 60%|██████ | 6/10 [03:27<02:30, 37.67s/it, data_size=368, test_acc=0.899, train_acc=0.86]Test 3: Data size 400: : 60%|██████ | 6/10 [04:13<02:30, 37.67s/it, data_size=400, test_acc=0.845, train_acc=0.832]Test 3: Data size 400: : 70%|███████ | 7/10 [04:13<02:01, 40.39s/it, data_size=400, test_acc=0.845, train_acc=0.832]Test 3: Data size 432: : 70%|███████ | 7/10 [04:13<02:01, 40.39s/it, data_size=400, test_acc=0.845, train_acc=0.832]Test 3: Data size 432: : 70%|███████ | 7/10 [05:02<02:01, 40.39s/it, data_size=432, test_acc=0.854, train_acc=0.795]Test 3: Data size 432: : 80%|████████ | 8/10 [05:02<01:26, 43.30s/it, data_size=432, test_acc=0.854, train_acc=0.795]Test 3: Data size 464: : 80%|████████ | 8/10 [05:02<01:26, 43.30s/it, data_size=432, test_acc=0.854, train_acc=0.795]Test 3: Data size 464: : 80%|████████ | 8/10 [05:55<01:26, 43.30s/it, data_size=464, test_acc=0.848, train_acc=0.733]Test 3: Data size 464: : 90%|█████████ | 9/10 [05:55<00:46, 46.13s/it, data_size=464, test_acc=0.848, train_acc=0.733]Test 3: Data size 496: : 90%|█████████ | 9/10 [05:55<00:46, 46.13s/it, data_size=464, test_acc=0.848, train_acc=0.733]Test 3: Data size 496: : 90%|█████████ | 9/10 [06:50<00:46, 46.13s/it, data_size=496, test_acc=0.888, train_acc=0.855]Test 3: Data size 496: : 100%|██████████| 10/10 [06:51<00:00, 49.14s/it, data_size=496, test_acc=0.888, train_acc=0.855]Test 3: Data size 496: : 100%|██████████| 10/10 [06:51<00:00, 41.11s/it, data_size=496, test_acc=0.888, train_acc=0.855]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.658, train_acc=0.656]Test 4: Data size 208: : 10%|█ | 1/10 [00:26<04:01, 26.87s/it, data_size=208, test_acc=0.658, train_acc=0.656]Test 4: Data size 240: : 10%|█ | 1/10 [00:26<04:01, 26.87s/it, data_size=208, test_acc=0.658, train_acc=0.656]Test 4: Data size 240: : 10%|█ | 1/10 [00:56<04:01, 26.87s/it, data_size=240, test_acc=0.724, train_acc=0.765]Test 4: Data size 240: : 20%|██ | 2/10 [00:56<03:48, 28.56s/it, data_size=240, test_acc=0.724, train_acc=0.765]Test 4: Data size 272: : 20%|██ | 2/10 [00:56<03:48, 28.56s/it, data_size=240, test_acc=0.724, train_acc=0.765]Test 4: Data size 272: : 20%|██ | 2/10 [01:29<03:48, 28.56s/it, data_size=272, test_acc=0.743, train_acc=0.79] Test 4: Data size 272: : 30%|███ | 3/10 [01:29<03:34, 30.63s/it, data_size=272, test_acc=0.743, train_acc=0.79]Test 4: Data size 304: : 30%|███ | 3/10 [01:29<03:34, 30.63s/it, data_size=272, test_acc=0.743, train_acc=0.79]Test 4: Data size 304: : 30%|███ | 3/10 [02:06<03:34, 30.63s/it, data_size=304, test_acc=0.745, train_acc=0.833]Test 4: Data size 304: : 40%|████ | 4/10 [02:06<03:17, 32.94s/it, data_size=304, test_acc=0.745, train_acc=0.833]Test 4: Data size 336: : 40%|████ | 4/10 [02:06<03:17, 32.94s/it, data_size=304, test_acc=0.745, train_acc=0.833]Test 4: Data size 336: : 40%|████ | 4/10 [02:45<03:17, 32.94s/it, data_size=336, test_acc=0.83, train_acc=0.825] Test 4: Data size 336: : 50%|█████ | 5/10 [02:45<02:56, 35.26s/it, data_size=336, test_acc=0.83, train_acc=0.825]Test 4: Data size 368: : 50%|█████ | 5/10 [02:45<02:56, 35.26s/it, data_size=336, test_acc=0.83, train_acc=0.825]Test 4: Data size 368: : 50%|█████ | 5/10 [03:28<02:56, 35.26s/it, data_size=368, test_acc=0.872, train_acc=0.855]Test 4: Data size 368: : 60%|██████ | 6/10 [03:28<02:31, 37.75s/it, data_size=368, test_acc=0.872, train_acc=0.855]Test 4: Data size 400: : 60%|██████ | 6/10 [03:28<02:31, 37.75s/it, data_size=368, test_acc=0.872, train_acc=0.855]Test 4: Data size 400: : 60%|██████ | 6/10 [04:13<02:31, 37.75s/it, data_size=400, test_acc=0.808, train_acc=0.784]Test 4: Data size 400: : 70%|███████ | 7/10 [04:14<02:01, 40.43s/it, data_size=400, test_acc=0.808, train_acc=0.784]Test 4: Data size 432: : 70%|███████ | 7/10 [04:14<02:01, 40.43s/it, data_size=400, test_acc=0.808, train_acc=0.784]Test 4: Data size 432: : 70%|███████ | 7/10 [05:02<02:01, 40.43s/it, data_size=432, test_acc=0.894, train_acc=0.862]Test 4: Data size 432: : 80%|████████ | 8/10 [05:03<01:26, 43.16s/it, data_size=432, test_acc=0.894, train_acc=0.862]Test 4: Data size 464: : 80%|████████ | 8/10 [05:03<01:26, 43.16s/it, data_size=432, test_acc=0.894, train_acc=0.862]Test 4: Data size 464: : 80%|████████ | 8/10 [05:55<01:26, 43.16s/it, data_size=464, test_acc=0.872, train_acc=0.886]Test 4: Data size 464: : 90%|█████████ | 9/10 [05:55<00:46, 46.11s/it, data_size=464, test_acc=0.872, train_acc=0.886]Test 4: Data size 496: : 90%|█████████ | 9/10 [05:55<00:46, 46.11s/it, data_size=464, test_acc=0.872, train_acc=0.886]Test 4: Data size 496: : 90%|█████████ | 9/10 [06:51<00:46, 46.11s/it, data_size=496, test_acc=0.881, train_acc=0.907]Test 4: Data size 496: : 100%|██████████| 10/10 [06:51<00:00, 49.06s/it, data_size=496, test_acc=0.881, train_acc=0.907]Test 4: Data size 496: : 100%|██████████| 10/10 [06:51<00:00, 41.14s/it, data_size=496, test_acc=0.881, train_acc=0.907]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.714, train_acc=0.725]Test 5: Data size 208: : 10%|█ | 1/10 [00:26<04:02, 26.95s/it, data_size=208, test_acc=0.714, train_acc=0.725]Test 5: Data size 240: : 10%|█ | 1/10 [00:26<04:02, 26.95s/it, data_size=208, test_acc=0.714, train_acc=0.725]Test 5: Data size 240: : 10%|█ | 1/10 [00:56<04:02, 26.95s/it, data_size=240, test_acc=0.733, train_acc=0.794]Test 5: Data size 240: : 20%|██ | 2/10 [00:56<03:49, 28.66s/it, data_size=240, test_acc=0.733, train_acc=0.794]Test 5: Data size 272: : 20%|██ | 2/10 [00:56<03:49, 28.66s/it, data_size=240, test_acc=0.733, train_acc=0.794]Test 5: Data size 272: : 20%|██ | 2/10 [01:29<03:49, 28.66s/it, data_size=272, test_acc=0.684, train_acc=0.731]Test 5: Data size 272: : 30%|███ | 3/10 [01:29<03:34, 30.68s/it, data_size=272, test_acc=0.684, train_acc=0.731]Test 5: Data size 304: : 30%|███ | 3/10 [01:29<03:34, 30.68s/it, data_size=272, test_acc=0.684, train_acc=0.731]Test 5: Data size 304: : 30%|███ | 3/10 [02:06<03:34, 30.68s/it, data_size=304, test_acc=0.787, train_acc=0.812]Test 5: Data size 304: : 40%|████ | 4/10 [02:06<03:17, 32.90s/it, data_size=304, test_acc=0.787, train_acc=0.812]Test 5: Data size 336: : 40%|████ | 4/10 [02:06<03:17, 32.90s/it, data_size=304, test_acc=0.787, train_acc=0.812]Test 5: Data size 336: : 40%|████ | 4/10 [02:45<03:17, 32.90s/it, data_size=336, test_acc=0.764, train_acc=0.795]Test 5: Data size 336: : 50%|█████ | 5/10 [02:46<02:57, 35.43s/it, data_size=336, test_acc=0.764, train_acc=0.795]Test 5: Data size 368: : 50%|█████ | 5/10 [02:46<02:57, 35.43s/it, data_size=336, test_acc=0.764, train_acc=0.795]Test 5: Data size 368: : 50%|█████ | 5/10 [03:28<02:57, 35.43s/it, data_size=368, test_acc=0.748, train_acc=0.777]Test 5: Data size 368: : 60%|██████ | 6/10 [03:29<02:32, 38.00s/it, data_size=368, test_acc=0.748, train_acc=0.777]Test 5: Data size 400: : 60%|██████ | 6/10 [03:29<02:32, 38.00s/it, data_size=368, test_acc=0.748, train_acc=0.777]Test 5: Data size 400: : 60%|██████ | 6/10 [04:15<02:32, 38.00s/it, data_size=400, test_acc=0.739, train_acc=0.798]Test 5: Data size 400: : 70%|███████ | 7/10 [04:16<02:02, 40.93s/it, data_size=400, test_acc=0.739, train_acc=0.798]Test 5: Data size 432: : 70%|███████ | 7/10 [04:16<02:02, 40.93s/it, data_size=400, test_acc=0.739, train_acc=0.798]Test 5: Data size 432: : 70%|███████ | 7/10 [05:05<02:02, 40.93s/it, data_size=432, test_acc=0.764, train_acc=0.825]Test 5: Data size 432: : 80%|████████ | 8/10 [05:05<01:27, 43.67s/it, data_size=432, test_acc=0.764, train_acc=0.825]Test 5: Data size 464: : 80%|████████ | 8/10 [05:05<01:27, 43.67s/it, data_size=432, test_acc=0.764, train_acc=0.825]Test 5: Data size 464: : 80%|████████ | 8/10 [05:58<01:27, 43.67s/it, data_size=464, test_acc=0.717, train_acc=0.721]Test 5: Data size 464: : 90%|█████████ | 9/10 [05:58<00:46, 46.58s/it, data_size=464, test_acc=0.717, train_acc=0.721]Test 5: Data size 496: : 90%|█████████ | 9/10 [05:58<00:46, 46.58s/it, data_size=464, test_acc=0.717, train_acc=0.721]Test 5: Data size 496: : 90%|█████████ | 9/10 [06:54<00:46, 46.58s/it, data_size=496, test_acc=0.759, train_acc=0.774]Test 5: Data size 496: : 100%|██████████| 10/10 [06:54<00:00, 49.53s/it, data_size=496, test_acc=0.759, train_acc=0.774]Test 5: Data size 496: : 100%|██████████| 10/10 [06:54<00:00, 41.47s/it, data_size=496, test_acc=0.759, train_acc=0.774]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.585, train_acc=0.595]Test 6: Data size 208: : 10%|█ | 1/10 [00:26<03:59, 26.61s/it, data_size=208, test_acc=0.585, train_acc=0.595]Test 6: Data size 240: : 10%|█ | 1/10 [00:26<03:59, 26.61s/it, data_size=208, test_acc=0.585, train_acc=0.595]Test 6: Data size 240: : 10%|█ | 1/10 [00:56<03:59, 26.61s/it, data_size=240, test_acc=0.71, train_acc=0.696] Test 6: Data size 240: : 20%|██ | 2/10 [00:56<03:48, 28.56s/it, data_size=240, test_acc=0.71, train_acc=0.696]Test 6: Data size 272: : 20%|██ | 2/10 [00:56<03:48, 28.56s/it, data_size=240, test_acc=0.71, train_acc=0.696]Test 6: Data size 272: : 20%|██ | 2/10 [01:29<03:48, 28.56s/it, data_size=272, test_acc=0.721, train_acc=0.752]Test 6: Data size 272: : 30%|███ | 3/10 [01:29<03:34, 30.65s/it, data_size=272, test_acc=0.721, train_acc=0.752]Test 6: Data size 304: : 30%|███ | 3/10 [01:29<03:34, 30.65s/it, data_size=272, test_acc=0.721, train_acc=0.752]Test 6: Data size 304: : 30%|███ | 3/10 [02:05<03:34, 30.65s/it, data_size=304, test_acc=0.646, train_acc=0.669]Test 6: Data size 304: : 40%|████ | 4/10 [02:05<03:16, 32.68s/it, data_size=304, test_acc=0.646, train_acc=0.669]Test 6: Data size 336: : 40%|████ | 4/10 [02:05<03:16, 32.68s/it, data_size=304, test_acc=0.646, train_acc=0.669]Test 6: Data size 336: : 40%|████ | 4/10 [02:44<03:16, 32.68s/it, data_size=336, test_acc=0.739, train_acc=0.783]Test 6: Data size 336: : 50%|█████ | 5/10 [02:44<02:55, 35.13s/it, data_size=336, test_acc=0.739, train_acc=0.783]Test 6: Data size 368: : 50%|█████ | 5/10 [02:44<02:55, 35.13s/it, data_size=336, test_acc=0.739, train_acc=0.783]Test 6: Data size 368: : 50%|█████ | 5/10 [03:27<02:55, 35.13s/it, data_size=368, test_acc=0.799, train_acc=0.794]Test 6: Data size 368: : 60%|██████ | 6/10 [03:27<02:30, 37.65s/it, data_size=368, test_acc=0.799, train_acc=0.794]Test 6: Data size 400: : 60%|██████ | 6/10 [03:27<02:30, 37.65s/it, data_size=368, test_acc=0.799, train_acc=0.794]Test 6: Data size 400: : 60%|██████ | 6/10 [04:13<02:30, 37.65s/it, data_size=400, test_acc=0.851, train_acc=0.868]Test 6: Data size 400: : 70%|███████ | 7/10 [04:13<02:00, 40.32s/it, data_size=400, test_acc=0.851, train_acc=0.868]Test 6: Data size 432: : 70%|███████ | 7/10 [04:13<02:00, 40.32s/it, data_size=400, test_acc=0.851, train_acc=0.868]Test 6: Data size 432: : 70%|███████ | 7/10 [05:02<02:00, 40.32s/it, data_size=432, test_acc=0.833, train_acc=0.81] Test 6: Data size 432: : 80%|████████ | 8/10 [05:02<01:26, 43.09s/it, data_size=432, test_acc=0.833, train_acc=0.81]Test 6: Data size 464: : 80%|████████ | 8/10 [05:02<01:26, 43.09s/it, data_size=432, test_acc=0.833, train_acc=0.81]Test 6: Data size 464: : 80%|████████ | 8/10 [05:54<01:26, 43.09s/it, data_size=464, test_acc=0.804, train_acc=0.786]Test 6: Data size 464: : 90%|█████████ | 9/10 [05:55<00:46, 46.09s/it, data_size=464, test_acc=0.804, train_acc=0.786]Test 6: Data size 496: : 90%|█████████ | 9/10 [05:55<00:46, 46.09s/it, data_size=464, test_acc=0.804, train_acc=0.786]Test 6: Data size 496: : 90%|█████████ | 9/10 [06:50<00:46, 46.09s/it, data_size=496, test_acc=0.868, train_acc=0.875]Test 6: Data size 496: : 100%|██████████| 10/10 [06:50<00:00, 49.11s/it, data_size=496, test_acc=0.868, train_acc=0.875]Test 6: Data size 496: : 100%|██████████| 10/10 [06:50<00:00, 41.09s/it, data_size=496, test_acc=0.868, train_acc=0.875]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:27<?, ?it/s, data_size=208, test_acc=0.688, train_acc=0.696]Test 7: Data size 208: : 10%|█ | 1/10 [00:27<04:05, 27.27s/it, data_size=208, test_acc=0.688, train_acc=0.696]Test 7: Data size 240: : 10%|█ | 1/10 [00:27<04:05, 27.27s/it, data_size=208, test_acc=0.688, train_acc=0.696]Test 7: Data size 240: : 10%|█ | 1/10 [00:57<04:05, 27.27s/it, data_size=240, test_acc=0.7, train_acc=0.721] Test 7: Data size 240: : 20%|██ | 2/10 [00:57<03:52, 29.10s/it, data_size=240, test_acc=0.7, train_acc=0.721]Test 7: Data size 272: : 20%|██ | 2/10 [00:57<03:52, 29.10s/it, data_size=240, test_acc=0.7, train_acc=0.721]Test 7: Data size 272: : 20%|██ | 2/10 [01:30<03:52, 29.10s/it, data_size=272, test_acc=0.734, train_acc=0.764]Test 7: Data size 272: : 30%|███ | 3/10 [01:31<03:37, 31.05s/it, data_size=272, test_acc=0.734, train_acc=0.764]Test 7: Data size 304: : 30%|███ | 3/10 [01:31<03:37, 31.05s/it, data_size=272, test_acc=0.734, train_acc=0.764]Test 7: Data size 304: : 30%|███ | 3/10 [02:07<03:37, 31.05s/it, data_size=304, test_acc=0.719, train_acc=0.75] Test 7: Data size 304: : 40%|████ | 4/10 [02:07<03:19, 33.25s/it, data_size=304, test_acc=0.719, train_acc=0.75]Test 7: Data size 336: : 40%|████ | 4/10 [02:07<03:19, 33.25s/it, data_size=304, test_acc=0.719, train_acc=0.75]Test 7: Data size 336: : 40%|████ | 4/10 [02:47<03:19, 33.25s/it, data_size=336, test_acc=0.734, train_acc=0.762]Test 7: Data size 336: : 50%|█████ | 5/10 [02:47<02:58, 35.64s/it, data_size=336, test_acc=0.734, train_acc=0.762]Test 7: Data size 368: : 50%|█████ | 5/10 [02:47<02:58, 35.64s/it, data_size=336, test_acc=0.734, train_acc=0.762]Test 7: Data size 368: : 50%|█████ | 5/10 [03:30<02:58, 35.64s/it, data_size=368, test_acc=0.714, train_acc=0.749]Test 7: Data size 368: : 60%|██████ | 6/10 [03:30<02:32, 38.23s/it, data_size=368, test_acc=0.714, train_acc=0.749]Test 7: Data size 400: : 60%|██████ | 6/10 [03:30<02:32, 38.23s/it, data_size=368, test_acc=0.714, train_acc=0.749]Test 7: Data size 400: : 60%|██████ | 6/10 [04:17<02:32, 38.23s/it, data_size=400, test_acc=0.736, train_acc=0.803]Test 7: Data size 400: : 70%|███████ | 7/10 [04:17<02:02, 40.93s/it, data_size=400, test_acc=0.736, train_acc=0.803]Test 7: Data size 432: : 70%|███████ | 7/10 [04:17<02:02, 40.93s/it, data_size=400, test_acc=0.736, train_acc=0.803]Test 7: Data size 432: : 70%|███████ | 7/10 [05:07<02:02, 40.93s/it, data_size=432, test_acc=0.756, train_acc=0.799]Test 7: Data size 432: : 80%|████████ | 8/10 [05:07<01:27, 43.84s/it, data_size=432, test_acc=0.756, train_acc=0.799]Test 7: Data size 464: : 80%|████████ | 8/10 [05:07<01:27, 43.84s/it, data_size=432, test_acc=0.756, train_acc=0.799]Test 7: Data size 464: : 80%|████████ | 8/10 [06:00<01:27, 43.84s/it, data_size=464, test_acc=0.877, train_acc=0.852]Test 7: Data size 464: : 90%|█████████ | 9/10 [06:00<00:46, 46.77s/it, data_size=464, test_acc=0.877, train_acc=0.852]Test 7: Data size 496: : 90%|█████████ | 9/10 [06:00<00:46, 46.77s/it, data_size=464, test_acc=0.877, train_acc=0.852]Test 7: Data size 496: : 90%|█████████ | 9/10 [06:56<00:46, 46.77s/it, data_size=496, test_acc=0.903, train_acc=0.871]Test 7: Data size 496: : 100%|██████████| 10/10 [06:56<00:00, 49.74s/it, data_size=496, test_acc=0.903, train_acc=0.871]Test 7: Data size 496: : 100%|██████████| 10/10 [06:56<00:00, 41.69s/it, data_size=496, test_acc=0.903, train_acc=0.871]
working on model Multimodal-middle-fusion-model-based-on-AlexNet with MAX_ENTROPY
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.704, train_acc=0.72]Test 0: Data size 208: : 10%|█ | 1/10 [00:26<04:00, 26.67s/it, data_size=208, test_acc=0.704, train_acc=0.72]Test 0: Data size 240: : 10%|█ | 1/10 [00:26<04:00, 26.67s/it, data_size=208, test_acc=0.704, train_acc=0.72]Test 0: Data size 240: : 10%|█ | 1/10 [00:56<04:00, 26.67s/it, data_size=240, test_acc=0.712, train_acc=0.792]Test 0: Data size 240: : 20%|██ | 2/10 [00:56<03:49, 28.65s/it, data_size=240, test_acc=0.712, train_acc=0.792]Test 0: Data size 272: : 20%|██ | 2/10 [00:56<03:49, 28.65s/it, data_size=240, test_acc=0.712, train_acc=0.792]Test 0: Data size 272: : 20%|██ | 2/10 [01:29<03:49, 28.65s/it, data_size=272, test_acc=0.694, train_acc=0.725]Test 0: Data size 272: : 30%|███ | 3/10 [01:30<03:35, 30.77s/it, data_size=272, test_acc=0.694, train_acc=0.725]Test 0: Data size 304: : 30%|███ | 3/10 [01:30<03:35, 30.77s/it, data_size=272, test_acc=0.694, train_acc=0.725]Test 0: Data size 304: : 30%|███ | 3/10 [02:05<03:35, 30.77s/it, data_size=304, test_acc=0.698, train_acc=0.736]Test 0: Data size 304: : 40%|████ | 4/10 [02:05<03:16, 32.74s/it, data_size=304, test_acc=0.698, train_acc=0.736]Test 0: Data size 336: : 40%|████ | 4/10 [02:05<03:16, 32.74s/it, data_size=304, test_acc=0.698, train_acc=0.736]Test 0: Data size 336: : 40%|████ | 4/10 [02:45<03:16, 32.74s/it, data_size=336, test_acc=0.738, train_acc=0.853]Test 0: Data size 336: : 50%|█████ | 5/10 [02:45<02:56, 35.22s/it, data_size=336, test_acc=0.738, train_acc=0.853]Test 0: Data size 368: : 50%|█████ | 5/10 [02:45<02:56, 35.22s/it, data_size=336, test_acc=0.738, train_acc=0.853]Test 0: Data size 368: : 50%|█████ | 5/10 [03:27<02:56, 35.22s/it, data_size=368, test_acc=0.787, train_acc=0.839]Test 0: Data size 368: : 60%|██████ | 6/10 [03:27<02:30, 37.73s/it, data_size=368, test_acc=0.787, train_acc=0.839]Test 0: Data size 400: : 60%|██████ | 6/10 [03:27<02:30, 37.73s/it, data_size=368, test_acc=0.787, train_acc=0.839]Test 0: Data size 400: : 60%|██████ | 6/10 [04:13<02:30, 37.73s/it, data_size=400, test_acc=0.763, train_acc=0.836]Test 0: Data size 400: : 70%|███████ | 7/10 [04:13<02:01, 40.38s/it, data_size=400, test_acc=0.763, train_acc=0.836]Test 0: Data size 432: : 70%|███████ | 7/10 [04:13<02:01, 40.38s/it, data_size=400, test_acc=0.763, train_acc=0.836]Test 0: Data size 432: : 70%|███████ | 7/10 [05:02<02:01, 40.38s/it, data_size=432, test_acc=0.831, train_acc=0.797]Test 0: Data size 432: : 80%|████████ | 8/10 [05:03<01:26, 43.19s/it, data_size=432, test_acc=0.831, train_acc=0.797]Test 0: Data size 464: : 80%|████████ | 8/10 [05:03<01:26, 43.19s/it, data_size=432, test_acc=0.831, train_acc=0.797]Test 0: Data size 464: : 80%|████████ | 8/10 [05:55<01:26, 43.19s/it, data_size=464, test_acc=0.72, train_acc=0.732] Test 0: Data size 464: : 90%|█████████ | 9/10 [05:55<00:46, 46.21s/it, data_size=464, test_acc=0.72, train_acc=0.732]Test 0: Data size 496: : 90%|█████████ | 9/10 [05:55<00:46, 46.21s/it, data_size=464, test_acc=0.72, train_acc=0.732]Test 0: Data size 496: : 90%|█████████ | 9/10 [06:51<00:46, 46.21s/it, data_size=496, test_acc=0.866, train_acc=0.889]Test 0: Data size 496: : 100%|██████████| 10/10 [06:51<00:00, 49.21s/it, data_size=496, test_acc=0.866, train_acc=0.889]Test 0: Data size 496: : 100%|██████████| 10/10 [06:51<00:00, 41.18s/it, data_size=496, test_acc=0.866, train_acc=0.889]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:27<?, ?it/s, data_size=208, test_acc=0.659, train_acc=0.65]Test 1: Data size 208: : 10%|█ | 1/10 [00:27<04:04, 27.19s/it, data_size=208, test_acc=0.659, train_acc=0.65]Test 1: Data size 240: : 10%|█ | 1/10 [00:27<04:04, 27.19s/it, data_size=208, test_acc=0.659, train_acc=0.65]Test 1: Data size 240: : 10%|█ | 1/10 [00:57<04:04, 27.19s/it, data_size=240, test_acc=0.779, train_acc=0.795]Test 1: Data size 240: : 20%|██ | 2/10 [00:57<03:52, 29.06s/it, data_size=240, test_acc=0.779, train_acc=0.795]Test 1: Data size 272: : 20%|██ | 2/10 [00:57<03:52, 29.06s/it, data_size=240, test_acc=0.779, train_acc=0.795]Test 1: Data size 272: : 20%|██ | 2/10 [01:30<03:52, 29.06s/it, data_size=272, test_acc=0.733, train_acc=0.762]Test 1: Data size 272: : 30%|███ | 3/10 [01:31<03:37, 31.11s/it, data_size=272, test_acc=0.733, train_acc=0.762]Test 1: Data size 304: : 30%|███ | 3/10 [01:31<03:37, 31.11s/it, data_size=272, test_acc=0.733, train_acc=0.762]Test 1: Data size 304: : 30%|███ | 3/10 [02:07<03:37, 31.11s/it, data_size=304, test_acc=0.777, train_acc=0.778]Test 1: Data size 304: : 40%|████ | 4/10 [02:07<03:19, 33.26s/it, data_size=304, test_acc=0.777, train_acc=0.778]Test 1: Data size 336: : 40%|████ | 4/10 [02:07<03:19, 33.26s/it, data_size=304, test_acc=0.777, train_acc=0.778]Test 1: Data size 336: : 40%|████ | 4/10 [02:47<03:19, 33.26s/it, data_size=336, test_acc=0.737, train_acc=0.753]Test 1: Data size 336: : 50%|█████ | 5/10 [02:47<02:57, 35.59s/it, data_size=336, test_acc=0.737, train_acc=0.753]Test 1: Data size 368: : 50%|█████ | 5/10 [02:47<02:57, 35.59s/it, data_size=336, test_acc=0.737, train_acc=0.753]Test 1: Data size 368: : 50%|█████ | 5/10 [03:30<02:57, 35.59s/it, data_size=368, test_acc=0.833, train_acc=0.845]Test 1: Data size 368: : 60%|██████ | 6/10 [03:30<02:32, 38.09s/it, data_size=368, test_acc=0.833, train_acc=0.845]Test 1: Data size 400: : 60%|██████ | 6/10 [03:30<02:32, 38.09s/it, data_size=368, test_acc=0.833, train_acc=0.845]Test 1: Data size 400: : 60%|██████ | 6/10 [04:16<02:32, 38.09s/it, data_size=400, test_acc=0.871, train_acc=0.869]Test 1: Data size 400: : 70%|███████ | 7/10 [04:16<02:02, 40.82s/it, data_size=400, test_acc=0.871, train_acc=0.869]Test 1: Data size 432: : 70%|███████ | 7/10 [04:16<02:02, 40.82s/it, data_size=400, test_acc=0.871, train_acc=0.869]Test 1: Data size 432: : 70%|███████ | 7/10 [05:06<02:02, 40.82s/it, data_size=432, test_acc=0.833, train_acc=0.801]Test 1: Data size 432: : 80%|████████ | 8/10 [05:06<01:27, 43.81s/it, data_size=432, test_acc=0.833, train_acc=0.801]Test 1: Data size 464: : 80%|████████ | 8/10 [05:06<01:27, 43.81s/it, data_size=432, test_acc=0.833, train_acc=0.801]Test 1: Data size 464: : 80%|████████ | 8/10 [05:59<01:27, 43.81s/it, data_size=464, test_acc=0.876, train_acc=0.889]Test 1: Data size 464: : 90%|█████████ | 9/10 [05:59<00:46, 46.68s/it, data_size=464, test_acc=0.876, train_acc=0.889]Test 1: Data size 496: : 90%|█████████ | 9/10 [05:59<00:46, 46.68s/it, data_size=464, test_acc=0.876, train_acc=0.889]Test 1: Data size 496: : 90%|█████████ | 9/10 [06:56<00:46, 46.68s/it, data_size=496, test_acc=0.861, train_acc=0.872]Test 1: Data size 496: : 100%|██████████| 10/10 [06:56<00:00, 49.74s/it, data_size=496, test_acc=0.861, train_acc=0.872]Test 1: Data size 496: : 100%|██████████| 10/10 [06:56<00:00, 41.65s/it, data_size=496, test_acc=0.861, train_acc=0.872]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.705, train_acc=0.724]Test 2: Data size 208: : 10%|█ | 1/10 [00:26<03:57, 26.40s/it, data_size=208, test_acc=0.705, train_acc=0.724]Test 2: Data size 240: : 10%|█ | 1/10 [00:26<03:57, 26.40s/it, data_size=208, test_acc=0.705, train_acc=0.724]Test 2: Data size 240: : 10%|█ | 1/10 [00:56<03:57, 26.40s/it, data_size=240, test_acc=0.689, train_acc=0.786]Test 2: Data size 240: : 20%|██ | 2/10 [00:56<03:47, 28.42s/it, data_size=240, test_acc=0.689, train_acc=0.786]Test 2: Data size 272: : 20%|██ | 2/10 [00:56<03:47, 28.42s/it, data_size=240, test_acc=0.689, train_acc=0.786]Test 2: Data size 272: : 20%|██ | 2/10 [01:28<03:47, 28.42s/it, data_size=272, test_acc=0.701, train_acc=0.787]Test 2: Data size 272: : 30%|███ | 3/10 [01:28<03:31, 30.21s/it, data_size=272, test_acc=0.701, train_acc=0.787]Test 2: Data size 304: : 30%|███ | 3/10 [01:28<03:31, 30.21s/it, data_size=272, test_acc=0.701, train_acc=0.787]Test 2: Data size 304: : 30%|███ | 3/10 [02:03<03:31, 30.21s/it, data_size=304, test_acc=0.755, train_acc=0.832]Test 2: Data size 304: : 40%|████ | 4/10 [02:04<03:13, 32.30s/it, data_size=304, test_acc=0.755, train_acc=0.832]Test 2: Data size 336: : 40%|████ | 4/10 [02:04<03:13, 32.30s/it, data_size=304, test_acc=0.755, train_acc=0.832]Test 2: Data size 336: : 40%|████ | 4/10 [02:42<03:13, 32.30s/it, data_size=336, test_acc=0.832, train_acc=0.854]Test 2: Data size 336: : 50%|█████ | 5/10 [02:42<02:52, 34.59s/it, data_size=336, test_acc=0.832, train_acc=0.854]Test 2: Data size 368: : 50%|█████ | 5/10 [02:42<02:52, 34.59s/it, data_size=336, test_acc=0.832, train_acc=0.854]Test 2: Data size 368: : 50%|█████ | 5/10 [03:24<02:52, 34.59s/it, data_size=368, test_acc=0.871, train_acc=0.908]Test 2: Data size 368: : 60%|██████ | 6/10 [03:24<02:28, 37.09s/it, data_size=368, test_acc=0.871, train_acc=0.908]Test 2: Data size 400: : 60%|██████ | 6/10 [03:24<02:28, 37.09s/it, data_size=368, test_acc=0.871, train_acc=0.908]Test 2: Data size 400: : 60%|██████ | 6/10 [04:09<02:28, 37.09s/it, data_size=400, test_acc=0.88, train_acc=0.843] Test 2: Data size 400: : 70%|███████ | 7/10 [04:09<01:58, 39.63s/it, data_size=400, test_acc=0.88, train_acc=0.843]Test 2: Data size 432: : 70%|███████ | 7/10 [04:09<01:58, 39.63s/it, data_size=400, test_acc=0.88, train_acc=0.843]Test 2: Data size 432: : 70%|███████ | 7/10 [04:57<01:58, 39.63s/it, data_size=432, test_acc=0.803, train_acc=0.834]Test 2: Data size 432: : 80%|████████ | 8/10 [04:58<01:24, 42.46s/it, data_size=432, test_acc=0.803, train_acc=0.834]Test 2: Data size 464: : 80%|████████ | 8/10 [04:58<01:24, 42.46s/it, data_size=432, test_acc=0.803, train_acc=0.834]Test 2: Data size 464: : 80%|████████ | 8/10 [05:49<01:24, 42.46s/it, data_size=464, test_acc=0.888, train_acc=0.903]Test 2: Data size 464: : 90%|█████████ | 9/10 [05:50<00:45, 45.44s/it, data_size=464, test_acc=0.888, train_acc=0.903]Test 2: Data size 496: : 90%|█████████ | 9/10 [05:50<00:45, 45.44s/it, data_size=464, test_acc=0.888, train_acc=0.903]Test 2: Data size 496: : 90%|█████████ | 9/10 [06:44<00:45, 45.44s/it, data_size=496, test_acc=0.859, train_acc=0.887]Test 2: Data size 496: : 100%|██████████| 10/10 [06:45<00:00, 48.39s/it, data_size=496, test_acc=0.859, train_acc=0.887]Test 2: Data size 496: : 100%|██████████| 10/10 [06:45<00:00, 40.50s/it, data_size=496, test_acc=0.859, train_acc=0.887]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.712, train_acc=0.725]Test 3: Data size 208: : 10%|█ | 1/10 [00:26<04:01, 26.85s/it, data_size=208, test_acc=0.712, train_acc=0.725]Test 3: Data size 240: : 10%|█ | 1/10 [00:26<04:01, 26.85s/it, data_size=208, test_acc=0.712, train_acc=0.725]Test 3: Data size 240: : 10%|█ | 1/10 [00:56<04:01, 26.85s/it, data_size=240, test_acc=0.767, train_acc=0.804]Test 3: Data size 240: : 20%|██ | 2/10 [00:56<03:48, 28.57s/it, data_size=240, test_acc=0.767, train_acc=0.804]Test 3: Data size 272: : 20%|██ | 2/10 [00:56<03:48, 28.57s/it, data_size=240, test_acc=0.767, train_acc=0.804]Test 3: Data size 272: : 20%|██ | 2/10 [01:29<03:48, 28.57s/it, data_size=272, test_acc=0.74, train_acc=0.767] Test 3: Data size 272: : 30%|███ | 3/10 [01:29<03:33, 30.56s/it, data_size=272, test_acc=0.74, train_acc=0.767]Test 3: Data size 304: : 30%|███ | 3/10 [01:29<03:33, 30.56s/it, data_size=272, test_acc=0.74, train_acc=0.767]Test 3: Data size 304: : 30%|███ | 3/10 [02:05<03:33, 30.56s/it, data_size=304, test_acc=0.731, train_acc=0.743]Test 3: Data size 304: : 40%|████ | 4/10 [02:05<03:16, 32.72s/it, data_size=304, test_acc=0.731, train_acc=0.743]Test 3: Data size 336: : 40%|████ | 4/10 [02:05<03:16, 32.72s/it, data_size=304, test_acc=0.731, train_acc=0.743]Test 3: Data size 336: : 40%|████ | 4/10 [02:44<03:16, 32.72s/it, data_size=336, test_acc=0.776, train_acc=0.858]Test 3: Data size 336: : 50%|█████ | 5/10 [02:44<02:55, 35.10s/it, data_size=336, test_acc=0.776, train_acc=0.858]Test 3: Data size 368: : 50%|█████ | 5/10 [02:44<02:55, 35.10s/it, data_size=336, test_acc=0.776, train_acc=0.858]Test 3: Data size 368: : 50%|█████ | 5/10 [03:27<02:55, 35.10s/it, data_size=368, test_acc=0.881, train_acc=0.899]Test 3: Data size 368: : 60%|██████ | 6/10 [03:27<02:30, 37.67s/it, data_size=368, test_acc=0.881, train_acc=0.899]Test 3: Data size 400: : 60%|██████ | 6/10 [03:27<02:30, 37.67s/it, data_size=368, test_acc=0.881, train_acc=0.899]Test 3: Data size 400: : 60%|██████ | 6/10 [04:13<02:30, 37.67s/it, data_size=400, test_acc=0.893, train_acc=0.917]Test 3: Data size 400: : 70%|███████ | 7/10 [04:13<02:01, 40.40s/it, data_size=400, test_acc=0.893, train_acc=0.917]Test 3: Data size 432: : 70%|███████ | 7/10 [04:13<02:01, 40.40s/it, data_size=400, test_acc=0.893, train_acc=0.917]Test 3: Data size 432: : 70%|███████ | 7/10 [05:03<02:01, 40.40s/it, data_size=432, test_acc=0.877, train_acc=0.883]Test 3: Data size 432: : 80%|████████ | 8/10 [05:03<01:26, 43.38s/it, data_size=432, test_acc=0.877, train_acc=0.883]Test 3: Data size 464: : 80%|████████ | 8/10 [05:03<01:26, 43.38s/it, data_size=432, test_acc=0.877, train_acc=0.883]Test 3: Data size 464: : 80%|████████ | 8/10 [05:55<01:26, 43.38s/it, data_size=464, test_acc=0.898, train_acc=0.9] Test 3: Data size 464: : 90%|█████████ | 9/10 [05:56<00:46, 46.28s/it, data_size=464, test_acc=0.898, train_acc=0.9]Test 3: Data size 496: : 90%|█████████ | 9/10 [05:56<00:46, 46.28s/it, data_size=464, test_acc=0.898, train_acc=0.9]Test 3: Data size 496: : 90%|█████████ | 9/10 [06:52<00:46, 46.28s/it, data_size=496, test_acc=0.898, train_acc=0.904]Test 3: Data size 496: : 100%|██████████| 10/10 [06:52<00:00, 49.37s/it, data_size=496, test_acc=0.898, train_acc=0.904]Test 3: Data size 496: : 100%|██████████| 10/10 [06:52<00:00, 41.23s/it, data_size=496, test_acc=0.898, train_acc=0.904]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.65, train_acc=0.633]Test 4: Data size 208: : 10%|█ | 1/10 [00:26<04:01, 26.83s/it, data_size=208, test_acc=0.65, train_acc=0.633]Test 4: Data size 240: : 10%|█ | 1/10 [00:26<04:01, 26.83s/it, data_size=208, test_acc=0.65, train_acc=0.633]Test 4: Data size 240: : 10%|█ | 1/10 [00:56<04:01, 26.83s/it, data_size=240, test_acc=0.743, train_acc=0.747]Test 4: Data size 240: : 20%|██ | 2/10 [00:56<03:47, 28.47s/it, data_size=240, test_acc=0.743, train_acc=0.747]Test 4: Data size 272: : 20%|██ | 2/10 [00:56<03:47, 28.47s/it, data_size=240, test_acc=0.743, train_acc=0.747]Test 4: Data size 272: : 20%|██ | 2/10 [01:29<03:47, 28.47s/it, data_size=272, test_acc=0.692, train_acc=0.707]Test 4: Data size 272: : 30%|███ | 3/10 [01:29<03:33, 30.55s/it, data_size=272, test_acc=0.692, train_acc=0.707]Test 4: Data size 304: : 30%|███ | 3/10 [01:29<03:33, 30.55s/it, data_size=272, test_acc=0.692, train_acc=0.707]Test 4: Data size 304: : 30%|███ | 3/10 [02:05<03:33, 30.55s/it, data_size=304, test_acc=0.807, train_acc=0.825]Test 4: Data size 304: : 40%|████ | 4/10 [02:05<03:17, 32.88s/it, data_size=304, test_acc=0.807, train_acc=0.825]Test 4: Data size 336: : 40%|████ | 4/10 [02:05<03:17, 32.88s/it, data_size=304, test_acc=0.807, train_acc=0.825]Test 4: Data size 336: : 40%|████ | 4/10 [02:45<03:17, 32.88s/it, data_size=336, test_acc=0.744, train_acc=0.817]Test 4: Data size 336: : 50%|█████ | 5/10 [02:45<02:56, 35.27s/it, data_size=336, test_acc=0.744, train_acc=0.817]Test 4: Data size 368: : 50%|█████ | 5/10 [02:45<02:56, 35.27s/it, data_size=336, test_acc=0.744, train_acc=0.817]Test 4: Data size 368: : 50%|█████ | 5/10 [03:27<02:56, 35.27s/it, data_size=368, test_acc=0.855, train_acc=0.875]Test 4: Data size 368: : 60%|██████ | 6/10 [03:28<02:31, 37.76s/it, data_size=368, test_acc=0.855, train_acc=0.875]Test 4: Data size 400: : 60%|██████ | 6/10 [03:28<02:31, 37.76s/it, data_size=368, test_acc=0.855, train_acc=0.875]Test 4: Data size 400: : 60%|██████ | 6/10 [04:13<02:31, 37.76s/it, data_size=400, test_acc=0.825, train_acc=0.773]Test 4: Data size 400: : 70%|███████ | 7/10 [04:14<02:01, 40.47s/it, data_size=400, test_acc=0.825, train_acc=0.773]Test 4: Data size 432: : 70%|███████ | 7/10 [04:14<02:01, 40.47s/it, data_size=400, test_acc=0.825, train_acc=0.773]Test 4: Data size 432: : 70%|███████ | 7/10 [05:03<02:01, 40.47s/it, data_size=432, test_acc=0.828, train_acc=0.891]Test 4: Data size 432: : 80%|████████ | 8/10 [05:03<01:26, 43.34s/it, data_size=432, test_acc=0.828, train_acc=0.891]Test 4: Data size 464: : 80%|████████ | 8/10 [05:03<01:26, 43.34s/it, data_size=432, test_acc=0.828, train_acc=0.891]Test 4: Data size 464: : 80%|████████ | 8/10 [05:56<01:26, 43.34s/it, data_size=464, test_acc=0.819, train_acc=0.892]Test 4: Data size 464: : 90%|█████████ | 9/10 [05:56<00:46, 46.41s/it, data_size=464, test_acc=0.819, train_acc=0.892]Test 4: Data size 496: : 90%|█████████ | 9/10 [05:56<00:46, 46.41s/it, data_size=464, test_acc=0.819, train_acc=0.892]Test 4: Data size 496: : 90%|█████████ | 9/10 [06:52<00:46, 46.41s/it, data_size=496, test_acc=0.864, train_acc=0.892]Test 4: Data size 496: : 100%|██████████| 10/10 [06:52<00:00, 49.34s/it, data_size=496, test_acc=0.864, train_acc=0.892]Test 4: Data size 496: : 100%|██████████| 10/10 [06:52<00:00, 41.26s/it, data_size=496, test_acc=0.864, train_acc=0.892]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:27<?, ?it/s, data_size=208, test_acc=0.714, train_acc=0.725]Test 5: Data size 208: : 10%|█ | 1/10 [00:27<04:04, 27.18s/it, data_size=208, test_acc=0.714, train_acc=0.725]Test 5: Data size 240: : 10%|█ | 1/10 [00:27<04:04, 27.18s/it, data_size=208, test_acc=0.714, train_acc=0.725]Test 5: Data size 240: : 10%|█ | 1/10 [00:57<04:04, 27.18s/it, data_size=240, test_acc=0.737, train_acc=0.812]Test 5: Data size 240: : 20%|██ | 2/10 [00:57<03:50, 28.85s/it, data_size=240, test_acc=0.737, train_acc=0.812]Test 5: Data size 272: : 20%|██ | 2/10 [00:57<03:50, 28.85s/it, data_size=240, test_acc=0.737, train_acc=0.812]Test 5: Data size 272: : 20%|██ | 2/10 [01:30<03:50, 28.85s/it, data_size=272, test_acc=0.74, train_acc=0.811] Test 5: Data size 272: : 30%|███ | 3/10 [01:30<03:35, 30.82s/it, data_size=272, test_acc=0.74, train_acc=0.811]Test 5: Data size 304: : 30%|███ | 3/10 [01:30<03:35, 30.82s/it, data_size=272, test_acc=0.74, train_acc=0.811]Test 5: Data size 304: : 30%|███ | 3/10 [02:06<03:35, 30.82s/it, data_size=304, test_acc=0.745, train_acc=0.817]Test 5: Data size 304: : 40%|████ | 4/10 [02:06<03:18, 33.04s/it, data_size=304, test_acc=0.745, train_acc=0.817]Test 5: Data size 336: : 40%|████ | 4/10 [02:06<03:18, 33.04s/it, data_size=304, test_acc=0.745, train_acc=0.817]Test 5: Data size 336: : 40%|████ | 4/10 [02:46<03:18, 33.04s/it, data_size=336, test_acc=0.782, train_acc=0.862]Test 5: Data size 336: : 50%|█████ | 5/10 [02:46<02:57, 35.52s/it, data_size=336, test_acc=0.782, train_acc=0.862]Test 5: Data size 368: : 50%|█████ | 5/10 [02:46<02:57, 35.52s/it, data_size=336, test_acc=0.782, train_acc=0.862]Test 5: Data size 368: : 50%|█████ | 5/10 [03:29<02:57, 35.52s/it, data_size=368, test_acc=0.736, train_acc=0.763]Test 5: Data size 368: : 60%|██████ | 6/10 [03:29<02:32, 38.09s/it, data_size=368, test_acc=0.736, train_acc=0.763]Test 5: Data size 400: : 60%|██████ | 6/10 [03:29<02:32, 38.09s/it, data_size=368, test_acc=0.736, train_acc=0.763]Test 5: Data size 400: : 60%|██████ | 6/10 [04:16<02:32, 38.09s/it, data_size=400, test_acc=0.782, train_acc=0.881]Test 5: Data size 400: : 70%|███████ | 7/10 [04:16<02:03, 41.02s/it, data_size=400, test_acc=0.782, train_acc=0.881]Test 5: Data size 432: : 70%|███████ | 7/10 [04:16<02:03, 41.02s/it, data_size=400, test_acc=0.782, train_acc=0.881]Test 5: Data size 432: : 70%|███████ | 7/10 [05:06<02:03, 41.02s/it, data_size=432, test_acc=0.764, train_acc=0.835]Test 5: Data size 432: : 80%|████████ | 8/10 [05:07<01:27, 43.94s/it, data_size=432, test_acc=0.764, train_acc=0.835]Test 5: Data size 464: : 80%|████████ | 8/10 [05:07<01:27, 43.94s/it, data_size=432, test_acc=0.764, train_acc=0.835]Test 5: Data size 464: : 80%|████████ | 8/10 [06:00<01:27, 43.94s/it, data_size=464, test_acc=0.851, train_acc=0.893]Test 5: Data size 464: : 90%|█████████ | 9/10 [06:00<00:47, 47.04s/it, data_size=464, test_acc=0.851, train_acc=0.893]Test 5: Data size 496: : 90%|█████████ | 9/10 [06:00<00:47, 47.04s/it, data_size=464, test_acc=0.851, train_acc=0.893]Test 5: Data size 496: : 90%|█████████ | 9/10 [06:58<00:47, 47.04s/it, data_size=496, test_acc=0.884, train_acc=0.935]Test 5: Data size 496: : 100%|██████████| 10/10 [06:58<00:00, 50.30s/it, data_size=496, test_acc=0.884, train_acc=0.935]Test 5: Data size 496: : 100%|██████████| 10/10 [06:58<00:00, 41.85s/it, data_size=496, test_acc=0.884, train_acc=0.935]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:26<?, ?it/s, data_size=208, test_acc=0.647, train_acc=0.669]Test 6: Data size 208: : 10%|█ | 1/10 [00:26<03:59, 26.61s/it, data_size=208, test_acc=0.647, train_acc=0.669]Test 6: Data size 240: : 10%|█ | 1/10 [00:26<03:59, 26.61s/it, data_size=208, test_acc=0.647, train_acc=0.669]Test 6: Data size 240: : 10%|█ | 1/10 [00:56<03:59, 26.61s/it, data_size=240, test_acc=0.744, train_acc=0.751]Test 6: Data size 240: : 20%|██ | 2/10 [00:56<03:48, 28.55s/it, data_size=240, test_acc=0.744, train_acc=0.751]Test 6: Data size 272: : 20%|██ | 2/10 [00:56<03:48, 28.55s/it, data_size=240, test_acc=0.744, train_acc=0.751]Test 6: Data size 272: : 20%|██ | 2/10 [01:29<03:48, 28.55s/it, data_size=272, test_acc=0.655, train_acc=0.71] Test 6: Data size 272: : 30%|███ | 3/10 [01:29<03:34, 30.60s/it, data_size=272, test_acc=0.655, train_acc=0.71]Test 6: Data size 304: : 30%|███ | 3/10 [01:29<03:34, 30.60s/it, data_size=272, test_acc=0.655, train_acc=0.71]Test 6: Data size 304: : 30%|███ | 3/10 [02:05<03:34, 30.60s/it, data_size=304, test_acc=0.733, train_acc=0.783]Test 6: Data size 304: : 40%|████ | 4/10 [02:05<03:15, 32.66s/it, data_size=304, test_acc=0.733, train_acc=0.783]Test 6: Data size 336: : 40%|████ | 4/10 [02:05<03:15, 32.66s/it, data_size=304, test_acc=0.733, train_acc=0.783]Test 6: Data size 336: : 40%|████ | 4/10 [02:44<03:15, 32.66s/it, data_size=336, test_acc=0.784, train_acc=0.82] Test 6: Data size 336: : 50%|█████ | 5/10 [02:45<02:56, 35.21s/it, data_size=336, test_acc=0.784, train_acc=0.82]Test 6: Data size 368: : 50%|█████ | 5/10 [02:45<02:56, 35.21s/it, data_size=336, test_acc=0.784, train_acc=0.82]Test 6: Data size 368: : 50%|█████ | 5/10 [03:27<02:56, 35.21s/it, data_size=368, test_acc=0.778, train_acc=0.855]Test 6: Data size 368: : 60%|██████ | 6/10 [03:27<02:30, 37.69s/it, data_size=368, test_acc=0.778, train_acc=0.855]Test 6: Data size 400: : 60%|██████ | 6/10 [03:27<02:30, 37.69s/it, data_size=368, test_acc=0.778, train_acc=0.855]Test 6: Data size 400: : 60%|██████ | 6/10 [04:13<02:30, 37.69s/it, data_size=400, test_acc=0.87, train_acc=0.875] Test 6: Data size 400: : 70%|███████ | 7/10 [04:13<02:01, 40.41s/it, data_size=400, test_acc=0.87, train_acc=0.875]Test 6: Data size 432: : 70%|███████ | 7/10 [04:13<02:01, 40.41s/it, data_size=400, test_acc=0.87, train_acc=0.875]Test 6: Data size 432: : 70%|███████ | 7/10 [05:02<02:01, 40.41s/it, data_size=432, test_acc=0.865, train_acc=0.862]Test 6: Data size 432: : 80%|████████ | 8/10 [05:02<01:26, 43.25s/it, data_size=432, test_acc=0.865, train_acc=0.862]Test 6: Data size 464: : 80%|████████ | 8/10 [05:02<01:26, 43.25s/it, data_size=432, test_acc=0.865, train_acc=0.862]Test 6: Data size 464: : 80%|████████ | 8/10 [05:55<01:26, 43.25s/it, data_size=464, test_acc=0.819, train_acc=0.84] Test 6: Data size 464: : 90%|█████████ | 9/10 [05:56<00:46, 46.33s/it, data_size=464, test_acc=0.819, train_acc=0.84]Test 6: Data size 496: : 90%|█████████ | 9/10 [05:56<00:46, 46.33s/it, data_size=464, test_acc=0.819, train_acc=0.84]Test 6: Data size 496: : 90%|█████████ | 9/10 [06:52<00:46, 46.33s/it, data_size=496, test_acc=0.864, train_acc=0.872]Test 6: Data size 496: : 100%|██████████| 10/10 [06:52<00:00, 49.45s/it, data_size=496, test_acc=0.864, train_acc=0.872]Test 6: Data size 496: : 100%|██████████| 10/10 [06:52<00:00, 41.25s/it, data_size=496, test_acc=0.864, train_acc=0.872]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:27<?, ?it/s, data_size=208, test_acc=0.712, train_acc=0.706]Test 7: Data size 208: : 10%|█ | 1/10 [00:27<04:04, 27.15s/it, data_size=208, test_acc=0.712, train_acc=0.706]Test 7: Data size 240: : 10%|█ | 1/10 [00:27<04:04, 27.15s/it, data_size=208, test_acc=0.712, train_acc=0.706]Test 7: Data size 240: : 10%|█ | 1/10 [00:57<04:04, 27.15s/it, data_size=240, test_acc=0.628, train_acc=0.7] Test 7: Data size 240: : 20%|██ | 2/10 [00:57<03:52, 29.11s/it, data_size=240, test_acc=0.628, train_acc=0.7]Test 7: Data size 272: : 20%|██ | 2/10 [00:57<03:52, 29.11s/it, data_size=240, test_acc=0.628, train_acc=0.7]Test 7: Data size 272: : 20%|██ | 2/10 [01:31<03:52, 29.11s/it, data_size=272, test_acc=0.724, train_acc=0.799]Test 7: Data size 272: : 30%|███ | 3/10 [01:31<03:38, 31.16s/it, data_size=272, test_acc=0.724, train_acc=0.799]Test 7: Data size 304: : 30%|███ | 3/10 [01:31<03:38, 31.16s/it, data_size=272, test_acc=0.724, train_acc=0.799]Test 7: Data size 304: : 30%|███ | 3/10 [02:07<03:38, 31.16s/it, data_size=304, test_acc=0.741, train_acc=0.819]Test 7: Data size 304: : 40%|████ | 4/10 [02:07<03:19, 33.33s/it, data_size=304, test_acc=0.741, train_acc=0.819]Test 7: Data size 336: : 40%|████ | 4/10 [02:07<03:19, 33.33s/it, data_size=304, test_acc=0.741, train_acc=0.819]Test 7: Data size 336: : 40%|████ | 4/10 [02:47<03:19, 33.33s/it, data_size=336, test_acc=0.707, train_acc=0.832]Test 7: Data size 336: : 50%|█████ | 5/10 [02:47<02:58, 35.66s/it, data_size=336, test_acc=0.707, train_acc=0.832]Test 7: Data size 368: : 50%|█████ | 5/10 [02:47<02:58, 35.66s/it, data_size=336, test_acc=0.707, train_acc=0.832]Test 7: Data size 368: : 50%|█████ | 5/10 [03:30<02:58, 35.66s/it, data_size=368, test_acc=0.73, train_acc=0.833] Test 7: Data size 368: : 60%|██████ | 6/10 [03:30<02:32, 38.18s/it, data_size=368, test_acc=0.73, train_acc=0.833]Test 7: Data size 400: : 60%|██████ | 6/10 [03:30<02:32, 38.18s/it, data_size=368, test_acc=0.73, train_acc=0.833]Test 7: Data size 400: : 60%|██████ | 6/10 [04:16<02:32, 38.18s/it, data_size=400, test_acc=0.828, train_acc=0.835]Test 7: Data size 400: : 70%|███████ | 7/10 [04:16<02:02, 40.81s/it, data_size=400, test_acc=0.828, train_acc=0.835]Test 7: Data size 432: : 70%|███████ | 7/10 [04:16<02:02, 40.81s/it, data_size=400, test_acc=0.828, train_acc=0.835]Test 7: Data size 432: : 70%|███████ | 7/10 [05:06<02:02, 40.81s/it, data_size=432, test_acc=0.832, train_acc=0.81] Test 7: Data size 432: : 80%|████████ | 8/10 [05:06<01:27, 43.62s/it, data_size=432, test_acc=0.832, train_acc=0.81]Test 7: Data size 464: : 80%|████████ | 8/10 [05:06<01:27, 43.62s/it, data_size=432, test_acc=0.832, train_acc=0.81]Test 7: Data size 464: : 80%|████████ | 8/10 [05:59<01:27, 43.62s/it, data_size=464, test_acc=0.866, train_acc=0.832]Test 7: Data size 464: : 90%|█████████ | 9/10 [05:59<00:46, 46.49s/it, data_size=464, test_acc=0.866, train_acc=0.832]Test 7: Data size 496: : 90%|█████████ | 9/10 [05:59<00:46, 46.49s/it, data_size=464, test_acc=0.866, train_acc=0.832]Test 7: Data size 496: : 90%|█████████ | 9/10 [06:55<00:46, 46.49s/it, data_size=496, test_acc=0.891, train_acc=0.894]Test 7: Data size 496: : 100%|██████████| 10/10 [06:55<00:00, 49.53s/it, data_size=496, test_acc=0.891, train_acc=0.894]Test 7: Data size 496: : 100%|██████████| 10/10 [06:55<00:00, 41.57s/it, data_size=496, test_acc=0.891, train_acc=0.894]
working on model Multimodal-middle-fusion-model-based-on-AlexNet with CLUSTER_MARGIN
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [01:21<?, ?it/s, data_size=208, test_acc=0.709, train_acc=0.721]Test 0: Data size 208: : 10%|█ | 1/10 [01:21<12:17, 81.97s/it, data_size=208, test_acc=0.709, train_acc=0.721]Test 0: Data size 240: : 10%|█ | 1/10 [01:21<12:17, 81.97s/it, data_size=208, test_acc=0.709, train_acc=0.721]Test 0: Data size 240: : 10%|█ | 1/10 [01:51<12:17, 81.97s/it, data_size=240, test_acc=0.703, train_acc=0.759]Test 0: Data size 240: : 20%|██ | 2/10 [01:51<06:48, 51.06s/it, data_size=240, test_acc=0.703, train_acc=0.759]Test 0: Data size 272: : 20%|██ | 2/10 [01:51<06:48, 51.06s/it, data_size=240, test_acc=0.703, train_acc=0.759]Test 0: Data size 272: : 20%|██ | 2/10 [02:23<06:48, 51.06s/it, data_size=272, test_acc=0.724, train_acc=0.772]Test 0: Data size 272: : 30%|███ | 3/10 [02:23<04:57, 42.44s/it, data_size=272, test_acc=0.724, train_acc=0.772]Test 0: Data size 304: : 30%|███ | 3/10 [02:23<04:57, 42.44s/it, data_size=272, test_acc=0.724, train_acc=0.772]Test 0: Data size 304: : 30%|███ | 3/10 [02:59<04:57, 42.44s/it, data_size=304, test_acc=0.765, train_acc=0.793]Test 0: Data size 304: : 40%|████ | 4/10 [02:59<03:58, 39.79s/it, data_size=304, test_acc=0.765, train_acc=0.793]Test 0: Data size 336: : 40%|████ | 4/10 [02:59<03:58, 39.79s/it, data_size=304, test_acc=0.765, train_acc=0.793]Test 0: Data size 336: : 40%|████ | 4/10 [03:37<03:58, 39.79s/it, data_size=336, test_acc=0.719, train_acc=0.764]Test 0: Data size 336: : 50%|█████ | 5/10 [03:37<03:16, 39.39s/it, data_size=336, test_acc=0.719, train_acc=0.764]Test 0: Data size 368: : 50%|█████ | 5/10 [03:37<03:16, 39.39s/it, data_size=336, test_acc=0.719, train_acc=0.764]Test 0: Data size 368: : 50%|█████ | 5/10 [04:19<03:16, 39.39s/it, data_size=368, test_acc=0.785, train_acc=0.813]Test 0: Data size 368: : 60%|██████ | 6/10 [04:19<02:40, 40.14s/it, data_size=368, test_acc=0.785, train_acc=0.813]Test 0: Data size 400: : 60%|██████ | 6/10 [04:19<02:40, 40.14s/it, data_size=368, test_acc=0.785, train_acc=0.813]Test 0: Data size 400: : 60%|██████ | 6/10 [05:04<02:40, 40.14s/it, data_size=400, test_acc=0.833, train_acc=0.869]Test 0: Data size 400: : 70%|███████ | 7/10 [05:04<02:05, 41.79s/it, data_size=400, test_acc=0.833, train_acc=0.869]Test 0: Data size 432: : 70%|███████ | 7/10 [05:04<02:05, 41.79s/it, data_size=400, test_acc=0.833, train_acc=0.869]Test 0: Data size 432: : 70%|███████ | 7/10 [05:53<02:05, 41.79s/it, data_size=432, test_acc=0.832, train_acc=0.776]Test 0: Data size 432: : 80%|████████ | 8/10 [05:53<01:27, 43.97s/it, data_size=432, test_acc=0.832, train_acc=0.776]Test 0: Data size 464: : 80%|████████ | 8/10 [05:53<01:27, 43.97s/it, data_size=432, test_acc=0.832, train_acc=0.776]Test 0: Data size 464: : 80%|████████ | 8/10 [06:45<01:27, 43.97s/it, data_size=464, test_acc=0.844, train_acc=0.88] Test 0: Data size 464: : 90%|█████████ | 9/10 [06:45<00:46, 46.50s/it, data_size=464, test_acc=0.844, train_acc=0.88]Test 0: Data size 496: : 90%|█████████ | 9/10 [06:45<00:46, 46.50s/it, data_size=464, test_acc=0.844, train_acc=0.88]Test 0: Data size 496: : 90%|█████████ | 9/10 [07:41<00:46, 46.50s/it, data_size=496, test_acc=0.834, train_acc=0.842]Test 0: Data size 496: : 100%|██████████| 10/10 [07:41<00:00, 49.42s/it, data_size=496, test_acc=0.834, train_acc=0.842]Test 0: Data size 496: : 100%|██████████| 10/10 [07:41<00:00, 46.14s/it, data_size=496, test_acc=0.834, train_acc=0.842]
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0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [01:21<?, ?it/s, data_size=208, test_acc=0.64, train_acc=0.674]Test 2: Data size 208: : 10%|█ | 1/10 [01:21<12:15, 81.73s/it, data_size=208, test_acc=0.64, train_acc=0.674]Test 2: Data size 240: : 10%|█ | 1/10 [01:21<12:15, 81.73s/it, data_size=208, test_acc=0.64, train_acc=0.674]Test 2: Data size 240: : 10%|█ | 1/10 [01:50<12:15, 81.73s/it, data_size=240, test_acc=0.681, train_acc=0.714]Test 2: Data size 240: : 20%|██ | 2/10 [01:51<06:47, 50.94s/it, data_size=240, test_acc=0.681, train_acc=0.714]Test 2: Data size 272: : 20%|██ | 2/10 [01:51<06:47, 50.94s/it, data_size=240, test_acc=0.681, train_acc=0.714]Test 2: Data size 272: : 20%|██ | 2/10 [02:23<06:47, 50.94s/it, data_size=272, test_acc=0.675, train_acc=0.663]Test 2: Data size 272: : 30%|███ | 3/10 [02:23<04:57, 42.45s/it, data_size=272, test_acc=0.675, train_acc=0.663]Test 2: Data size 304: : 30%|███ | 3/10 [02:23<04:57, 42.45s/it, data_size=272, test_acc=0.675, train_acc=0.663]Test 2: Data size 304: : 30%|███ | 3/10 [02:59<04:57, 42.45s/it, data_size=304, test_acc=0.74, train_acc=0.726] Test 2: Data size 304: : 40%|████ | 4/10 [02:59<03:59, 39.86s/it, data_size=304, test_acc=0.74, train_acc=0.726]Test 2: Data size 336: : 40%|████ | 4/10 [02:59<03:59, 39.86s/it, data_size=304, test_acc=0.74, train_acc=0.726]Test 2: Data size 336: : 40%|████ | 4/10 [03:38<03:59, 39.86s/it, data_size=336, test_acc=0.742, train_acc=0.796]Test 2: Data size 336: : 50%|█████ | 5/10 [03:38<03:18, 39.61s/it, data_size=336, test_acc=0.742, train_acc=0.796]Test 2: Data size 368: : 50%|█████ | 5/10 [03:38<03:18, 39.61s/it, data_size=336, test_acc=0.742, train_acc=0.796]Test 2: Data size 368: : 50%|█████ | 5/10 [04:21<03:18, 39.61s/it, data_size=368, test_acc=0.838, train_acc=0.833]Test 2: Data size 368: : 60%|██████ | 6/10 [04:21<02:42, 40.63s/it, data_size=368, test_acc=0.838, train_acc=0.833]Test 2: Data size 400: : 60%|██████ | 6/10 [04:21<02:42, 40.63s/it, data_size=368, test_acc=0.838, train_acc=0.833]Test 2: Data size 400: : 60%|██████ | 6/10 [05:06<02:42, 40.63s/it, data_size=400, test_acc=0.862, train_acc=0.875]Test 2: Data size 400: : 70%|███████ | 7/10 [05:06<02:06, 42.29s/it, data_size=400, test_acc=0.862, train_acc=0.875]Test 2: Data size 432: : 70%|███████ | 7/10 [05:06<02:06, 42.29s/it, data_size=400, test_acc=0.862, train_acc=0.875]Test 2: Data size 432: : 70%|███████ | 7/10 [05:55<02:06, 42.29s/it, data_size=432, test_acc=0.903, train_acc=0.903]Test 2: Data size 432: : 80%|████████ | 8/10 [05:55<01:28, 44.42s/it, data_size=432, test_acc=0.903, train_acc=0.903]Test 2: Data size 464: : 80%|████████ | 8/10 [05:55<01:28, 44.42s/it, data_size=432, test_acc=0.903, train_acc=0.903]Test 2: Data size 464: : 80%|████████ | 8/10 [06:47<01:28, 44.42s/it, data_size=464, test_acc=0.796, train_acc=0.769]Test 2: Data size 464: : 90%|█████████ | 9/10 [06:47<00:46, 46.80s/it, data_size=464, test_acc=0.796, train_acc=0.769]Test 2: Data size 496: : 90%|█████████ | 9/10 [06:47<00:46, 46.80s/it, data_size=464, test_acc=0.796, train_acc=0.769]Test 2: Data size 496: : 90%|█████████ | 9/10 [07:43<00:46, 46.80s/it, data_size=496, test_acc=0.908, train_acc=0.892]Test 2: Data size 496: : 100%|██████████| 10/10 [07:43<00:00, 49.54s/it, data_size=496, test_acc=0.908, train_acc=0.892]Test 2: Data size 496: : 100%|██████████| 10/10 [07:43<00:00, 46.35s/it, data_size=496, test_acc=0.908, train_acc=0.892]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [01:21<?, ?it/s, data_size=208, test_acc=0.753, train_acc=0.761]Test 3: Data size 208: : 10%|█ | 1/10 [01:22<12:18, 82.01s/it, data_size=208, test_acc=0.753, train_acc=0.761]Test 3: Data size 240: : 10%|█ | 1/10 [01:22<12:18, 82.01s/it, data_size=208, test_acc=0.753, train_acc=0.761]Test 3: Data size 240: : 10%|█ | 1/10 [01:51<12:18, 82.01s/it, data_size=240, test_acc=0.667, train_acc=0.675]Test 3: Data size 240: : 20%|██ | 2/10 [01:51<06:48, 51.08s/it, data_size=240, test_acc=0.667, train_acc=0.675]Test 3: Data size 272: : 20%|██ | 2/10 [01:51<06:48, 51.08s/it, data_size=240, test_acc=0.667, train_acc=0.675]Test 3: Data size 272: : 20%|██ | 2/10 [02:23<06:48, 51.08s/it, data_size=272, test_acc=0.743, train_acc=0.748]Test 3: Data size 272: : 30%|███ | 3/10 [02:24<04:58, 42.63s/it, data_size=272, test_acc=0.743, train_acc=0.748]Test 3: Data size 304: : 30%|███ | 3/10 [02:24<04:58, 42.63s/it, data_size=272, test_acc=0.743, train_acc=0.748]Test 3: Data size 304: : 30%|███ | 3/10 [03:00<04:58, 42.63s/it, data_size=304, test_acc=0.687, train_acc=0.685]Test 3: Data size 304: : 40%|████ | 4/10 [03:00<04:00, 40.08s/it, data_size=304, test_acc=0.687, train_acc=0.685]Test 3: Data size 336: : 40%|████ | 4/10 [03:00<04:00, 40.08s/it, data_size=304, test_acc=0.687, train_acc=0.685]Test 3: Data size 336: : 40%|████ | 4/10 [03:39<04:00, 40.08s/it, data_size=336, test_acc=0.751, train_acc=0.779]Test 3: Data size 336: : 50%|█████ | 5/10 [03:39<03:19, 39.81s/it, data_size=336, test_acc=0.751, train_acc=0.779]Test 3: Data size 368: : 50%|█████ | 5/10 [03:39<03:19, 39.81s/it, data_size=336, test_acc=0.751, train_acc=0.779]Test 3: Data size 368: : 50%|█████ | 5/10 [04:22<03:19, 39.81s/it, data_size=368, test_acc=0.763, train_acc=0.761]Test 3: Data size 368: : 60%|██████ | 6/10 [04:22<02:43, 40.77s/it, data_size=368, test_acc=0.763, train_acc=0.761]Test 3: Data size 400: : 60%|██████ | 6/10 [04:22<02:43, 40.77s/it, data_size=368, test_acc=0.763, train_acc=0.761]Test 3: Data size 400: : 60%|██████ | 6/10 [05:07<02:43, 40.77s/it, data_size=400, test_acc=0.87, train_acc=0.812] Test 3: Data size 400: : 70%|███████ | 7/10 [05:07<02:07, 42.42s/it, data_size=400, test_acc=0.87, train_acc=0.812]Test 3: Data size 432: : 70%|███████ | 7/10 [05:07<02:07, 42.42s/it, data_size=400, test_acc=0.87, train_acc=0.812]Test 3: Data size 432: : 70%|███████ | 7/10 [05:57<02:07, 42.42s/it, data_size=432, test_acc=0.875, train_acc=0.818]Test 3: Data size 432: : 80%|████████ | 8/10 [05:57<01:29, 44.69s/it, data_size=432, test_acc=0.875, train_acc=0.818]Test 3: Data size 464: : 80%|████████ | 8/10 [05:57<01:29, 44.69s/it, data_size=432, test_acc=0.875, train_acc=0.818]Test 3: Data size 464: : 80%|████████ | 8/10 [06:50<01:29, 44.69s/it, data_size=464, test_acc=0.864, train_acc=0.807]Test 3: Data size 464: : 90%|█████████ | 9/10 [06:50<00:47, 47.26s/it, data_size=464, test_acc=0.864, train_acc=0.807]Test 3: Data size 496: : 90%|█████████ | 9/10 [06:50<00:47, 47.26s/it, data_size=464, test_acc=0.864, train_acc=0.807]Test 3: Data size 496: : 90%|█████████ | 9/10 [07:46<00:47, 47.26s/it, data_size=496, test_acc=0.887, train_acc=0.817]Test 3: Data size 496: : 100%|██████████| 10/10 [07:46<00:00, 49.95s/it, data_size=496, test_acc=0.887, train_acc=0.817]Test 3: Data size 496: : 100%|██████████| 10/10 [07:46<00:00, 46.64s/it, data_size=496, test_acc=0.887, train_acc=0.817]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [01:21<?, ?it/s, data_size=208, test_acc=0.648, train_acc=0.656]Test 4: Data size 208: : 10%|█ | 1/10 [01:21<12:15, 81.75s/it, data_size=208, test_acc=0.648, train_acc=0.656]Test 4: Data size 240: : 10%|█ | 1/10 [01:21<12:15, 81.75s/it, data_size=208, test_acc=0.648, train_acc=0.656]Test 4: Data size 240: : 10%|█ | 1/10 [01:50<12:15, 81.75s/it, data_size=240, test_acc=0.738, train_acc=0.765]Test 4: Data size 240: : 20%|██ | 2/10 [01:50<06:45, 50.73s/it, data_size=240, test_acc=0.738, train_acc=0.765]Test 4: Data size 272: : 20%|██ | 2/10 [01:50<06:45, 50.73s/it, data_size=240, test_acc=0.738, train_acc=0.765]Test 4: Data size 272: : 20%|██ | 2/10 [02:22<06:45, 50.73s/it, data_size=272, test_acc=0.734, train_acc=0.747]Test 4: Data size 272: : 30%|███ | 3/10 [02:22<04:54, 42.13s/it, data_size=272, test_acc=0.734, train_acc=0.747]Test 4: Data size 304: : 30%|███ | 3/10 [02:22<04:54, 42.13s/it, data_size=272, test_acc=0.734, train_acc=0.747]Test 4: Data size 304: : 30%|███ | 3/10 [02:57<04:54, 42.13s/it, data_size=304, test_acc=0.735, train_acc=0.787]Test 4: Data size 304: : 40%|████ | 4/10 [02:57<03:56, 39.42s/it, data_size=304, test_acc=0.735, train_acc=0.787]Test 4: Data size 336: : 40%|████ | 4/10 [02:57<03:56, 39.42s/it, data_size=304, test_acc=0.735, train_acc=0.787]Test 4: Data size 336: : 40%|████ | 4/10 [03:36<03:56, 39.42s/it, data_size=336, test_acc=0.741, train_acc=0.725]Test 4: Data size 336: : 50%|█████ | 5/10 [03:36<03:15, 39.13s/it, data_size=336, test_acc=0.741, train_acc=0.725]Test 4: Data size 368: : 50%|█████ | 5/10 [03:36<03:15, 39.13s/it, data_size=336, test_acc=0.741, train_acc=0.725]Test 4: Data size 368: : 50%|█████ | 5/10 [04:17<03:15, 39.13s/it, data_size=368, test_acc=0.844, train_acc=0.744]Test 4: Data size 368: : 60%|██████ | 6/10 [04:18<02:39, 39.93s/it, data_size=368, test_acc=0.844, train_acc=0.744]Test 4: Data size 400: : 60%|██████ | 6/10 [04:18<02:39, 39.93s/it, data_size=368, test_acc=0.844, train_acc=0.744]Test 4: Data size 400: : 60%|██████ | 6/10 [05:02<02:39, 39.93s/it, data_size=400, test_acc=0.816, train_acc=0.85] Test 4: Data size 400: : 70%|███████ | 7/10 [05:02<02:04, 41.49s/it, data_size=400, test_acc=0.816, train_acc=0.85]Test 4: Data size 432: : 70%|███████ | 7/10 [05:02<02:04, 41.49s/it, data_size=400, test_acc=0.816, train_acc=0.85]Test 4: Data size 432: : 70%|███████ | 7/10 [05:50<02:04, 41.49s/it, data_size=432, test_acc=0.846, train_acc=0.85]Test 4: Data size 432: : 80%|████████ | 8/10 [05:50<01:26, 43.43s/it, data_size=432, test_acc=0.846, train_acc=0.85]Test 4: Data size 464: : 80%|████████ | 8/10 [05:50<01:26, 43.43s/it, data_size=432, test_acc=0.846, train_acc=0.85]Test 4: Data size 464: : 80%|████████ | 8/10 [06:41<01:26, 43.43s/it, data_size=464, test_acc=0.857, train_acc=0.799]Test 4: Data size 464: : 90%|█████████ | 9/10 [06:41<00:45, 45.89s/it, data_size=464, test_acc=0.857, train_acc=0.799]Test 4: Data size 496: : 90%|█████████ | 9/10 [06:41<00:45, 45.89s/it, data_size=464, test_acc=0.857, train_acc=0.799]Test 4: Data size 496: : 90%|█████████ | 9/10 [07:36<00:45, 45.89s/it, data_size=496, test_acc=0.876, train_acc=0.863]Test 4: Data size 496: : 100%|██████████| 10/10 [07:36<00:00, 48.71s/it, data_size=496, test_acc=0.876, train_acc=0.863]Test 4: Data size 496: : 100%|██████████| 10/10 [07:36<00:00, 45.66s/it, data_size=496, test_acc=0.876, train_acc=0.863]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [01:22<?, ?it/s, data_size=208, test_acc=0.698, train_acc=0.734]Test 5: Data size 208: : 10%|█ | 1/10 [01:22<12:21, 82.40s/it, data_size=208, test_acc=0.698, train_acc=0.734]Test 5: Data size 240: : 10%|█ | 1/10 [01:22<12:21, 82.40s/it, data_size=208, test_acc=0.698, train_acc=0.734]Test 5: Data size 240: : 10%|█ | 1/10 [01:51<12:21, 82.40s/it, data_size=240, test_acc=0.74, train_acc=0.763] Test 5: Data size 240: : 20%|██ | 2/10 [01:51<06:50, 51.26s/it, data_size=240, test_acc=0.74, train_acc=0.763]Test 5: Data size 272: : 20%|██ | 2/10 [01:51<06:50, 51.26s/it, data_size=240, test_acc=0.74, train_acc=0.763]Test 5: Data size 272: : 20%|██ | 2/10 [02:24<06:50, 51.26s/it, data_size=272, test_acc=0.758, train_acc=0.841]Test 5: Data size 272: : 30%|███ | 3/10 [02:25<05:01, 43.02s/it, data_size=272, test_acc=0.758, train_acc=0.841]Test 5: Data size 304: : 30%|███ | 3/10 [02:25<05:01, 43.02s/it, data_size=272, test_acc=0.758, train_acc=0.841]Test 5: Data size 304: : 30%|███ | 3/10 [03:01<05:01, 43.02s/it, data_size=304, test_acc=0.762, train_acc=0.844]Test 5: Data size 304: : 40%|████ | 4/10 [03:01<04:02, 40.48s/it, data_size=304, test_acc=0.762, train_acc=0.844]Test 5: Data size 336: : 40%|████ | 4/10 [03:01<04:02, 40.48s/it, data_size=304, test_acc=0.762, train_acc=0.844]Test 5: Data size 336: : 40%|████ | 4/10 [03:41<04:02, 40.48s/it, data_size=336, test_acc=0.721, train_acc=0.734]Test 5: Data size 336: : 50%|█████ | 5/10 [03:41<03:21, 40.20s/it, data_size=336, test_acc=0.721, train_acc=0.734]Test 5: Data size 368: : 50%|█████ | 5/10 [03:41<03:21, 40.20s/it, data_size=336, test_acc=0.721, train_acc=0.734]Test 5: Data size 368: : 50%|█████ | 5/10 [04:24<03:21, 40.20s/it, data_size=368, test_acc=0.769, train_acc=0.79] Test 5: Data size 368: : 60%|██████ | 6/10 [04:24<02:44, 41.18s/it, data_size=368, test_acc=0.769, train_acc=0.79]Test 5: Data size 400: : 60%|██████ | 6/10 [04:24<02:44, 41.18s/it, data_size=368, test_acc=0.769, train_acc=0.79]Test 5: Data size 400: : 60%|██████ | 6/10 [05:10<02:44, 41.18s/it, data_size=400, test_acc=0.767, train_acc=0.835]Test 5: Data size 400: : 70%|███████ | 7/10 [05:10<02:08, 42.79s/it, data_size=400, test_acc=0.767, train_acc=0.835]Test 5: Data size 432: : 70%|███████ | 7/10 [05:10<02:08, 42.79s/it, data_size=400, test_acc=0.767, train_acc=0.835]Test 5: Data size 432: : 70%|███████ | 7/10 [05:59<02:08, 42.79s/it, data_size=432, test_acc=0.757, train_acc=0.749]Test 5: Data size 432: : 80%|████████ | 8/10 [05:59<01:29, 44.90s/it, data_size=432, test_acc=0.757, train_acc=0.749]Test 5: Data size 464: : 80%|████████ | 8/10 [05:59<01:29, 44.90s/it, data_size=432, test_acc=0.757, train_acc=0.749]Test 5: Data size 464: : 80%|████████ | 8/10 [06:53<01:29, 44.90s/it, data_size=464, test_acc=0.759, train_acc=0.8] Test 5: Data size 464: : 90%|█████████ | 9/10 [06:53<00:47, 47.52s/it, data_size=464, test_acc=0.759, train_acc=0.8]Test 5: Data size 496: : 90%|█████████ | 9/10 [06:53<00:47, 47.52s/it, data_size=464, test_acc=0.759, train_acc=0.8]Test 5: Data size 496: : 90%|█████████ | 9/10 [07:49<00:47, 47.52s/it, data_size=496, test_acc=0.779, train_acc=0.85]Test 5: Data size 496: : 100%|██████████| 10/10 [07:49<00:00, 50.24s/it, data_size=496, test_acc=0.779, train_acc=0.85]Test 5: Data size 496: : 100%|██████████| 10/10 [07:49<00:00, 46.96s/it, data_size=496, test_acc=0.779, train_acc=0.85]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [01:21<?, ?it/s, data_size=208, test_acc=0.585, train_acc=0.595]Test 6: Data size 208: : 10%|█ | 1/10 [01:21<12:14, 81.62s/it, data_size=208, test_acc=0.585, train_acc=0.595]Test 6: Data size 240: : 10%|█ | 1/10 [01:21<12:14, 81.62s/it, data_size=208, test_acc=0.585, train_acc=0.595]Test 6: Data size 240: : 10%|█ | 1/10 [01:50<12:14, 81.62s/it, data_size=240, test_acc=0.683, train_acc=0.702]Test 6: Data size 240: : 20%|██ | 2/10 [01:50<06:46, 50.79s/it, data_size=240, test_acc=0.683, train_acc=0.702]Test 6: Data size 272: : 20%|██ | 2/10 [01:50<06:46, 50.79s/it, data_size=240, test_acc=0.683, train_acc=0.702]Test 6: Data size 272: : 20%|██ | 2/10 [02:22<06:46, 50.79s/it, data_size=272, test_acc=0.7, train_acc=0.69] Test 6: Data size 272: : 30%|███ | 3/10 [02:22<04:55, 42.23s/it, data_size=272, test_acc=0.7, train_acc=0.69]Test 6: Data size 304: : 30%|███ | 3/10 [02:22<04:55, 42.23s/it, data_size=272, test_acc=0.7, train_acc=0.69]Test 6: Data size 304: : 30%|███ | 3/10 [02:58<04:55, 42.23s/it, data_size=304, test_acc=0.628, train_acc=0.663]Test 6: Data size 304: : 40%|████ | 4/10 [02:58<03:57, 39.56s/it, data_size=304, test_acc=0.628, train_acc=0.663]Test 6: Data size 336: : 40%|████ | 4/10 [02:58<03:57, 39.56s/it, data_size=304, test_acc=0.628, train_acc=0.663]Test 6: Data size 336: : 40%|████ | 4/10 [03:36<03:57, 39.56s/it, data_size=336, test_acc=0.694, train_acc=0.782]Test 6: Data size 336: : 50%|█████ | 5/10 [03:36<03:15, 39.18s/it, data_size=336, test_acc=0.694, train_acc=0.782]Test 6: Data size 368: : 50%|█████ | 5/10 [03:36<03:15, 39.18s/it, data_size=336, test_acc=0.694, train_acc=0.782]Test 6: Data size 368: : 50%|█████ | 5/10 [04:18<03:15, 39.18s/it, data_size=368, test_acc=0.68, train_acc=0.752] Test 6: Data size 368: : 60%|██████ | 6/10 [04:18<02:39, 39.97s/it, data_size=368, test_acc=0.68, train_acc=0.752]Test 6: Data size 400: : 60%|██████ | 6/10 [04:18<02:39, 39.97s/it, data_size=368, test_acc=0.68, train_acc=0.752]Test 6: Data size 400: : 60%|██████ | 6/10 [05:03<02:39, 39.97s/it, data_size=400, test_acc=0.713, train_acc=0.751]Test 6: Data size 400: : 70%|███████ | 7/10 [05:03<02:04, 41.61s/it, data_size=400, test_acc=0.713, train_acc=0.751]Test 6: Data size 432: : 70%|███████ | 7/10 [05:03<02:04, 41.61s/it, data_size=400, test_acc=0.713, train_acc=0.751]Test 6: Data size 432: : 70%|███████ | 7/10 [05:51<02:04, 41.61s/it, data_size=432, test_acc=0.861, train_acc=0.866]Test 6: Data size 432: : 80%|████████ | 8/10 [05:51<01:27, 43.79s/it, data_size=432, test_acc=0.861, train_acc=0.866]Test 6: Data size 464: : 80%|████████ | 8/10 [05:51<01:27, 43.79s/it, data_size=432, test_acc=0.861, train_acc=0.866]Test 6: Data size 464: : 80%|████████ | 8/10 [06:42<01:27, 43.79s/it, data_size=464, test_acc=0.882, train_acc=0.862]Test 6: Data size 464: : 90%|█████████ | 9/10 [06:43<00:46, 46.13s/it, data_size=464, test_acc=0.882, train_acc=0.862]Test 6: Data size 496: : 90%|█████████ | 9/10 [06:43<00:46, 46.13s/it, data_size=464, test_acc=0.882, train_acc=0.862]Test 6: Data size 496: : 90%|█████████ | 9/10 [07:37<00:46, 46.13s/it, data_size=496, test_acc=0.871, train_acc=0.854]Test 6: Data size 496: : 100%|██████████| 10/10 [07:37<00:00, 48.73s/it, data_size=496, test_acc=0.871, train_acc=0.854]Test 6: Data size 496: : 100%|██████████| 10/10 [07:37<00:00, 45.76s/it, data_size=496, test_acc=0.871, train_acc=0.854]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [01:22<?, ?it/s, data_size=208, test_acc=0.665, train_acc=0.639]Test 7: Data size 208: : 10%|█ | 1/10 [01:22<12:20, 82.29s/it, data_size=208, test_acc=0.665, train_acc=0.639]Test 7: Data size 240: : 10%|█ | 1/10 [01:22<12:20, 82.29s/it, data_size=208, test_acc=0.665, train_acc=0.639]Test 7: Data size 240: : 10%|█ | 1/10 [01:51<12:20, 82.29s/it, data_size=240, test_acc=0.69, train_acc=0.735] Test 7: Data size 240: : 20%|██ | 2/10 [01:51<06:47, 50.99s/it, data_size=240, test_acc=0.69, train_acc=0.735]Test 7: Data size 272: : 20%|██ | 2/10 [01:51<06:47, 50.99s/it, data_size=240, test_acc=0.69, train_acc=0.735]Test 7: Data size 272: : 20%|██ | 2/10 [02:23<06:47, 50.99s/it, data_size=272, test_acc=0.727, train_acc=0.788]Test 7: Data size 272: : 30%|███ | 3/10 [02:23<04:56, 42.42s/it, data_size=272, test_acc=0.727, train_acc=0.788]Test 7: Data size 304: : 30%|███ | 3/10 [02:23<04:56, 42.42s/it, data_size=272, test_acc=0.727, train_acc=0.788]Test 7: Data size 304: : 30%|███ | 3/10 [02:59<04:56, 42.42s/it, data_size=304, test_acc=0.728, train_acc=0.768]Test 7: Data size 304: : 40%|████ | 4/10 [02:59<03:58, 39.81s/it, data_size=304, test_acc=0.728, train_acc=0.768]Test 7: Data size 336: : 40%|████ | 4/10 [02:59<03:58, 39.81s/it, data_size=304, test_acc=0.728, train_acc=0.768]Test 7: Data size 336: : 40%|████ | 4/10 [03:38<03:58, 39.81s/it, data_size=336, test_acc=0.742, train_acc=0.777]Test 7: Data size 336: : 50%|█████ | 5/10 [03:39<03:18, 39.76s/it, data_size=336, test_acc=0.742, train_acc=0.777]Test 7: Data size 368: : 50%|█████ | 5/10 [03:39<03:18, 39.76s/it, data_size=336, test_acc=0.742, train_acc=0.777]Test 7: Data size 368: : 50%|█████ | 5/10 [04:21<03:18, 39.76s/it, data_size=368, test_acc=0.737, train_acc=0.763]Test 7: Data size 368: : 60%|██████ | 6/10 [04:21<02:42, 40.73s/it, data_size=368, test_acc=0.737, train_acc=0.763]Test 7: Data size 400: : 60%|██████ | 6/10 [04:21<02:42, 40.73s/it, data_size=368, test_acc=0.737, train_acc=0.763]Test 7: Data size 400: : 60%|██████ | 6/10 [05:07<02:42, 40.73s/it, data_size=400, test_acc=0.728, train_acc=0.804]Test 7: Data size 400: : 70%|███████ | 7/10 [05:07<02:06, 42.32s/it, data_size=400, test_acc=0.728, train_acc=0.804]Test 7: Data size 432: : 70%|███████ | 7/10 [05:07<02:06, 42.32s/it, data_size=400, test_acc=0.728, train_acc=0.804]Test 7: Data size 432: : 70%|███████ | 7/10 [05:56<02:06, 42.32s/it, data_size=432, test_acc=0.732, train_acc=0.762]Test 7: Data size 432: : 80%|████████ | 8/10 [05:56<01:28, 44.49s/it, data_size=432, test_acc=0.732, train_acc=0.762]Test 7: Data size 464: : 80%|████████ | 8/10 [05:56<01:28, 44.49s/it, data_size=432, test_acc=0.732, train_acc=0.762]Test 7: Data size 464: : 80%|████████ | 8/10 [06:48<01:28, 44.49s/it, data_size=464, test_acc=0.733, train_acc=0.781]Test 7: Data size 464: : 90%|█████████ | 9/10 [06:48<00:46, 46.93s/it, data_size=464, test_acc=0.733, train_acc=0.781]Test 7: Data size 496: : 90%|█████████ | 9/10 [06:48<00:46, 46.93s/it, data_size=464, test_acc=0.733, train_acc=0.781]Test 7: Data size 496: : 90%|█████████ | 9/10 [07:44<00:46, 46.93s/it, data_size=496, test_acc=0.716, train_acc=0.736]Test 7: Data size 496: : 100%|██████████| 10/10 [07:44<00:00, 49.58s/it, data_size=496, test_acc=0.716, train_acc=0.736]Test 7: Data size 496: : 100%|██████████| 10/10 [07:44<00:00, 46.42s/it, data_size=496, test_acc=0.716, train_acc=0.736]
working on model Multimodal-middle-fusion-model-based-on-AlexNet with BADGE
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [01:02<?, ?it/s, data_size=208, test_acc=0.671, train_acc=0.668]Test 0: Data size 208: : 10%|█ | 1/10 [01:02<09:26, 62.95s/it, data_size=208, test_acc=0.671, train_acc=0.668]Test 0: Data size 239: : 10%|█ | 1/10 [01:02<09:26, 62.95s/it, data_size=208, test_acc=0.671, train_acc=0.668]Test 0: Data size 239: : 10%|█ | 1/10 [02:08<09:26, 62.95s/it, data_size=239, test_acc=0.615, train_acc=0.626]Test 0: Data size 239: : 20%|██ | 2/10 [02:08<08:36, 64.58s/it, data_size=239, test_acc=0.615, train_acc=0.626]Test 0: Data size 270: : 20%|██ | 2/10 [02:08<08:36, 64.58s/it, data_size=239, test_acc=0.615, train_acc=0.626]Test 0: Data size 270: : 20%|██ | 2/10 [03:17<08:36, 64.58s/it, data_size=270, test_acc=0.62, train_acc=0.672] Test 0: Data size 270: : 30%|███ | 3/10 [03:17<07:45, 66.52s/it, data_size=270, test_acc=0.62, train_acc=0.672]Test 0: Data size 301: : 30%|███ | 3/10 [03:17<07:45, 66.52s/it, data_size=270, test_acc=0.62, train_acc=0.672]Test 0: Data size 301: : 30%|███ | 3/10 [04:29<07:45, 66.52s/it, data_size=301, test_acc=0.73, train_acc=0.755]Test 0: Data size 301: : 40%|████ | 4/10 [04:29<06:51, 68.55s/it, data_size=301, test_acc=0.73, train_acc=0.755]Test 0: Data size 332: : 40%|████ | 4/10 [04:29<06:51, 68.55s/it, data_size=301, test_acc=0.73, train_acc=0.755]Test 0: Data size 332: : 40%|████ | 4/10 [05:43<06:51, 68.55s/it, data_size=332, test_acc=0.701, train_acc=0.761]Test 0: Data size 332: : 50%|█████ | 5/10 [05:43<05:53, 70.69s/it, data_size=332, test_acc=0.701, train_acc=0.761]Test 0: Data size 363: : 50%|█████ | 5/10 [05:43<05:53, 70.69s/it, data_size=332, test_acc=0.701, train_acc=0.761]Test 0: Data size 363: : 50%|█████ | 5/10 [07:00<05:53, 70.69s/it, data_size=363, test_acc=0.766, train_acc=0.809]Test 0: Data size 363: : 60%|██████ | 6/10 [07:00<04:51, 72.87s/it, data_size=363, test_acc=0.766, train_acc=0.809]Test 0: Data size 394: : 60%|██████ | 6/10 [07:00<04:51, 72.87s/it, data_size=363, test_acc=0.766, train_acc=0.809]Test 0: Data size 394: : 60%|██████ | 6/10 [08:20<04:51, 72.87s/it, data_size=394, test_acc=0.772, train_acc=0.816]Test 0: Data size 394: : 70%|███████ | 7/10 [08:20<03:45, 75.26s/it, data_size=394, test_acc=0.772, train_acc=0.816]Test 0: Data size 425: : 70%|███████ | 7/10 [08:20<03:45, 75.26s/it, data_size=394, test_acc=0.772, train_acc=0.816]Test 0: Data size 425: : 70%|███████ | 7/10 [09:43<03:45, 75.26s/it, data_size=425, test_acc=0.808, train_acc=0.854]Test 0: Data size 425: : 80%|████████ | 8/10 [09:43<02:35, 77.68s/it, data_size=425, test_acc=0.808, train_acc=0.854]Test 0: Data size 456: : 80%|████████ | 8/10 [09:43<02:35, 77.68s/it, data_size=425, test_acc=0.808, train_acc=0.854]Test 0: Data size 456: : 80%|████████ | 8/10 [11:09<02:35, 77.68s/it, data_size=456, test_acc=0.822, train_acc=0.84] Test 0: Data size 456: : 90%|█████████ | 9/10 [11:09<01:20, 80.23s/it, data_size=456, test_acc=0.822, train_acc=0.84]Test 0: Data size 487: : 90%|█████████ | 9/10 [11:09<01:20, 80.23s/it, data_size=456, test_acc=0.822, train_acc=0.84]Test 0: Data size 487: : 90%|█████████ | 9/10 [12:38<01:20, 80.23s/it, data_size=487, test_acc=0.819, train_acc=0.862]Test 0: Data size 487: : 100%|██████████| 10/10 [12:38<00:00, 82.93s/it, data_size=487, test_acc=0.819, train_acc=0.862]Test 0: Data size 487: : 100%|██████████| 10/10 [12:38<00:00, 75.86s/it, data_size=487, test_acc=0.819, train_acc=0.862]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [01:03<?, ?it/s, data_size=208, test_acc=0.681, train_acc=0.676]Test 1: Data size 208: : 10%|█ | 1/10 [01:03<09:33, 63.73s/it, data_size=208, test_acc=0.681, train_acc=0.676]Test 1: Data size 239: : 10%|█ | 1/10 [01:03<09:33, 63.73s/it, data_size=208, test_acc=0.681, train_acc=0.676]Test 1: Data size 239: : 10%|█ | 1/10 [02:10<09:33, 63.73s/it, data_size=239, test_acc=0.781, train_acc=0.77] Test 1: Data size 239: : 20%|██ | 2/10 [02:10<08:43, 65.39s/it, data_size=239, test_acc=0.781, train_acc=0.77]Test 1: Data size 270: : 20%|██ | 2/10 [02:10<08:43, 65.39s/it, data_size=239, test_acc=0.781, train_acc=0.77]Test 1: Data size 270: : 20%|██ | 2/10 [03:19<08:43, 65.39s/it, data_size=270, test_acc=0.682, train_acc=0.679]Test 1: Data size 270: : 30%|███ | 3/10 [03:19<07:50, 67.19s/it, data_size=270, test_acc=0.682, train_acc=0.679]Test 1: Data size 301: : 30%|███ | 3/10 [03:19<07:50, 67.19s/it, data_size=270, test_acc=0.682, train_acc=0.679]Test 1: Data size 301: : 30%|███ | 3/10 [04:31<07:50, 67.19s/it, data_size=301, test_acc=0.734, train_acc=0.75] Test 1: Data size 301: : 40%|████ | 4/10 [04:31<06:55, 69.24s/it, data_size=301, test_acc=0.734, train_acc=0.75]Test 1: Data size 332: : 40%|████ | 4/10 [04:31<06:55, 69.24s/it, data_size=301, test_acc=0.734, train_acc=0.75]Test 1: Data size 332: : 40%|████ | 4/10 [05:47<06:55, 69.24s/it, data_size=332, test_acc=0.872, train_acc=0.831]Test 1: Data size 332: : 50%|█████ | 5/10 [05:47<05:57, 71.44s/it, data_size=332, test_acc=0.872, train_acc=0.831]Test 1: Data size 363: : 50%|█████ | 5/10 [05:47<05:57, 71.44s/it, data_size=332, test_acc=0.872, train_acc=0.831]Test 1: Data size 363: : 50%|█████ | 5/10 [07:05<05:57, 71.44s/it, data_size=363, test_acc=0.75, train_acc=0.793] Test 1: Data size 363: : 60%|██████ | 6/10 [07:05<04:54, 73.67s/it, data_size=363, test_acc=0.75, train_acc=0.793]Test 1: Data size 394: : 60%|██████ | 6/10 [07:05<04:54, 73.67s/it, data_size=363, test_acc=0.75, train_acc=0.793]Test 1: Data size 394: : 60%|██████ | 6/10 [08:26<04:54, 73.67s/it, data_size=394, test_acc=0.85, train_acc=0.853]Test 1: Data size 394: : 70%|███████ | 7/10 [08:26<03:48, 76.06s/it, data_size=394, test_acc=0.85, train_acc=0.853]Test 1: Data size 425: : 70%|███████ | 7/10 [08:26<03:48, 76.06s/it, data_size=394, test_acc=0.85, train_acc=0.853]Test 1: Data size 425: : 70%|███████ | 7/10 [09:50<03:48, 76.06s/it, data_size=425, test_acc=0.852, train_acc=0.863]Test 1: Data size 425: : 80%|████████ | 8/10 [09:50<02:37, 78.65s/it, data_size=425, test_acc=0.852, train_acc=0.863]Test 1: Data size 456: : 80%|████████ | 8/10 [09:50<02:37, 78.65s/it, data_size=425, test_acc=0.852, train_acc=0.863]Test 1: Data size 456: : 80%|████████ | 8/10 [11:17<02:37, 78.65s/it, data_size=456, test_acc=0.768, train_acc=0.828]Test 1: Data size 456: : 90%|█████████ | 9/10 [11:17<01:21, 81.18s/it, data_size=456, test_acc=0.768, train_acc=0.828]Test 1: Data size 487: : 90%|█████████ | 9/10 [11:17<01:21, 81.18s/it, data_size=456, test_acc=0.768, train_acc=0.828]Test 1: Data size 487: : 90%|█████████ | 9/10 [12:48<01:21, 81.18s/it, data_size=487, test_acc=0.828, train_acc=0.86] Test 1: Data size 487: : 100%|██████████| 10/10 [12:48<00:00, 84.22s/it, data_size=487, test_acc=0.828, train_acc=0.86]Test 1: Data size 487: : 100%|██████████| 10/10 [12:48<00:00, 76.83s/it, data_size=487, test_acc=0.828, train_acc=0.86]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [01:02<?, ?it/s, data_size=208, test_acc=0.638, train_acc=0.665]Test 2: Data size 208: : 10%|█ | 1/10 [01:02<09:26, 62.95s/it, data_size=208, test_acc=0.638, train_acc=0.665]Test 2: Data size 239: : 10%|█ | 1/10 [01:02<09:26, 62.95s/it, data_size=208, test_acc=0.638, train_acc=0.665]Test 2: Data size 239: : 10%|█ | 1/10 [02:08<09:26, 62.95s/it, data_size=239, test_acc=0.651, train_acc=0.673]Test 2: Data size 239: : 20%|██ | 2/10 [02:08<08:36, 64.59s/it, data_size=239, test_acc=0.651, train_acc=0.673]Test 2: Data size 270: : 20%|██ | 2/10 [02:08<08:36, 64.59s/it, data_size=239, test_acc=0.651, train_acc=0.673]Test 2: Data size 270: : 20%|██ | 2/10 [03:17<08:36, 64.59s/it, data_size=270, test_acc=0.703, train_acc=0.754]Test 2: Data size 270: : 30%|███ | 3/10 [03:17<07:45, 66.51s/it, data_size=270, test_acc=0.703, train_acc=0.754]Test 2: Data size 301: : 30%|███ | 3/10 [03:17<07:45, 66.51s/it, data_size=270, test_acc=0.703, train_acc=0.754]Test 2: Data size 301: : 30%|███ | 3/10 [04:28<07:45, 66.51s/it, data_size=301, test_acc=0.728, train_acc=0.787]Test 2: Data size 301: : 40%|████ | 4/10 [04:28<06:50, 68.38s/it, data_size=301, test_acc=0.728, train_acc=0.787]Test 2: Data size 332: : 40%|████ | 4/10 [04:28<06:50, 68.38s/it, data_size=301, test_acc=0.728, train_acc=0.787]Test 2: Data size 332: : 40%|████ | 4/10 [05:43<06:50, 68.38s/it, data_size=332, test_acc=0.678, train_acc=0.758]Test 2: Data size 332: : 50%|█████ | 5/10 [05:43<05:53, 70.61s/it, data_size=332, test_acc=0.678, train_acc=0.758]Test 2: Data size 363: : 50%|█████ | 5/10 [05:43<05:53, 70.61s/it, data_size=332, test_acc=0.678, train_acc=0.758]Test 2: Data size 363: : 50%|█████ | 5/10 [07:01<05:53, 70.61s/it, data_size=363, test_acc=0.835, train_acc=0.879]Test 2: Data size 363: : 60%|██████ | 6/10 [07:01<04:52, 73.10s/it, data_size=363, test_acc=0.835, train_acc=0.879]Test 2: Data size 394: : 60%|██████ | 6/10 [07:01<04:52, 73.10s/it, data_size=363, test_acc=0.835, train_acc=0.879]Test 2: Data size 394: : 60%|██████ | 6/10 [08:21<04:52, 73.10s/it, data_size=394, test_acc=0.81, train_acc=0.844] Test 2: Data size 394: : 70%|███████ | 7/10 [08:21<03:46, 75.61s/it, data_size=394, test_acc=0.81, train_acc=0.844]Test 2: Data size 425: : 70%|███████ | 7/10 [08:21<03:46, 75.61s/it, data_size=394, test_acc=0.81, train_acc=0.844]Test 2: Data size 425: : 70%|███████ | 7/10 [09:45<03:46, 75.61s/it, data_size=425, test_acc=0.812, train_acc=0.861]Test 2: Data size 425: : 80%|████████ | 8/10 [09:45<02:36, 78.21s/it, data_size=425, test_acc=0.812, train_acc=0.861]Test 2: Data size 456: : 80%|████████ | 8/10 [09:45<02:36, 78.21s/it, data_size=425, test_acc=0.812, train_acc=0.861]Test 2: Data size 456: : 80%|████████ | 8/10 [11:11<02:36, 78.21s/it, data_size=456, test_acc=0.81, train_acc=0.852] Test 2: Data size 456: : 90%|█████████ | 9/10 [11:11<01:20, 80.71s/it, data_size=456, test_acc=0.81, train_acc=0.852]Test 2: Data size 487: : 90%|█████████ | 9/10 [11:11<01:20, 80.71s/it, data_size=456, test_acc=0.81, train_acc=0.852]Test 2: Data size 487: : 90%|█████████ | 9/10 [12:41<01:20, 80.71s/it, data_size=487, test_acc=0.835, train_acc=0.863]Test 2: Data size 487: : 100%|██████████| 10/10 [12:41<00:00, 83.46s/it, data_size=487, test_acc=0.835, train_acc=0.863]Test 2: Data size 487: : 100%|██████████| 10/10 [12:41<00:00, 76.16s/it, data_size=487, test_acc=0.835, train_acc=0.863]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [01:03<?, ?it/s, data_size=208, test_acc=0.663, train_acc=0.694]Test 3: Data size 208: : 10%|█ | 1/10 [01:03<09:34, 63.88s/it, data_size=208, test_acc=0.663, train_acc=0.694]Test 3: Data size 239: : 10%|█ | 1/10 [01:03<09:34, 63.88s/it, data_size=208, test_acc=0.663, train_acc=0.694]Test 3: Data size 239: : 10%|█ | 1/10 [02:10<09:34, 63.88s/it, data_size=239, test_acc=0.771, train_acc=0.774]Test 3: Data size 239: : 20%|██ | 2/10 [02:10<08:44, 65.62s/it, data_size=239, test_acc=0.771, train_acc=0.774]Test 3: Data size 270: : 20%|██ | 2/10 [02:10<08:44, 65.62s/it, data_size=239, test_acc=0.771, train_acc=0.774]Test 3: Data size 270: : 20%|██ | 2/10 [03:20<08:44, 65.62s/it, data_size=270, test_acc=0.771, train_acc=0.773]Test 3: Data size 270: : 30%|███ | 3/10 [03:20<07:52, 67.54s/it, data_size=270, test_acc=0.771, train_acc=0.773]Test 3: Data size 301: : 30%|███ | 3/10 [03:20<07:52, 67.54s/it, data_size=270, test_acc=0.771, train_acc=0.773]Test 3: Data size 301: : 30%|███ | 3/10 [04:32<07:52, 67.54s/it, data_size=301, test_acc=0.85, train_acc=0.853] Test 3: Data size 301: : 40%|████ | 4/10 [04:33<06:57, 69.52s/it, data_size=301, test_acc=0.85, train_acc=0.853]Test 3: Data size 332: : 40%|████ | 4/10 [04:33<06:57, 69.52s/it, data_size=301, test_acc=0.85, train_acc=0.853]Test 3: Data size 332: : 40%|████ | 4/10 [05:48<06:57, 69.52s/it, data_size=332, test_acc=0.759, train_acc=0.752]Test 3: Data size 332: : 50%|█████ | 5/10 [05:49<05:59, 71.83s/it, data_size=332, test_acc=0.759, train_acc=0.752]Test 3: Data size 363: : 50%|█████ | 5/10 [05:49<05:59, 71.83s/it, data_size=332, test_acc=0.759, train_acc=0.752]Test 3: Data size 363: : 50%|█████ | 5/10 [07:07<05:59, 71.83s/it, data_size=363, test_acc=0.821, train_acc=0.837]Test 3: Data size 363: : 60%|██████ | 6/10 [07:07<04:56, 74.01s/it, data_size=363, test_acc=0.821, train_acc=0.837]Test 3: Data size 394: : 60%|██████ | 6/10 [07:07<04:56, 74.01s/it, data_size=363, test_acc=0.821, train_acc=0.837]Test 3: Data size 394: : 60%|██████ | 6/10 [08:28<04:56, 74.01s/it, data_size=394, test_acc=0.879, train_acc=0.867]Test 3: Data size 394: : 70%|███████ | 7/10 [08:28<03:48, 76.29s/it, data_size=394, test_acc=0.879, train_acc=0.867]Test 3: Data size 425: : 70%|███████ | 7/10 [08:28<03:48, 76.29s/it, data_size=394, test_acc=0.879, train_acc=0.867]Test 3: Data size 425: : 70%|███████ | 7/10 [09:52<03:48, 76.29s/it, data_size=425, test_acc=0.896, train_acc=0.889]Test 3: Data size 425: : 80%|████████ | 8/10 [09:52<02:37, 78.76s/it, data_size=425, test_acc=0.896, train_acc=0.889]Test 3: Data size 456: : 80%|████████ | 8/10 [09:52<02:37, 78.76s/it, data_size=425, test_acc=0.896, train_acc=0.889]Test 3: Data size 456: : 80%|████████ | 8/10 [11:18<02:37, 78.76s/it, data_size=456, test_acc=0.89, train_acc=0.884] Test 3: Data size 456: : 90%|█████████ | 9/10 [11:19<01:21, 81.24s/it, data_size=456, test_acc=0.89, train_acc=0.884]Test 3: Data size 487: : 90%|█████████ | 9/10 [11:19<01:21, 81.24s/it, data_size=456, test_acc=0.89, train_acc=0.884]Test 3: Data size 487: : 90%|█████████ | 9/10 [12:48<01:21, 81.24s/it, data_size=487, test_acc=0.881, train_acc=0.902]Test 3: Data size 487: : 100%|██████████| 10/10 [12:49<00:00, 83.96s/it, data_size=487, test_acc=0.881, train_acc=0.902]Test 3: Data size 487: : 100%|██████████| 10/10 [12:49<00:00, 76.90s/it, data_size=487, test_acc=0.881, train_acc=0.902]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [01:02<?, ?it/s, data_size=208, test_acc=0.704, train_acc=0.715]Test 4: Data size 208: : 10%|█ | 1/10 [01:03<09:27, 63.05s/it, data_size=208, test_acc=0.704, train_acc=0.715]Test 4: Data size 239: : 10%|█ | 1/10 [01:03<09:27, 63.05s/it, data_size=208, test_acc=0.704, train_acc=0.715]Test 4: Data size 239: : 10%|█ | 1/10 [02:09<09:27, 63.05s/it, data_size=239, test_acc=0.728, train_acc=0.759]Test 4: Data size 239: : 20%|██ | 2/10 [02:09<08:39, 64.98s/it, data_size=239, test_acc=0.728, train_acc=0.759]Test 4: Data size 270: : 20%|██ | 2/10 [02:09<08:39, 64.98s/it, data_size=239, test_acc=0.728, train_acc=0.759]Test 4: Data size 270: : 20%|██ | 2/10 [03:18<08:39, 64.98s/it, data_size=270, test_acc=0.733, train_acc=0.777]Test 4: Data size 270: : 30%|███ | 3/10 [03:18<07:48, 66.86s/it, data_size=270, test_acc=0.733, train_acc=0.777]Test 4: Data size 301: : 30%|███ | 3/10 [03:18<07:48, 66.86s/it, data_size=270, test_acc=0.733, train_acc=0.777]Test 4: Data size 301: : 30%|███ | 3/10 [04:30<07:48, 66.86s/it, data_size=301, test_acc=0.787, train_acc=0.812]Test 4: Data size 301: : 40%|████ | 4/10 [04:30<06:52, 68.77s/it, data_size=301, test_acc=0.787, train_acc=0.812]Test 4: Data size 332: : 40%|████ | 4/10 [04:30<06:52, 68.77s/it, data_size=301, test_acc=0.787, train_acc=0.812]Test 4: Data size 332: : 40%|████ | 4/10 [05:45<06:52, 68.77s/it, data_size=332, test_acc=0.835, train_acc=0.861]Test 4: Data size 332: : 50%|█████ | 5/10 [05:45<05:55, 71.10s/it, data_size=332, test_acc=0.835, train_acc=0.861]Test 4: Data size 363: : 50%|█████ | 5/10 [05:45<05:55, 71.10s/it, data_size=332, test_acc=0.835, train_acc=0.861]Test 4: Data size 363: : 50%|█████ | 5/10 [07:03<05:55, 71.10s/it, data_size=363, test_acc=0.875, train_acc=0.906]Test 4: Data size 363: : 60%|██████ | 6/10 [07:03<04:53, 73.46s/it, data_size=363, test_acc=0.875, train_acc=0.906]Test 4: Data size 394: : 60%|██████ | 6/10 [07:03<04:53, 73.46s/it, data_size=363, test_acc=0.875, train_acc=0.906]Test 4: Data size 394: : 60%|██████ | 6/10 [08:24<04:53, 73.46s/it, data_size=394, test_acc=0.807, train_acc=0.806]Test 4: Data size 394: : 70%|███████ | 7/10 [08:24<03:47, 75.90s/it, data_size=394, test_acc=0.807, train_acc=0.806]Test 4: Data size 425: : 70%|███████ | 7/10 [08:24<03:47, 75.90s/it, data_size=394, test_acc=0.807, train_acc=0.806]Test 4: Data size 425: : 70%|███████ | 7/10 [09:47<03:47, 75.90s/it, data_size=425, test_acc=0.867, train_acc=0.88] Test 4: Data size 425: : 80%|████████ | 8/10 [09:47<02:36, 78.31s/it, data_size=425, test_acc=0.867, train_acc=0.88]Test 4: Data size 456: : 80%|████████ | 8/10 [09:47<02:36, 78.31s/it, data_size=425, test_acc=0.867, train_acc=0.88]Test 4: Data size 456: : 80%|████████ | 8/10 [11:14<02:36, 78.31s/it, data_size=456, test_acc=0.891, train_acc=0.882]Test 4: Data size 456: : 90%|█████████ | 9/10 [11:14<01:20, 80.96s/it, data_size=456, test_acc=0.891, train_acc=0.882]Test 4: Data size 487: : 90%|█████████ | 9/10 [11:14<01:20, 80.96s/it, data_size=456, test_acc=0.891, train_acc=0.882]Test 4: Data size 487: : 90%|█████████ | 9/10 [12:44<01:20, 80.96s/it, data_size=487, test_acc=0.887, train_acc=0.898]Test 4: Data size 487: : 100%|██████████| 10/10 [12:44<00:00, 83.62s/it, data_size=487, test_acc=0.887, train_acc=0.898]Test 4: Data size 487: : 100%|██████████| 10/10 [12:44<00:00, 76.42s/it, data_size=487, test_acc=0.887, train_acc=0.898]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [01:03<?, ?it/s, data_size=208, test_acc=0.64, train_acc=0.64]Test 5: Data size 208: : 10%|█ | 1/10 [01:03<09:32, 63.62s/it, data_size=208, test_acc=0.64, train_acc=0.64]Test 5: Data size 239: : 10%|█ | 1/10 [01:03<09:32, 63.62s/it, data_size=208, test_acc=0.64, train_acc=0.64]Test 5: Data size 239: : 10%|█ | 1/10 [02:10<09:32, 63.62s/it, data_size=239, test_acc=0.729, train_acc=0.775]Test 5: Data size 239: : 20%|██ | 2/10 [02:10<08:42, 65.34s/it, data_size=239, test_acc=0.729, train_acc=0.775]Test 5: Data size 270: : 20%|██ | 2/10 [02:10<08:42, 65.34s/it, data_size=239, test_acc=0.729, train_acc=0.775]Test 5: Data size 270: : 20%|██ | 2/10 [03:19<08:42, 65.34s/it, data_size=270, test_acc=0.76, train_acc=0.77] Test 5: Data size 270: : 30%|███ | 3/10 [03:19<07:49, 67.14s/it, data_size=270, test_acc=0.76, train_acc=0.77]Test 5: Data size 301: : 30%|███ | 3/10 [03:19<07:49, 67.14s/it, data_size=270, test_acc=0.76, train_acc=0.77]Test 5: Data size 301: : 30%|███ | 3/10 [04:31<07:49, 67.14s/it, data_size=301, test_acc=0.763, train_acc=0.771]Test 5: Data size 301: : 40%|████ | 4/10 [04:31<06:54, 69.09s/it, data_size=301, test_acc=0.763, train_acc=0.771]Test 5: Data size 332: : 40%|████ | 4/10 [04:31<06:54, 69.09s/it, data_size=301, test_acc=0.763, train_acc=0.771]Test 5: Data size 332: : 40%|████ | 4/10 [05:46<06:54, 69.09s/it, data_size=332, test_acc=0.812, train_acc=0.822]Test 5: Data size 332: : 50%|█████ | 5/10 [05:46<05:55, 71.19s/it, data_size=332, test_acc=0.812, train_acc=0.822]Test 5: Data size 363: : 50%|█████ | 5/10 [05:46<05:55, 71.19s/it, data_size=332, test_acc=0.812, train_acc=0.822]Test 5: Data size 363: : 50%|█████ | 5/10 [07:04<05:55, 71.19s/it, data_size=363, test_acc=0.814, train_acc=0.795]Test 5: Data size 363: : 60%|██████ | 6/10 [07:04<04:53, 73.42s/it, data_size=363, test_acc=0.814, train_acc=0.795]Test 5: Data size 394: : 60%|██████ | 6/10 [07:04<04:53, 73.42s/it, data_size=363, test_acc=0.814, train_acc=0.795]Test 5: Data size 394: : 60%|██████ | 6/10 [08:24<04:53, 73.42s/it, data_size=394, test_acc=0.86, train_acc=0.885] Test 5: Data size 394: : 70%|███████ | 7/10 [08:24<03:47, 75.78s/it, data_size=394, test_acc=0.86, train_acc=0.885]Test 5: Data size 425: : 70%|███████ | 7/10 [08:24<03:47, 75.78s/it, data_size=394, test_acc=0.86, train_acc=0.885]Test 5: Data size 425: : 70%|███████ | 7/10 [09:48<03:47, 75.78s/it, data_size=425, test_acc=0.85, train_acc=0.889]Test 5: Data size 425: : 80%|████████ | 8/10 [09:48<02:36, 78.33s/it, data_size=425, test_acc=0.85, train_acc=0.889]Test 5: Data size 456: : 80%|████████ | 8/10 [09:48<02:36, 78.33s/it, data_size=425, test_acc=0.85, train_acc=0.889]Test 5: Data size 456: : 80%|████████ | 8/10 [11:14<02:36, 78.33s/it, data_size=456, test_acc=0.86, train_acc=0.864]Test 5: Data size 456: : 90%|█████████ | 9/10 [11:15<01:20, 80.86s/it, data_size=456, test_acc=0.86, train_acc=0.864]Test 5: Data size 487: : 90%|█████████ | 9/10 [11:15<01:20, 80.86s/it, data_size=456, test_acc=0.86, train_acc=0.864]Test 5: Data size 487: : 90%|█████████ | 9/10 [12:45<01:20, 80.86s/it, data_size=487, test_acc=0.872, train_acc=0.914]Test 5: Data size 487: : 100%|██████████| 10/10 [12:45<00:00, 83.93s/it, data_size=487, test_acc=0.872, train_acc=0.914]Test 5: Data size 487: : 100%|██████████| 10/10 [12:45<00:00, 76.58s/it, data_size=487, test_acc=0.872, train_acc=0.914]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [01:02<?, ?it/s, data_size=208, test_acc=0.641, train_acc=0.657]Test 6: Data size 208: : 10%|█ | 1/10 [01:03<09:27, 63.02s/it, data_size=208, test_acc=0.641, train_acc=0.657]Test 6: Data size 239: : 10%|█ | 1/10 [01:03<09:27, 63.02s/it, data_size=208, test_acc=0.641, train_acc=0.657]Test 6: Data size 239: : 10%|█ | 1/10 [02:08<09:27, 63.02s/it, data_size=239, test_acc=0.689, train_acc=0.696]Test 6: Data size 239: : 20%|██ | 2/10 [02:08<08:36, 64.57s/it, data_size=239, test_acc=0.689, train_acc=0.696]Test 6: Data size 270: : 20%|██ | 2/10 [02:08<08:36, 64.57s/it, data_size=239, test_acc=0.689, train_acc=0.696]Test 6: Data size 270: : 20%|██ | 2/10 [03:17<08:36, 64.57s/it, data_size=270, test_acc=0.676, train_acc=0.717]Test 6: Data size 270: : 30%|███ | 3/10 [03:17<07:44, 66.38s/it, data_size=270, test_acc=0.676, train_acc=0.717]Test 6: Data size 301: : 30%|███ | 3/10 [03:17<07:44, 66.38s/it, data_size=270, test_acc=0.676, train_acc=0.717]Test 6: Data size 301: : 30%|███ | 3/10 [04:28<07:44, 66.38s/it, data_size=301, test_acc=0.711, train_acc=0.752]Test 6: Data size 301: : 40%|████ | 4/10 [04:29<06:51, 68.52s/it, data_size=301, test_acc=0.711, train_acc=0.752]Test 6: Data size 332: : 40%|████ | 4/10 [04:29<06:51, 68.52s/it, data_size=301, test_acc=0.711, train_acc=0.752]Test 6: Data size 332: : 40%|████ | 4/10 [05:43<06:51, 68.52s/it, data_size=332, test_acc=0.698, train_acc=0.749]Test 6: Data size 332: : 50%|█████ | 5/10 [05:44<05:54, 70.86s/it, data_size=332, test_acc=0.698, train_acc=0.749]Test 6: Data size 363: : 50%|█████ | 5/10 [05:44<05:54, 70.86s/it, data_size=332, test_acc=0.698, train_acc=0.749]Test 6: Data size 363: : 50%|█████ | 5/10 [07:01<05:54, 70.86s/it, data_size=363, test_acc=0.701, train_acc=0.733]Test 6: Data size 363: : 60%|██████ | 6/10 [07:01<04:52, 73.23s/it, data_size=363, test_acc=0.701, train_acc=0.733]Test 6: Data size 394: : 60%|██████ | 6/10 [07:01<04:52, 73.23s/it, data_size=363, test_acc=0.701, train_acc=0.733]Test 6: Data size 394: : 60%|██████ | 6/10 [08:22<04:52, 73.23s/it, data_size=394, test_acc=0.832, train_acc=0.861]Test 6: Data size 394: : 70%|███████ | 7/10 [08:22<03:46, 75.62s/it, data_size=394, test_acc=0.832, train_acc=0.861]Test 6: Data size 425: : 70%|███████ | 7/10 [08:22<03:46, 75.62s/it, data_size=394, test_acc=0.832, train_acc=0.861]Test 6: Data size 425: : 70%|███████ | 7/10 [09:46<03:46, 75.62s/it, data_size=425, test_acc=0.829, train_acc=0.855]Test 6: Data size 425: : 80%|████████ | 8/10 [09:46<02:36, 78.25s/it, data_size=425, test_acc=0.829, train_acc=0.855]Test 6: Data size 456: : 80%|████████ | 8/10 [09:46<02:36, 78.25s/it, data_size=425, test_acc=0.829, train_acc=0.855]Test 6: Data size 456: : 80%|████████ | 8/10 [11:12<02:36, 78.25s/it, data_size=456, test_acc=0.805, train_acc=0.851]Test 6: Data size 456: : 90%|█████████ | 9/10 [11:12<01:20, 80.87s/it, data_size=456, test_acc=0.805, train_acc=0.851]Test 6: Data size 487: : 90%|█████████ | 9/10 [11:12<01:20, 80.87s/it, data_size=456, test_acc=0.805, train_acc=0.851]Test 6: Data size 487: : 90%|█████████ | 9/10 [12:42<01:20, 80.87s/it, data_size=487, test_acc=0.883, train_acc=0.912]Test 6: Data size 487: : 100%|██████████| 10/10 [12:42<00:00, 83.64s/it, data_size=487, test_acc=0.883, train_acc=0.912]Test 6: Data size 487: : 100%|██████████| 10/10 [12:42<00:00, 76.27s/it, data_size=487, test_acc=0.883, train_acc=0.912]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [01:03<?, ?it/s, data_size=208, test_acc=0.712, train_acc=0.713]Test 7: Data size 208: : 10%|█ | 1/10 [01:03<09:34, 63.82s/it, data_size=208, test_acc=0.712, train_acc=0.713]Test 7: Data size 239: : 10%|█ | 1/10 [01:03<09:34, 63.82s/it, data_size=208, test_acc=0.712, train_acc=0.713]Test 7: Data size 239: : 10%|█ | 1/10 [02:10<09:34, 63.82s/it, data_size=239, test_acc=0.69, train_acc=0.696] Test 7: Data size 239: : 20%|██ | 2/10 [02:10<08:44, 65.62s/it, data_size=239, test_acc=0.69, train_acc=0.696]Test 7: Data size 270: : 20%|██ | 2/10 [02:10<08:44, 65.62s/it, data_size=239, test_acc=0.69, train_acc=0.696]Test 7: Data size 270: : 20%|██ | 2/10 [03:20<08:44, 65.62s/it, data_size=270, test_acc=0.692, train_acc=0.703]Test 7: Data size 270: : 30%|███ | 3/10 [03:20<07:52, 67.46s/it, data_size=270, test_acc=0.692, train_acc=0.703]Test 7: Data size 301: : 30%|███ | 3/10 [03:20<07:52, 67.46s/it, data_size=270, test_acc=0.692, train_acc=0.703]Test 7: Data size 301: : 30%|███ | 3/10 [04:32<07:52, 67.46s/it, data_size=301, test_acc=0.742, train_acc=0.784]Test 7: Data size 301: : 40%|████ | 4/10 [04:32<06:56, 69.38s/it, data_size=301, test_acc=0.742, train_acc=0.784]Test 7: Data size 332: : 40%|████ | 4/10 [04:32<06:56, 69.38s/it, data_size=301, test_acc=0.742, train_acc=0.784]Test 7: Data size 332: : 40%|████ | 4/10 [05:48<06:56, 69.38s/it, data_size=332, test_acc=0.697, train_acc=0.756]Test 7: Data size 332: : 50%|█████ | 5/10 [05:48<05:58, 71.67s/it, data_size=332, test_acc=0.697, train_acc=0.756]Test 7: Data size 363: : 50%|█████ | 5/10 [05:48<05:58, 71.67s/it, data_size=332, test_acc=0.697, train_acc=0.756]Test 7: Data size 363: : 50%|█████ | 5/10 [07:06<05:58, 71.67s/it, data_size=363, test_acc=0.792, train_acc=0.797]Test 7: Data size 363: : 60%|██████ | 6/10 [07:06<04:55, 73.91s/it, data_size=363, test_acc=0.792, train_acc=0.797]Test 7: Data size 394: : 60%|██████ | 6/10 [07:06<04:55, 73.91s/it, data_size=363, test_acc=0.792, train_acc=0.797]Test 7: Data size 394: : 60%|██████ | 6/10 [08:27<04:55, 73.91s/it, data_size=394, test_acc=0.846, train_acc=0.823]Test 7: Data size 394: : 70%|███████ | 7/10 [08:27<03:48, 76.26s/it, data_size=394, test_acc=0.846, train_acc=0.823]Test 7: Data size 425: : 70%|███████ | 7/10 [08:27<03:48, 76.26s/it, data_size=394, test_acc=0.846, train_acc=0.823]Test 7: Data size 425: : 70%|███████ | 7/10 [09:51<03:48, 76.26s/it, data_size=425, test_acc=0.846, train_acc=0.834]Test 7: Data size 425: : 80%|████████ | 8/10 [09:52<02:37, 78.81s/it, data_size=425, test_acc=0.846, train_acc=0.834]Test 7: Data size 456: : 80%|████████ | 8/10 [09:52<02:37, 78.81s/it, data_size=425, test_acc=0.846, train_acc=0.834]Test 7: Data size 456: : 80%|████████ | 8/10 [11:18<02:37, 78.81s/it, data_size=456, test_acc=0.86, train_acc=0.865] Test 7: Data size 456: : 90%|█████████ | 9/10 [11:19<01:21, 81.39s/it, data_size=456, test_acc=0.86, train_acc=0.865]Test 7: Data size 487: : 90%|█████████ | 9/10 [11:19<01:21, 81.39s/it, data_size=456, test_acc=0.86, train_acc=0.865]Test 7: Data size 487: : 90%|█████████ | 9/10 [12:49<01:21, 81.39s/it, data_size=487, test_acc=0.893, train_acc=0.9] Test 7: Data size 487: : 100%|██████████| 10/10 [12:49<00:00, 84.15s/it, data_size=487, test_acc=0.893, train_acc=0.9]Test 7: Data size 487: : 100%|██████████| 10/10 [12:49<00:00, 76.94s/it, data_size=487, test_acc=0.893, train_acc=0.9]
working on model Multimodal-late-fusion-model-based-on-AlexNet with RANDOM
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:05<?, ?it/s, data_size=208, test_acc=0.49, train_acc=0.488]Test 0: Data size 208: : 10%|█ | 1/10 [00:05<00:47, 5.30s/it, data_size=208, test_acc=0.49, train_acc=0.488]Test 0: Data size 240: : 10%|█ | 1/10 [00:05<00:47, 5.30s/it, data_size=208, test_acc=0.49, train_acc=0.488]Test 0: Data size 240: : 10%|█ | 1/10 [00:10<00:47, 5.30s/it, data_size=240, test_acc=0.525, train_acc=0.527]Test 0: Data size 240: : 20%|██ | 2/10 [00:10<00:43, 5.40s/it, data_size=240, test_acc=0.525, train_acc=0.527]Test 0: Data size 272: : 20%|██ | 2/10 [00:10<00:43, 5.40s/it, data_size=240, test_acc=0.525, train_acc=0.527]Test 0: Data size 272: : 20%|██ | 2/10 [00:21<00:43, 5.40s/it, data_size=272, test_acc=0.742, train_acc=0.773]Test 0: Data size 272: : 30%|███ | 3/10 [00:21<00:53, 7.67s/it, data_size=272, test_acc=0.742, train_acc=0.773]Test 0: Data size 304: : 30%|███ | 3/10 [00:21<00:53, 7.67s/it, data_size=272, test_acc=0.742, train_acc=0.773]Test 0: Data size 304: : 30%|███ | 3/10 [00:31<00:53, 7.67s/it, data_size=304, test_acc=0.838, train_acc=0.859]Test 0: Data size 304: : 40%|████ | 4/10 [00:31<00:52, 8.71s/it, data_size=304, test_acc=0.838, train_acc=0.859]Test 0: Data size 336: : 40%|████ | 4/10 [00:31<00:52, 8.71s/it, data_size=304, test_acc=0.838, train_acc=0.859]Test 0: Data size 336: : 40%|████ | 4/10 [00:41<00:52, 8.71s/it, data_size=336, test_acc=0.888, train_acc=0.928]Test 0: Data size 336: : 50%|█████ | 5/10 [00:41<00:46, 9.35s/it, data_size=336, test_acc=0.888, train_acc=0.928]Test 0: Data size 368: : 50%|█████ | 5/10 [00:41<00:46, 9.35s/it, data_size=336, test_acc=0.888, train_acc=0.928]Test 0: Data size 368: : 50%|█████ | 5/10 [00:52<00:46, 9.35s/it, data_size=368, test_acc=0.909, train_acc=0.933]Test 0: Data size 368: : 60%|██████ | 6/10 [00:52<00:39, 9.81s/it, data_size=368, test_acc=0.909, train_acc=0.933]Test 0: Data size 400: : 60%|██████ | 6/10 [00:52<00:39, 9.81s/it, data_size=368, test_acc=0.909, train_acc=0.933]Test 0: Data size 400: : 60%|██████ | 6/10 [01:07<00:39, 9.81s/it, data_size=400, test_acc=0.879, train_acc=0.933]Test 0: Data size 400: : 70%|███████ | 7/10 [01:07<00:34, 11.62s/it, data_size=400, test_acc=0.879, train_acc=0.933]Test 0: Data size 432: : 70%|███████ | 7/10 [01:07<00:34, 11.62s/it, data_size=400, test_acc=0.879, train_acc=0.933]Test 0: Data size 432: : 70%|███████ | 7/10 [01:23<00:34, 11.62s/it, data_size=432, test_acc=0.905, train_acc=0.96] Test 0: Data size 432: : 80%|████████ | 8/10 [01:23<00:25, 12.85s/it, data_size=432, test_acc=0.905, train_acc=0.96]Test 0: Data size 464: : 80%|████████ | 8/10 [01:23<00:25, 12.85s/it, data_size=432, test_acc=0.905, train_acc=0.96]Test 0: Data size 464: : 80%|████████ | 8/10 [01:38<00:25, 12.85s/it, data_size=464, test_acc=0.908, train_acc=0.942]Test 0: Data size 464: : 90%|█████████ | 9/10 [01:38<00:13, 13.65s/it, data_size=464, test_acc=0.908, train_acc=0.942]Test 0: Data size 496: : 90%|█████████ | 9/10 [01:38<00:13, 13.65s/it, data_size=464, test_acc=0.908, train_acc=0.942]Test 0: Data size 496: : 90%|█████████ | 9/10 [01:54<00:13, 13.65s/it, data_size=496, test_acc=0.906, train_acc=0.938]Test 0: Data size 496: : 100%|██████████| 10/10 [01:54<00:00, 14.15s/it, data_size=496, test_acc=0.906, train_acc=0.938]Test 0: Data size 496: : 100%|██████████| 10/10 [01:54<00:00, 11.41s/it, data_size=496, test_acc=0.906, train_acc=0.938]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:05<?, ?it/s, data_size=208, test_acc=0.497, train_acc=0.49]Test 1: Data size 208: : 10%|█ | 1/10 [00:05<00:49, 5.51s/it, data_size=208, test_acc=0.497, train_acc=0.49]Test 1: Data size 240: : 10%|█ | 1/10 [00:05<00:49, 5.51s/it, data_size=208, test_acc=0.497, train_acc=0.49]Test 1: Data size 240: : 10%|█ | 1/10 [00:10<00:49, 5.51s/it, data_size=240, test_acc=0.633, train_acc=0.636]Test 1: Data size 240: : 20%|██ | 2/10 [00:11<00:44, 5.54s/it, data_size=240, test_acc=0.633, train_acc=0.636]Test 1: Data size 272: : 20%|██ | 2/10 [00:11<00:44, 5.54s/it, data_size=240, test_acc=0.633, train_acc=0.636]Test 1: Data size 272: : 20%|██ | 2/10 [00:21<00:44, 5.54s/it, data_size=272, test_acc=0.735, train_acc=0.71] Test 1: Data size 272: : 30%|███ | 3/10 [00:21<00:53, 7.68s/it, data_size=272, test_acc=0.735, train_acc=0.71]Test 1: Data size 304: : 30%|███ | 3/10 [00:21<00:53, 7.68s/it, data_size=272, test_acc=0.735, train_acc=0.71]Test 1: Data size 304: : 30%|███ | 3/10 [00:31<00:53, 7.68s/it, data_size=304, test_acc=0.833, train_acc=0.814]Test 1: Data size 304: : 40%|████ | 4/10 [00:31<00:52, 8.73s/it, data_size=304, test_acc=0.833, train_acc=0.814]Test 1: Data size 336: : 40%|████ | 4/10 [00:31<00:52, 8.73s/it, data_size=304, test_acc=0.833, train_acc=0.814]Test 1: Data size 336: : 40%|████ | 4/10 [00:41<00:52, 8.73s/it, data_size=336, test_acc=0.877, train_acc=0.846]Test 1: Data size 336: : 50%|█████ | 5/10 [00:42<00:46, 9.32s/it, data_size=336, test_acc=0.877, train_acc=0.846]Test 1: Data size 368: : 50%|█████ | 5/10 [00:42<00:46, 9.32s/it, data_size=336, test_acc=0.877, train_acc=0.846]Test 1: Data size 368: : 50%|█████ | 5/10 [00:52<00:46, 9.32s/it, data_size=368, test_acc=0.9, train_acc=0.916] Test 1: Data size 368: : 60%|██████ | 6/10 [00:52<00:38, 9.75s/it, data_size=368, test_acc=0.9, train_acc=0.916]Test 1: Data size 400: : 60%|██████ | 6/10 [00:52<00:38, 9.75s/it, data_size=368, test_acc=0.9, train_acc=0.916]Test 1: Data size 400: : 60%|██████ | 6/10 [01:07<00:38, 9.75s/it, data_size=400, test_acc=0.894, train_acc=0.927]Test 1: Data size 400: : 70%|███████ | 7/10 [01:07<00:34, 11.54s/it, data_size=400, test_acc=0.894, train_acc=0.927]Test 1: Data size 432: : 70%|███████ | 7/10 [01:07<00:34, 11.54s/it, data_size=400, test_acc=0.894, train_acc=0.927]Test 1: Data size 432: : 70%|███████ | 7/10 [01:23<00:34, 11.54s/it, data_size=432, test_acc=0.91, train_acc=0.917] Test 1: Data size 432: : 80%|████████ | 8/10 [01:23<00:25, 12.75s/it, data_size=432, test_acc=0.91, train_acc=0.917]Test 1: Data size 464: : 80%|████████ | 8/10 [01:23<00:25, 12.75s/it, data_size=432, test_acc=0.91, train_acc=0.917]Test 1: Data size 464: : 80%|████████ | 8/10 [01:38<00:25, 12.75s/it, data_size=464, test_acc=0.905, train_acc=0.946]Test 1: Data size 464: : 90%|█████████ | 9/10 [01:38<00:13, 13.60s/it, data_size=464, test_acc=0.905, train_acc=0.946]Test 1: Data size 496: : 90%|█████████ | 9/10 [01:38<00:13, 13.60s/it, data_size=464, test_acc=0.905, train_acc=0.946]Test 1: Data size 496: : 90%|█████████ | 9/10 [01:53<00:13, 13.60s/it, data_size=496, test_acc=0.908, train_acc=0.936]Test 1: Data size 496: : 100%|██████████| 10/10 [01:53<00:00, 14.00s/it, data_size=496, test_acc=0.908, train_acc=0.936]Test 1: Data size 496: : 100%|██████████| 10/10 [01:53<00:00, 11.35s/it, data_size=496, test_acc=0.908, train_acc=0.936]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:05<?, ?it/s, data_size=208, test_acc=0.498, train_acc=0.5]Test 2: Data size 208: : 10%|█ | 1/10 [00:05<00:49, 5.46s/it, data_size=208, test_acc=0.498, train_acc=0.5]Test 2: Data size 240: : 10%|█ | 1/10 [00:05<00:49, 5.46s/it, data_size=208, test_acc=0.498, train_acc=0.5]Test 2: Data size 240: : 10%|█ | 1/10 [00:10<00:49, 5.46s/it, data_size=240, test_acc=0.711, train_acc=0.743]Test 2: Data size 240: : 20%|██ | 2/10 [00:11<00:44, 5.55s/it, data_size=240, test_acc=0.711, train_acc=0.743]Test 2: Data size 272: : 20%|██ | 2/10 [00:11<00:44, 5.55s/it, data_size=240, test_acc=0.711, train_acc=0.743]Test 2: Data size 272: : 20%|██ | 2/10 [00:21<00:44, 5.55s/it, data_size=272, test_acc=0.763, train_acc=0.759]Test 2: Data size 272: : 30%|███ | 3/10 [00:21<00:54, 7.74s/it, data_size=272, test_acc=0.763, train_acc=0.759]Test 2: Data size 304: : 30%|███ | 3/10 [00:21<00:54, 7.74s/it, data_size=272, test_acc=0.763, train_acc=0.759]Test 2: Data size 304: : 30%|███ | 3/10 [00:31<00:54, 7.74s/it, data_size=304, test_acc=0.779, train_acc=0.774]Test 2: Data size 304: : 40%|████ | 4/10 [00:31<00:52, 8.81s/it, data_size=304, test_acc=0.779, train_acc=0.774]Test 2: Data size 336: : 40%|████ | 4/10 [00:31<00:52, 8.81s/it, data_size=304, test_acc=0.779, train_acc=0.774]Test 2: Data size 336: : 40%|████ | 4/10 [00:42<00:52, 8.81s/it, data_size=336, test_acc=0.827, train_acc=0.832]Test 2: Data size 336: : 50%|█████ | 5/10 [00:42<00:46, 9.39s/it, data_size=336, test_acc=0.827, train_acc=0.832]Test 2: Data size 368: : 50%|█████ | 5/10 [00:42<00:46, 9.39s/it, data_size=336, test_acc=0.827, train_acc=0.832]Test 2: Data size 368: : 50%|█████ | 5/10 [00:52<00:46, 9.39s/it, data_size=368, test_acc=0.906, train_acc=0.913]Test 2: Data size 368: : 60%|██████ | 6/10 [00:52<00:39, 9.77s/it, data_size=368, test_acc=0.906, train_acc=0.913]Test 2: Data size 400: : 60%|██████ | 6/10 [00:52<00:39, 9.77s/it, data_size=368, test_acc=0.906, train_acc=0.913]Test 2: Data size 400: : 60%|██████ | 6/10 [01:07<00:39, 9.77s/it, data_size=400, test_acc=0.898, train_acc=0.926]Test 2: Data size 400: : 70%|███████ | 7/10 [01:08<00:34, 11.58s/it, data_size=400, test_acc=0.898, train_acc=0.926]Test 2: Data size 432: : 70%|███████ | 7/10 [01:08<00:34, 11.58s/it, data_size=400, test_acc=0.898, train_acc=0.926]Test 2: Data size 432: : 70%|███████ | 7/10 [01:23<00:34, 11.58s/it, data_size=432, test_acc=0.905, train_acc=0.932]Test 2: Data size 432: : 80%|████████ | 8/10 [01:23<00:25, 12.88s/it, data_size=432, test_acc=0.905, train_acc=0.932]Test 2: Data size 464: : 80%|████████ | 8/10 [01:23<00:25, 12.88s/it, data_size=432, test_acc=0.905, train_acc=0.932]Test 2: Data size 464: : 80%|████████ | 8/10 [01:38<00:25, 12.88s/it, data_size=464, test_acc=0.902, train_acc=0.937]Test 2: Data size 464: : 90%|█████████ | 9/10 [01:38<00:13, 13.56s/it, data_size=464, test_acc=0.902, train_acc=0.937]Test 2: Data size 496: : 90%|█████████ | 9/10 [01:38<00:13, 13.56s/it, data_size=464, test_acc=0.902, train_acc=0.937]Test 2: Data size 496: : 90%|█████████ | 9/10 [01:54<00:13, 13.56s/it, data_size=496, test_acc=0.9, train_acc=0.933] Test 2: Data size 496: : 100%|██████████| 10/10 [01:54<00:00, 14.26s/it, data_size=496, test_acc=0.9, train_acc=0.933]Test 2: Data size 496: : 100%|██████████| 10/10 [01:54<00:00, 11.47s/it, data_size=496, test_acc=0.9, train_acc=0.933]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:05<?, ?it/s, data_size=208, test_acc=0.607, train_acc=0.634]Test 3: Data size 208: : 10%|█ | 1/10 [00:05<00:47, 5.28s/it, data_size=208, test_acc=0.607, train_acc=0.634]Test 3: Data size 240: : 10%|█ | 1/10 [00:05<00:47, 5.28s/it, data_size=208, test_acc=0.607, train_acc=0.634]Test 3: Data size 240: : 10%|█ | 1/10 [00:10<00:47, 5.28s/it, data_size=240, test_acc=0.744, train_acc=0.771]Test 3: Data size 240: : 20%|██ | 2/10 [00:10<00:42, 5.35s/it, data_size=240, test_acc=0.744, train_acc=0.771]Test 3: Data size 272: : 20%|██ | 2/10 [00:10<00:42, 5.35s/it, data_size=240, test_acc=0.744, train_acc=0.771]Test 3: Data size 272: : 20%|██ | 2/10 [00:20<00:42, 5.35s/it, data_size=272, test_acc=0.827, train_acc=0.838]Test 3: Data size 272: : 30%|███ | 3/10 [00:20<00:51, 7.41s/it, data_size=272, test_acc=0.827, train_acc=0.838]Test 3: Data size 304: : 30%|███ | 3/10 [00:20<00:51, 7.41s/it, data_size=272, test_acc=0.827, train_acc=0.838]Test 3: Data size 304: : 30%|███ | 3/10 [00:30<00:51, 7.41s/it, data_size=304, test_acc=0.857, train_acc=0.86] Test 3: Data size 304: : 40%|████ | 4/10 [00:30<00:50, 8.38s/it, data_size=304, test_acc=0.857, train_acc=0.86]Test 3: Data size 336: : 40%|████ | 4/10 [00:30<00:50, 8.38s/it, data_size=304, test_acc=0.857, train_acc=0.86]Test 3: Data size 336: : 40%|████ | 4/10 [00:40<00:50, 8.38s/it, data_size=336, test_acc=0.844, train_acc=0.878]Test 3: Data size 336: : 50%|█████ | 5/10 [00:40<00:44, 8.96s/it, data_size=336, test_acc=0.844, train_acc=0.878]Test 3: Data size 368: : 50%|█████ | 5/10 [00:40<00:44, 8.96s/it, data_size=336, test_acc=0.844, train_acc=0.878]Test 3: Data size 368: : 50%|█████ | 5/10 [00:50<00:44, 8.96s/it, data_size=368, test_acc=0.842, train_acc=0.844]Test 3: Data size 368: : 60%|██████ | 6/10 [00:50<00:37, 9.42s/it, data_size=368, test_acc=0.842, train_acc=0.844]Test 3: Data size 400: : 60%|██████ | 6/10 [00:50<00:37, 9.42s/it, data_size=368, test_acc=0.842, train_acc=0.844]Test 3: Data size 400: : 60%|██████ | 6/10 [01:05<00:37, 9.42s/it, data_size=400, test_acc=0.882, train_acc=0.894]Test 3: Data size 400: : 70%|███████ | 7/10 [01:05<00:33, 11.20s/it, data_size=400, test_acc=0.882, train_acc=0.894]Test 3: Data size 432: : 70%|███████ | 7/10 [01:05<00:33, 11.20s/it, data_size=400, test_acc=0.882, train_acc=0.894]Test 3: Data size 432: : 70%|███████ | 7/10 [01:20<00:33, 11.20s/it, data_size=432, test_acc=0.865, train_acc=0.861]Test 3: Data size 432: : 80%|████████ | 8/10 [01:20<00:24, 12.47s/it, data_size=432, test_acc=0.865, train_acc=0.861]Test 3: Data size 464: : 80%|████████ | 8/10 [01:20<00:24, 12.47s/it, data_size=432, test_acc=0.865, train_acc=0.861]Test 3: Data size 464: : 80%|████████ | 8/10 [01:36<00:24, 12.47s/it, data_size=464, test_acc=0.839, train_acc=0.868]Test 3: Data size 464: : 90%|█████████ | 9/10 [01:36<00:13, 13.57s/it, data_size=464, test_acc=0.839, train_acc=0.868]Test 3: Data size 496: : 90%|█████████ | 9/10 [01:36<00:13, 13.57s/it, data_size=464, test_acc=0.839, train_acc=0.868]Test 3: Data size 496: : 90%|█████████ | 9/10 [01:51<00:13, 13.57s/it, data_size=496, test_acc=0.897, train_acc=0.91] Test 3: Data size 496: : 100%|██████████| 10/10 [01:52<00:00, 14.10s/it, data_size=496, test_acc=0.897, train_acc=0.91]Test 3: Data size 496: : 100%|██████████| 10/10 [01:52<00:00, 11.20s/it, data_size=496, test_acc=0.897, train_acc=0.91]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:05<?, ?it/s, data_size=208, test_acc=0.493, train_acc=0.485]Test 4: Data size 208: : 10%|█ | 1/10 [00:05<00:49, 5.54s/it, data_size=208, test_acc=0.493, train_acc=0.485]Test 4: Data size 240: : 10%|█ | 1/10 [00:05<00:49, 5.54s/it, data_size=208, test_acc=0.493, train_acc=0.485]Test 4: Data size 240: : 10%|█ | 1/10 [00:10<00:49, 5.54s/it, data_size=240, test_acc=0.689, train_acc=0.689]Test 4: Data size 240: : 20%|██ | 2/10 [00:11<00:44, 5.56s/it, data_size=240, test_acc=0.689, train_acc=0.689]Test 4: Data size 272: : 20%|██ | 2/10 [00:11<00:44, 5.56s/it, data_size=240, test_acc=0.689, train_acc=0.689]Test 4: Data size 272: : 20%|██ | 2/10 [00:21<00:44, 5.56s/it, data_size=272, test_acc=0.814, train_acc=0.868]Test 4: Data size 272: : 30%|███ | 3/10 [00:21<00:54, 7.72s/it, data_size=272, test_acc=0.814, train_acc=0.868]Test 4: Data size 304: : 30%|███ | 3/10 [00:21<00:54, 7.72s/it, data_size=272, test_acc=0.814, train_acc=0.868]Test 4: Data size 304: : 30%|███ | 3/10 [00:31<00:54, 7.72s/it, data_size=304, test_acc=0.83, train_acc=0.872] Test 4: Data size 304: : 40%|████ | 4/10 [00:31<00:52, 8.77s/it, data_size=304, test_acc=0.83, train_acc=0.872]Test 4: Data size 336: : 40%|████ | 4/10 [00:31<00:52, 8.77s/it, data_size=304, test_acc=0.83, train_acc=0.872]Test 4: Data size 336: : 40%|████ | 4/10 [00:42<00:52, 8.77s/it, data_size=336, test_acc=0.834, train_acc=0.897]Test 4: Data size 336: : 50%|█████ | 5/10 [00:42<00:46, 9.36s/it, data_size=336, test_acc=0.834, train_acc=0.897]Test 4: Data size 368: : 50%|█████ | 5/10 [00:42<00:46, 9.36s/it, data_size=336, test_acc=0.834, train_acc=0.897]Test 4: Data size 368: : 50%|█████ | 5/10 [00:52<00:46, 9.36s/it, data_size=368, test_acc=0.87, train_acc=0.897] Test 4: Data size 368: : 60%|██████ | 6/10 [00:52<00:39, 9.77s/it, data_size=368, test_acc=0.87, train_acc=0.897]Test 4: Data size 400: : 60%|██████ | 6/10 [00:52<00:39, 9.77s/it, data_size=368, test_acc=0.87, train_acc=0.897]Test 4: Data size 400: : 60%|██████ | 6/10 [01:08<00:39, 9.77s/it, data_size=400, test_acc=0.873, train_acc=0.916]Test 4: Data size 400: : 70%|███████ | 7/10 [01:08<00:35, 11.72s/it, data_size=400, test_acc=0.873, train_acc=0.916]Test 4: Data size 432: : 70%|███████ | 7/10 [01:08<00:35, 11.72s/it, data_size=400, test_acc=0.873, train_acc=0.916]Test 4: Data size 432: : 70%|███████ | 7/10 [01:23<00:35, 11.72s/it, data_size=432, test_acc=0.88, train_acc=0.914] Test 4: Data size 432: : 80%|████████ | 8/10 [01:24<00:25, 12.96s/it, data_size=432, test_acc=0.88, train_acc=0.914]Test 4: Data size 464: : 80%|████████ | 8/10 [01:24<00:25, 12.96s/it, data_size=432, test_acc=0.88, train_acc=0.914]Test 4: Data size 464: : 80%|████████ | 8/10 [01:39<00:25, 12.96s/it, data_size=464, test_acc=0.882, train_acc=0.934]Test 4: Data size 464: : 90%|█████████ | 9/10 [01:39<00:13, 13.78s/it, data_size=464, test_acc=0.882, train_acc=0.934]Test 4: Data size 496: : 90%|█████████ | 9/10 [01:39<00:13, 13.78s/it, data_size=464, test_acc=0.882, train_acc=0.934]Test 4: Data size 496: : 90%|█████████ | 9/10 [01:54<00:13, 13.78s/it, data_size=496, test_acc=0.881, train_acc=0.921]Test 4: Data size 496: : 100%|██████████| 10/10 [01:55<00:00, 14.29s/it, data_size=496, test_acc=0.881, train_acc=0.921]Test 4: Data size 496: : 100%|██████████| 10/10 [01:55<00:00, 11.51s/it, data_size=496, test_acc=0.881, train_acc=0.921]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:05<?, ?it/s, data_size=208, test_acc=0.534, train_acc=0.548]Test 5: Data size 208: : 10%|█ | 1/10 [00:05<00:50, 5.57s/it, data_size=208, test_acc=0.534, train_acc=0.548]Test 5: Data size 240: : 10%|█ | 1/10 [00:05<00:50, 5.57s/it, data_size=208, test_acc=0.534, train_acc=0.548]Test 5: Data size 240: : 10%|█ | 1/10 [00:11<00:50, 5.57s/it, data_size=240, test_acc=0.751, train_acc=0.799]Test 5: Data size 240: : 20%|██ | 2/10 [00:11<00:44, 5.62s/it, data_size=240, test_acc=0.751, train_acc=0.799]Test 5: Data size 272: : 20%|██ | 2/10 [00:11<00:44, 5.62s/it, data_size=240, test_acc=0.751, train_acc=0.799]Test 5: Data size 272: : 20%|██ | 2/10 [00:21<00:44, 5.62s/it, data_size=272, test_acc=0.765, train_acc=0.787]Test 5: Data size 272: : 30%|███ | 3/10 [00:21<00:54, 7.82s/it, data_size=272, test_acc=0.765, train_acc=0.787]Test 5: Data size 304: : 30%|███ | 3/10 [00:21<00:54, 7.82s/it, data_size=272, test_acc=0.765, train_acc=0.787]Test 5: Data size 304: : 30%|███ | 3/10 [00:32<00:54, 7.82s/it, data_size=304, test_acc=0.84, train_acc=0.869] Test 5: Data size 304: : 40%|████ | 4/10 [00:32<00:53, 8.90s/it, data_size=304, test_acc=0.84, train_acc=0.869]Test 5: Data size 336: : 40%|████ | 4/10 [00:32<00:53, 8.90s/it, data_size=304, test_acc=0.84, train_acc=0.869]Test 5: Data size 336: : 40%|████ | 4/10 [00:42<00:53, 8.90s/it, data_size=336, test_acc=0.885, train_acc=0.936]Test 5: Data size 336: : 50%|█████ | 5/10 [00:42<00:47, 9.51s/it, data_size=336, test_acc=0.885, train_acc=0.936]Test 5: Data size 368: : 50%|█████ | 5/10 [00:42<00:47, 9.51s/it, data_size=336, test_acc=0.885, train_acc=0.936]Test 5: Data size 368: : 50%|█████ | 5/10 [00:53<00:47, 9.51s/it, data_size=368, test_acc=0.873, train_acc=0.946]Test 5: Data size 368: : 60%|██████ | 6/10 [00:53<00:39, 9.98s/it, data_size=368, test_acc=0.873, train_acc=0.946]Test 5: Data size 400: : 60%|██████ | 6/10 [00:53<00:39, 9.98s/it, data_size=368, test_acc=0.873, train_acc=0.946]Test 5: Data size 400: : 60%|██████ | 6/10 [01:09<00:39, 9.98s/it, data_size=400, test_acc=0.869, train_acc=0.92] Test 5: Data size 400: : 70%|███████ | 7/10 [01:09<00:35, 11.83s/it, data_size=400, test_acc=0.869, train_acc=0.92]Test 5: Data size 432: : 70%|███████ | 7/10 [01:09<00:35, 11.83s/it, data_size=400, test_acc=0.869, train_acc=0.92]Test 5: Data size 432: : 70%|███████ | 7/10 [01:24<00:35, 11.83s/it, data_size=432, test_acc=0.889, train_acc=0.916]Test 5: Data size 432: : 80%|████████ | 8/10 [01:24<00:26, 13.03s/it, data_size=432, test_acc=0.889, train_acc=0.916]Test 5: Data size 464: : 80%|████████ | 8/10 [01:24<00:26, 13.03s/it, data_size=432, test_acc=0.889, train_acc=0.916]Test 5: Data size 464: : 80%|████████ | 8/10 [01:40<00:26, 13.03s/it, data_size=464, test_acc=0.881, train_acc=0.924]Test 5: Data size 464: : 90%|█████████ | 9/10 [01:40<00:13, 13.81s/it, data_size=464, test_acc=0.881, train_acc=0.924]Test 5: Data size 496: : 90%|█████████ | 9/10 [01:40<00:13, 13.81s/it, data_size=464, test_acc=0.881, train_acc=0.924]Test 5: Data size 496: : 90%|█████████ | 9/10 [01:55<00:13, 13.81s/it, data_size=496, test_acc=0.881, train_acc=0.927]Test 5: Data size 496: : 100%|██████████| 10/10 [01:55<00:00, 14.22s/it, data_size=496, test_acc=0.881, train_acc=0.927]Test 5: Data size 496: : 100%|██████████| 10/10 [01:55<00:00, 11.56s/it, data_size=496, test_acc=0.881, train_acc=0.927]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:05<?, ?it/s, data_size=208, test_acc=0.497, train_acc=0.497]Test 6: Data size 208: : 10%|█ | 1/10 [00:05<00:50, 5.57s/it, data_size=208, test_acc=0.497, train_acc=0.497]Test 6: Data size 240: : 10%|█ | 1/10 [00:05<00:50, 5.57s/it, data_size=208, test_acc=0.497, train_acc=0.497]Test 6: Data size 240: : 10%|█ | 1/10 [00:11<00:50, 5.57s/it, data_size=240, test_acc=0.716, train_acc=0.736]Test 6: Data size 240: : 20%|██ | 2/10 [00:11<00:45, 5.63s/it, data_size=240, test_acc=0.716, train_acc=0.736]Test 6: Data size 272: : 20%|██ | 2/10 [00:11<00:45, 5.63s/it, data_size=240, test_acc=0.716, train_acc=0.736]Test 6: Data size 272: : 20%|██ | 2/10 [00:21<00:45, 5.63s/it, data_size=272, test_acc=0.749, train_acc=0.762]Test 6: Data size 272: : 30%|███ | 3/10 [00:21<00:54, 7.79s/it, data_size=272, test_acc=0.749, train_acc=0.762]Test 6: Data size 304: : 30%|███ | 3/10 [00:21<00:54, 7.79s/it, data_size=272, test_acc=0.749, train_acc=0.762]Test 6: Data size 304: : 30%|███ | 3/10 [00:31<00:54, 7.79s/it, data_size=304, test_acc=0.717, train_acc=0.757]Test 6: Data size 304: : 40%|████ | 4/10 [00:32<00:53, 8.86s/it, data_size=304, test_acc=0.717, train_acc=0.757]Test 6: Data size 336: : 40%|████ | 4/10 [00:32<00:53, 8.86s/it, data_size=304, test_acc=0.717, train_acc=0.757]Test 6: Data size 336: : 40%|████ | 4/10 [00:42<00:53, 8.86s/it, data_size=336, test_acc=0.755, train_acc=0.783]Test 6: Data size 336: : 50%|█████ | 5/10 [00:42<00:47, 9.44s/it, data_size=336, test_acc=0.755, train_acc=0.783]Test 6: Data size 368: : 50%|█████ | 5/10 [00:42<00:47, 9.44s/it, data_size=336, test_acc=0.755, train_acc=0.783]Test 6: Data size 368: : 50%|█████ | 5/10 [00:53<00:47, 9.44s/it, data_size=368, test_acc=0.813, train_acc=0.812]Test 6: Data size 368: : 60%|██████ | 6/10 [00:53<00:39, 9.87s/it, data_size=368, test_acc=0.813, train_acc=0.812]Test 6: Data size 400: : 60%|██████ | 6/10 [00:53<00:39, 9.87s/it, data_size=368, test_acc=0.813, train_acc=0.812]Test 6: Data size 400: : 60%|██████ | 6/10 [01:08<00:39, 9.87s/it, data_size=400, test_acc=0.817, train_acc=0.844]Test 6: Data size 400: : 70%|███████ | 7/10 [01:08<00:35, 11.69s/it, data_size=400, test_acc=0.817, train_acc=0.844]Test 6: Data size 432: : 70%|███████ | 7/10 [01:08<00:35, 11.69s/it, data_size=400, test_acc=0.817, train_acc=0.844]Test 6: Data size 432: : 70%|███████ | 7/10 [01:24<00:35, 11.69s/it, data_size=432, test_acc=0.846, train_acc=0.867]Test 6: Data size 432: : 80%|████████ | 8/10 [01:24<00:25, 12.88s/it, data_size=432, test_acc=0.846, train_acc=0.867]Test 6: Data size 464: : 80%|████████ | 8/10 [01:24<00:25, 12.88s/it, data_size=432, test_acc=0.846, train_acc=0.867]Test 6: Data size 464: : 80%|████████ | 8/10 [01:39<00:25, 12.88s/it, data_size=464, test_acc=0.88, train_acc=0.905] Test 6: Data size 464: : 90%|█████████ | 9/10 [01:39<00:13, 13.65s/it, data_size=464, test_acc=0.88, train_acc=0.905]Test 6: Data size 496: : 90%|█████████ | 9/10 [01:39<00:13, 13.65s/it, data_size=464, test_acc=0.88, train_acc=0.905]Test 6: Data size 496: : 90%|█████████ | 9/10 [01:55<00:13, 13.65s/it, data_size=496, test_acc=0.87, train_acc=0.92] Test 6: Data size 496: : 100%|██████████| 10/10 [01:55<00:00, 14.32s/it, data_size=496, test_acc=0.87, train_acc=0.92]Test 6: Data size 496: : 100%|██████████| 10/10 [01:55<00:00, 11.53s/it, data_size=496, test_acc=0.87, train_acc=0.92]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:05<?, ?it/s, data_size=208, test_acc=0.5, train_acc=0.5]Test 7: Data size 208: : 10%|█ | 1/10 [00:05<00:50, 5.56s/it, data_size=208, test_acc=0.5, train_acc=0.5]Test 7: Data size 240: : 10%|█ | 1/10 [00:05<00:50, 5.56s/it, data_size=208, test_acc=0.5, train_acc=0.5]Test 7: Data size 240: : 10%|█ | 1/10 [00:11<00:50, 5.56s/it, data_size=240, test_acc=0.619, train_acc=0.609]Test 7: Data size 240: : 20%|██ | 2/10 [00:11<00:44, 5.61s/it, data_size=240, test_acc=0.619, train_acc=0.609]Test 7: Data size 272: : 20%|██ | 2/10 [00:11<00:44, 5.61s/it, data_size=240, test_acc=0.619, train_acc=0.609]Test 7: Data size 272: : 20%|██ | 2/10 [00:21<00:44, 5.61s/it, data_size=272, test_acc=0.694, train_acc=0.681]Test 7: Data size 272: : 30%|███ | 3/10 [00:21<00:54, 7.78s/it, data_size=272, test_acc=0.694, train_acc=0.681]Test 7: Data size 304: : 30%|███ | 3/10 [00:21<00:54, 7.78s/it, data_size=272, test_acc=0.694, train_acc=0.681]Test 7: Data size 304: : 30%|███ | 3/10 [00:31<00:54, 7.78s/it, data_size=304, test_acc=0.85, train_acc=0.802] Test 7: Data size 304: : 40%|████ | 4/10 [00:32<00:53, 8.87s/it, data_size=304, test_acc=0.85, train_acc=0.802]Test 7: Data size 336: : 40%|████ | 4/10 [00:32<00:53, 8.87s/it, data_size=304, test_acc=0.85, train_acc=0.802]Test 7: Data size 336: : 40%|████ | 4/10 [00:42<00:53, 8.87s/it, data_size=336, test_acc=0.899, train_acc=0.884]Test 7: Data size 336: : 50%|█████ | 5/10 [00:42<00:47, 9.45s/it, data_size=336, test_acc=0.899, train_acc=0.884]Test 7: Data size 368: : 50%|█████ | 5/10 [00:42<00:47, 9.45s/it, data_size=336, test_acc=0.899, train_acc=0.884]Test 7: Data size 368: : 50%|█████ | 5/10 [00:53<00:47, 9.45s/it, data_size=368, test_acc=0.899, train_acc=0.89] Test 7: Data size 368: : 60%|██████ | 6/10 [00:53<00:39, 9.88s/it, data_size=368, test_acc=0.899, train_acc=0.89]Test 7: Data size 400: : 60%|██████ | 6/10 [00:53<00:39, 9.88s/it, data_size=368, test_acc=0.899, train_acc=0.89]Test 7: Data size 400: : 60%|██████ | 6/10 [01:08<00:39, 9.88s/it, data_size=400, test_acc=0.896, train_acc=0.87]Test 7: Data size 400: : 70%|███████ | 7/10 [01:08<00:35, 11.72s/it, data_size=400, test_acc=0.896, train_acc=0.87]Test 7: Data size 432: : 70%|███████ | 7/10 [01:08<00:35, 11.72s/it, data_size=400, test_acc=0.896, train_acc=0.87]Test 7: Data size 432: : 70%|███████ | 7/10 [01:24<00:35, 11.72s/it, data_size=432, test_acc=0.909, train_acc=0.901]Test 7: Data size 432: : 80%|████████ | 8/10 [01:24<00:26, 13.00s/it, data_size=432, test_acc=0.909, train_acc=0.901]Test 7: Data size 464: : 80%|████████ | 8/10 [01:24<00:26, 13.00s/it, data_size=432, test_acc=0.909, train_acc=0.901]Test 7: Data size 464: : 80%|████████ | 8/10 [01:39<00:26, 13.00s/it, data_size=464, test_acc=0.889, train_acc=0.871]Test 7: Data size 464: : 90%|█████████ | 9/10 [01:39<00:13, 13.75s/it, data_size=464, test_acc=0.889, train_acc=0.871]Test 7: Data size 496: : 90%|█████████ | 9/10 [01:39<00:13, 13.75s/it, data_size=464, test_acc=0.889, train_acc=0.871]Test 7: Data size 496: : 90%|█████████ | 9/10 [01:55<00:13, 13.75s/it, data_size=496, test_acc=0.894, train_acc=0.901]Test 7: Data size 496: : 100%|██████████| 10/10 [01:55<00:00, 14.37s/it, data_size=496, test_acc=0.894, train_acc=0.901]Test 7: Data size 496: : 100%|██████████| 10/10 [01:55<00:00, 11.57s/it, data_size=496, test_acc=0.894, train_acc=0.901]
working on model Multimodal-late-fusion-model-based-on-AlexNet with MIN_MAX
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:08<?, ?it/s, data_size=208, test_acc=0.489, train_acc=0.488]Test 0: Data size 208: : 10%|█ | 1/10 [00:09<01:21, 9.04s/it, data_size=208, test_acc=0.489, train_acc=0.488]Test 0: Data size 240: : 10%|█ | 1/10 [00:09<01:21, 9.04s/it, data_size=208, test_acc=0.489, train_acc=0.488]Test 0: Data size 240: : 10%|█ | 1/10 [00:18<01:21, 9.04s/it, data_size=240, test_acc=0.553, train_acc=0.626]Test 0: Data size 240: : 20%|██ | 2/10 [00:18<01:14, 9.37s/it, data_size=240, test_acc=0.553, train_acc=0.626]Test 0: Data size 272: : 20%|██ | 2/10 [00:18<01:14, 9.37s/it, data_size=240, test_acc=0.553, train_acc=0.626]Test 0: Data size 272: : 20%|██ | 2/10 [00:32<01:14, 9.37s/it, data_size=272, test_acc=0.76, train_acc=0.88] Test 0: Data size 272: : 30%|███ | 3/10 [00:33<01:21, 11.67s/it, data_size=272, test_acc=0.76, train_acc=0.88]Test 0: Data size 304: : 30%|███ | 3/10 [00:33<01:21, 11.67s/it, data_size=272, test_acc=0.76, train_acc=0.88]Test 0: Data size 304: : 30%|███ | 3/10 [00:47<01:21, 11.67s/it, data_size=304, test_acc=0.72, train_acc=0.807]Test 0: Data size 304: : 40%|████ | 4/10 [00:47<01:17, 12.88s/it, data_size=304, test_acc=0.72, train_acc=0.807]Test 0: Data size 336: : 40%|████ | 4/10 [00:47<01:17, 12.88s/it, data_size=304, test_acc=0.72, train_acc=0.807]Test 0: Data size 336: : 40%|████ | 4/10 [01:02<01:17, 12.88s/it, data_size=336, test_acc=0.746, train_acc=0.813]Test 0: Data size 336: : 50%|█████ | 5/10 [01:02<01:07, 13.43s/it, data_size=336, test_acc=0.746, train_acc=0.813]Test 0: Data size 368: : 50%|█████ | 5/10 [01:02<01:07, 13.43s/it, data_size=336, test_acc=0.746, train_acc=0.813]Test 0: Data size 368: : 50%|█████ | 5/10 [01:16<01:07, 13.43s/it, data_size=368, test_acc=0.826, train_acc=0.88] Test 0: Data size 368: : 60%|██████ | 6/10 [01:16<00:54, 13.62s/it, data_size=368, test_acc=0.826, train_acc=0.88]Test 0: Data size 400: : 60%|██████ | 6/10 [01:16<00:54, 13.62s/it, data_size=368, test_acc=0.826, train_acc=0.88]Test 0: Data size 400: : 60%|██████ | 6/10 [01:34<00:54, 13.62s/it, data_size=400, test_acc=0.865, train_acc=0.9] Test 0: Data size 400: : 70%|███████ | 7/10 [01:35<00:46, 15.34s/it, data_size=400, test_acc=0.865, train_acc=0.9]Test 0: Data size 432: : 70%|███████ | 7/10 [01:35<00:46, 15.34s/it, data_size=400, test_acc=0.865, train_acc=0.9]Test 0: Data size 432: : 70%|███████ | 7/10 [01:54<00:46, 15.34s/it, data_size=432, test_acc=0.884, train_acc=0.908]Test 0: Data size 432: : 80%|████████ | 8/10 [01:54<00:33, 16.64s/it, data_size=432, test_acc=0.884, train_acc=0.908]Test 0: Data size 464: : 80%|████████ | 8/10 [01:54<00:33, 16.64s/it, data_size=432, test_acc=0.884, train_acc=0.908]Test 0: Data size 464: : 80%|████████ | 8/10 [02:12<00:33, 16.64s/it, data_size=464, test_acc=0.886, train_acc=0.917]Test 0: Data size 464: : 90%|█████████ | 9/10 [02:12<00:17, 17.22s/it, data_size=464, test_acc=0.886, train_acc=0.917]Test 0: Data size 496: : 90%|█████████ | 9/10 [02:12<00:17, 17.22s/it, data_size=464, test_acc=0.886, train_acc=0.917]Test 0: Data size 496: : 90%|█████████ | 9/10 [02:31<00:17, 17.22s/it, data_size=496, test_acc=0.892, train_acc=0.926]Test 0: Data size 496: : 100%|██████████| 10/10 [02:31<00:00, 17.65s/it, data_size=496, test_acc=0.892, train_acc=0.926]Test 0: Data size 496: : 100%|██████████| 10/10 [02:31<00:00, 15.16s/it, data_size=496, test_acc=0.892, train_acc=0.926]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:09<?, ?it/s, data_size=208, test_acc=0.497, train_acc=0.49]Test 1: Data size 208: : 10%|█ | 1/10 [00:09<01:27, 9.74s/it, data_size=208, test_acc=0.497, train_acc=0.49]Test 1: Data size 240: : 10%|█ | 1/10 [00:09<01:27, 9.74s/it, data_size=208, test_acc=0.497, train_acc=0.49]Test 1: Data size 240: : 10%|█ | 1/10 [00:19<01:27, 9.74s/it, data_size=240, test_acc=0.636, train_acc=0.74]Test 1: Data size 240: : 20%|██ | 2/10 [00:19<01:18, 9.81s/it, data_size=240, test_acc=0.636, train_acc=0.74]Test 1: Data size 272: : 20%|██ | 2/10 [00:19<01:18, 9.81s/it, data_size=240, test_acc=0.636, train_acc=0.74]Test 1: Data size 272: : 20%|██ | 2/10 [00:34<01:18, 9.81s/it, data_size=272, test_acc=0.762, train_acc=0.802]Test 1: Data size 272: : 30%|███ | 3/10 [00:34<01:24, 12.11s/it, data_size=272, test_acc=0.762, train_acc=0.802]Test 1: Data size 304: : 30%|███ | 3/10 [00:34<01:24, 12.11s/it, data_size=272, test_acc=0.762, train_acc=0.802]Test 1: Data size 304: : 30%|███ | 3/10 [00:49<01:24, 12.11s/it, data_size=304, test_acc=0.775, train_acc=0.861]Test 1: Data size 304: : 40%|████ | 4/10 [00:49<01:18, 13.14s/it, data_size=304, test_acc=0.775, train_acc=0.861]Test 1: Data size 336: : 40%|████ | 4/10 [00:49<01:18, 13.14s/it, data_size=304, test_acc=0.775, train_acc=0.861]Test 1: Data size 336: : 40%|████ | 4/10 [01:03<01:18, 13.14s/it, data_size=336, test_acc=0.797, train_acc=0.836]Test 1: Data size 336: : 50%|█████ | 5/10 [01:03<01:08, 13.73s/it, data_size=336, test_acc=0.797, train_acc=0.836]Test 1: Data size 368: : 50%|█████ | 5/10 [01:03<01:08, 13.73s/it, data_size=336, test_acc=0.797, train_acc=0.836]Test 1: Data size 368: : 50%|█████ | 5/10 [01:18<01:08, 13.73s/it, data_size=368, test_acc=0.769, train_acc=0.83] Test 1: Data size 368: : 60%|██████ | 6/10 [01:18<00:55, 13.94s/it, data_size=368, test_acc=0.769, train_acc=0.83]Test 1: Data size 400: : 60%|██████ | 6/10 [01:18<00:55, 13.94s/it, data_size=368, test_acc=0.769, train_acc=0.83]Test 1: Data size 400: : 60%|██████ | 6/10 [01:37<00:55, 13.94s/it, data_size=400, test_acc=0.774, train_acc=0.834]Test 1: Data size 400: : 70%|███████ | 7/10 [01:37<00:46, 15.62s/it, data_size=400, test_acc=0.774, train_acc=0.834]Test 1: Data size 432: : 70%|███████ | 7/10 [01:37<00:46, 15.62s/it, data_size=400, test_acc=0.774, train_acc=0.834]Test 1: Data size 432: : 70%|███████ | 7/10 [01:56<00:46, 15.62s/it, data_size=432, test_acc=0.882, train_acc=0.896]Test 1: Data size 432: : 80%|████████ | 8/10 [01:56<00:33, 16.82s/it, data_size=432, test_acc=0.882, train_acc=0.896]Test 1: Data size 464: : 80%|████████ | 8/10 [01:56<00:33, 16.82s/it, data_size=432, test_acc=0.882, train_acc=0.896]Test 1: Data size 464: : 80%|████████ | 8/10 [02:16<00:33, 16.82s/it, data_size=464, test_acc=0.898, train_acc=0.907]Test 1: Data size 464: : 90%|█████████ | 9/10 [02:16<00:17, 17.79s/it, data_size=464, test_acc=0.898, train_acc=0.907]Test 1: Data size 496: : 90%|█████████ | 9/10 [02:16<00:17, 17.79s/it, data_size=464, test_acc=0.898, train_acc=0.907]Test 1: Data size 496: : 90%|█████████ | 9/10 [02:36<00:17, 17.79s/it, data_size=496, test_acc=0.904, train_acc=0.888]Test 1: Data size 496: : 100%|██████████| 10/10 [02:36<00:00, 18.45s/it, data_size=496, test_acc=0.904, train_acc=0.888]Test 1: Data size 496: : 100%|██████████| 10/10 [02:36<00:00, 15.66s/it, data_size=496, test_acc=0.904, train_acc=0.888]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:08<?, ?it/s, data_size=208, test_acc=0.497, train_acc=0.5]Test 2: Data size 208: : 10%|█ | 1/10 [00:08<01:20, 8.95s/it, data_size=208, test_acc=0.497, train_acc=0.5]Test 2: Data size 240: : 10%|█ | 1/10 [00:08<01:20, 8.95s/it, data_size=208, test_acc=0.497, train_acc=0.5]Test 2: Data size 240: : 10%|█ | 1/10 [00:17<01:20, 8.95s/it, data_size=240, test_acc=0.638, train_acc=0.748]Test 2: Data size 240: : 20%|██ | 2/10 [00:17<01:11, 8.96s/it, data_size=240, test_acc=0.638, train_acc=0.748]Test 2: Data size 272: : 20%|██ | 2/10 [00:17<01:11, 8.96s/it, data_size=240, test_acc=0.638, train_acc=0.748]Test 2: Data size 272: : 20%|██ | 2/10 [00:31<01:11, 8.96s/it, data_size=272, test_acc=0.684, train_acc=0.828]Test 2: Data size 272: : 30%|███ | 3/10 [00:31<01:18, 11.16s/it, data_size=272, test_acc=0.684, train_acc=0.828]Test 2: Data size 304: : 30%|███ | 3/10 [00:31<01:18, 11.16s/it, data_size=272, test_acc=0.684, train_acc=0.828]Test 2: Data size 304: : 30%|███ | 3/10 [00:45<01:18, 11.16s/it, data_size=304, test_acc=0.757, train_acc=0.87] Test 2: Data size 304: : 40%|████ | 4/10 [00:45<01:13, 12.25s/it, data_size=304, test_acc=0.757, train_acc=0.87]Test 2: Data size 336: : 40%|████ | 4/10 [00:45<01:13, 12.25s/it, data_size=304, test_acc=0.757, train_acc=0.87]Test 2: Data size 336: : 40%|████ | 4/10 [00:59<01:13, 12.25s/it, data_size=336, test_acc=0.754, train_acc=0.874]Test 2: Data size 336: : 50%|█████ | 5/10 [00:59<01:04, 12.88s/it, data_size=336, test_acc=0.754, train_acc=0.874]Test 2: Data size 368: : 50%|█████ | 5/10 [00:59<01:04, 12.88s/it, data_size=336, test_acc=0.754, train_acc=0.874]Test 2: Data size 368: : 50%|█████ | 5/10 [01:13<01:04, 12.88s/it, data_size=368, test_acc=0.75, train_acc=0.852] Test 2: Data size 368: : 60%|██████ | 6/10 [01:13<00:53, 13.29s/it, data_size=368, test_acc=0.75, train_acc=0.852]Test 2: Data size 400: : 60%|██████ | 6/10 [01:13<00:53, 13.29s/it, data_size=368, test_acc=0.75, train_acc=0.852]Test 2: Data size 400: : 60%|██████ | 6/10 [01:33<00:53, 13.29s/it, data_size=400, test_acc=0.768, train_acc=0.861]Test 2: Data size 400: : 70%|███████ | 7/10 [01:33<00:46, 15.34s/it, data_size=400, test_acc=0.768, train_acc=0.861]Test 2: Data size 432: : 70%|███████ | 7/10 [01:33<00:46, 15.34s/it, data_size=400, test_acc=0.768, train_acc=0.861]Test 2: Data size 432: : 70%|███████ | 7/10 [01:51<00:46, 15.34s/it, data_size=432, test_acc=0.743, train_acc=0.807]Test 2: Data size 432: : 80%|████████ | 8/10 [01:51<00:32, 16.42s/it, data_size=432, test_acc=0.743, train_acc=0.807]Test 2: Data size 464: : 80%|████████ | 8/10 [01:51<00:32, 16.42s/it, data_size=432, test_acc=0.743, train_acc=0.807]Test 2: Data size 464: : 80%|████████ | 8/10 [02:11<00:32, 16.42s/it, data_size=464, test_acc=0.76, train_acc=0.845] Test 2: Data size 464: : 90%|█████████ | 9/10 [02:11<00:17, 17.28s/it, data_size=464, test_acc=0.76, train_acc=0.845]Test 2: Data size 496: : 90%|█████████ | 9/10 [02:11<00:17, 17.28s/it, data_size=464, test_acc=0.76, train_acc=0.845]Test 2: Data size 496: : 90%|█████████ | 9/10 [02:30<00:17, 17.28s/it, data_size=496, test_acc=0.767, train_acc=0.865]Test 2: Data size 496: : 100%|██████████| 10/10 [02:30<00:00, 17.85s/it, data_size=496, test_acc=0.767, train_acc=0.865]Test 2: Data size 496: : 100%|██████████| 10/10 [02:30<00:00, 15.03s/it, data_size=496, test_acc=0.767, train_acc=0.865]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:09<?, ?it/s, data_size=208, test_acc=0.496, train_acc=0.489]Test 3: Data size 208: : 10%|█ | 1/10 [00:09<01:23, 9.30s/it, data_size=208, test_acc=0.496, train_acc=0.489]Test 3: Data size 240: : 10%|█ | 1/10 [00:09<01:23, 9.30s/it, data_size=208, test_acc=0.496, train_acc=0.489]Test 3: Data size 240: : 10%|█ | 1/10 [00:18<01:23, 9.30s/it, data_size=240, test_acc=0.732, train_acc=0.855]Test 3: Data size 240: : 20%|██ | 2/10 [00:18<01:15, 9.43s/it, data_size=240, test_acc=0.732, train_acc=0.855]Test 3: Data size 272: : 20%|██ | 2/10 [00:18<01:15, 9.43s/it, data_size=240, test_acc=0.732, train_acc=0.855]Test 3: Data size 272: : 20%|██ | 2/10 [00:33<01:15, 9.43s/it, data_size=272, test_acc=0.724, train_acc=0.8] Test 3: Data size 272: : 30%|███ | 3/10 [00:33<01:22, 11.72s/it, data_size=272, test_acc=0.724, train_acc=0.8]Test 3: Data size 304: : 30%|███ | 3/10 [00:33<01:22, 11.72s/it, data_size=272, test_acc=0.724, train_acc=0.8]Test 3: Data size 304: : 30%|███ | 3/10 [00:47<01:22, 11.72s/it, data_size=304, test_acc=0.866, train_acc=0.882]Test 3: Data size 304: : 40%|████ | 4/10 [00:47<01:17, 12.84s/it, data_size=304, test_acc=0.866, train_acc=0.882]Test 3: Data size 336: : 40%|████ | 4/10 [00:47<01:17, 12.84s/it, data_size=304, test_acc=0.866, train_acc=0.882]Test 3: Data size 336: : 40%|████ | 4/10 [01:02<01:17, 12.84s/it, data_size=336, test_acc=0.846, train_acc=0.836]Test 3: Data size 336: : 50%|█████ | 5/10 [01:02<01:07, 13.44s/it, data_size=336, test_acc=0.846, train_acc=0.836]Test 3: Data size 368: : 50%|█████ | 5/10 [01:02<01:07, 13.44s/it, data_size=336, test_acc=0.846, train_acc=0.836]Test 3: Data size 368: : 50%|█████ | 5/10 [01:16<01:07, 13.44s/it, data_size=368, test_acc=0.879, train_acc=0.906]Test 3: Data size 368: : 60%|██████ | 6/10 [01:16<00:55, 13.76s/it, data_size=368, test_acc=0.879, train_acc=0.906]Test 3: Data size 400: : 60%|██████ | 6/10 [01:16<00:55, 13.76s/it, data_size=368, test_acc=0.879, train_acc=0.906]Test 3: Data size 400: : 60%|██████ | 6/10 [01:35<00:55, 13.76s/it, data_size=400, test_acc=0.89, train_acc=0.868] Test 3: Data size 400: : 70%|███████ | 7/10 [01:35<00:46, 15.44s/it, data_size=400, test_acc=0.89, train_acc=0.868]Test 3: Data size 432: : 70%|███████ | 7/10 [01:35<00:46, 15.44s/it, data_size=400, test_acc=0.89, train_acc=0.868]Test 3: Data size 432: : 70%|███████ | 7/10 [01:54<00:46, 15.44s/it, data_size=432, test_acc=0.895, train_acc=0.895]Test 3: Data size 432: : 80%|████████ | 8/10 [01:54<00:33, 16.60s/it, data_size=432, test_acc=0.895, train_acc=0.895]Test 3: Data size 464: : 80%|████████ | 8/10 [01:54<00:33, 16.60s/it, data_size=432, test_acc=0.895, train_acc=0.895]Test 3: Data size 464: : 80%|████████ | 8/10 [02:13<00:33, 16.60s/it, data_size=464, test_acc=0.914, train_acc=0.923]Test 3: Data size 464: : 90%|█████████ | 9/10 [02:13<00:17, 17.23s/it, data_size=464, test_acc=0.914, train_acc=0.923]Test 3: Data size 496: : 90%|█████████ | 9/10 [02:13<00:17, 17.23s/it, data_size=464, test_acc=0.914, train_acc=0.923]Test 3: Data size 496: : 90%|█████████ | 9/10 [02:32<00:17, 17.23s/it, data_size=496, test_acc=0.915, train_acc=0.907]Test 3: Data size 496: : 100%|██████████| 10/10 [02:32<00:00, 17.76s/it, data_size=496, test_acc=0.915, train_acc=0.907]Test 3: Data size 496: : 100%|██████████| 10/10 [02:32<00:00, 15.22s/it, data_size=496, test_acc=0.915, train_acc=0.907]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:09<?, ?it/s, data_size=208, test_acc=0.493, train_acc=0.493]Test 4: Data size 208: : 10%|█ | 1/10 [00:09<01:22, 9.19s/it, data_size=208, test_acc=0.493, train_acc=0.493]Test 4: Data size 240: : 10%|█ | 1/10 [00:09<01:22, 9.19s/it, data_size=208, test_acc=0.493, train_acc=0.493]Test 4: Data size 240: : 10%|█ | 1/10 [00:18<01:22, 9.19s/it, data_size=240, test_acc=0.653, train_acc=0.724]Test 4: Data size 240: : 20%|██ | 2/10 [00:18<01:13, 9.23s/it, data_size=240, test_acc=0.653, train_acc=0.724]Test 4: Data size 272: : 20%|██ | 2/10 [00:18<01:13, 9.23s/it, data_size=240, test_acc=0.653, train_acc=0.724]Test 4: Data size 272: : 20%|██ | 2/10 [00:32<01:13, 9.23s/it, data_size=272, test_acc=0.746, train_acc=0.831]Test 4: Data size 272: : 30%|███ | 3/10 [00:32<01:21, 11.59s/it, data_size=272, test_acc=0.746, train_acc=0.831]Test 4: Data size 304: : 30%|███ | 3/10 [00:32<01:21, 11.59s/it, data_size=272, test_acc=0.746, train_acc=0.831]Test 4: Data size 304: : 30%|███ | 3/10 [00:46<01:21, 11.59s/it, data_size=304, test_acc=0.857, train_acc=0.89] Test 4: Data size 304: : 40%|████ | 4/10 [00:47<01:15, 12.63s/it, data_size=304, test_acc=0.857, train_acc=0.89]Test 4: Data size 336: : 40%|████ | 4/10 [00:47<01:15, 12.63s/it, data_size=304, test_acc=0.857, train_acc=0.89]Test 4: Data size 336: : 40%|████ | 4/10 [01:01<01:15, 12.63s/it, data_size=336, test_acc=0.883, train_acc=0.864]Test 4: Data size 336: : 50%|█████ | 5/10 [01:01<01:06, 13.21s/it, data_size=336, test_acc=0.883, train_acc=0.864]Test 4: Data size 368: : 50%|█████ | 5/10 [01:01<01:06, 13.21s/it, data_size=336, test_acc=0.883, train_acc=0.864]Test 4: Data size 368: : 50%|█████ | 5/10 [01:15<01:06, 13.21s/it, data_size=368, test_acc=0.899, train_acc=0.879]Test 4: Data size 368: : 60%|██████ | 6/10 [01:15<00:53, 13.50s/it, data_size=368, test_acc=0.899, train_acc=0.879]Test 4: Data size 400: : 60%|██████ | 6/10 [01:15<00:53, 13.50s/it, data_size=368, test_acc=0.899, train_acc=0.879]Test 4: Data size 400: : 60%|██████ | 6/10 [01:34<00:53, 13.50s/it, data_size=400, test_acc=0.882, train_acc=0.898]Test 4: Data size 400: : 70%|███████ | 7/10 [01:34<00:46, 15.34s/it, data_size=400, test_acc=0.882, train_acc=0.898]Test 4: Data size 432: : 70%|███████ | 7/10 [01:34<00:46, 15.34s/it, data_size=400, test_acc=0.882, train_acc=0.898]Test 4: Data size 432: : 70%|███████ | 7/10 [01:53<00:46, 15.34s/it, data_size=432, test_acc=0.89, train_acc=0.908] Test 4: Data size 432: : 80%|████████ | 8/10 [01:53<00:33, 16.56s/it, data_size=432, test_acc=0.89, train_acc=0.908]Test 4: Data size 464: : 80%|████████ | 8/10 [01:53<00:33, 16.56s/it, data_size=432, test_acc=0.89, train_acc=0.908]Test 4: Data size 464: : 80%|████████ | 8/10 [02:12<00:33, 16.56s/it, data_size=464, test_acc=0.886, train_acc=0.87]Test 4: Data size 464: : 90%|█████████ | 9/10 [02:12<00:17, 17.33s/it, data_size=464, test_acc=0.886, train_acc=0.87]Test 4: Data size 496: : 90%|█████████ | 9/10 [02:12<00:17, 17.33s/it, data_size=464, test_acc=0.886, train_acc=0.87]Test 4: Data size 496: : 90%|█████████ | 9/10 [02:31<00:17, 17.33s/it, data_size=496, test_acc=0.899, train_acc=0.905]Test 4: Data size 496: : 100%|██████████| 10/10 [02:31<00:00, 17.85s/it, data_size=496, test_acc=0.899, train_acc=0.905]Test 4: Data size 496: : 100%|██████████| 10/10 [02:31<00:00, 15.17s/it, data_size=496, test_acc=0.899, train_acc=0.905]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:09<?, ?it/s, data_size=208, test_acc=0.498, train_acc=0.5]Test 5: Data size 208: : 10%|█ | 1/10 [00:09<01:24, 9.36s/it, data_size=208, test_acc=0.498, train_acc=0.5]Test 5: Data size 240: : 10%|█ | 1/10 [00:09<01:24, 9.36s/it, data_size=208, test_acc=0.498, train_acc=0.5]Test 5: Data size 240: : 10%|█ | 1/10 [00:18<01:24, 9.36s/it, data_size=240, test_acc=0.712, train_acc=0.849]Test 5: Data size 240: : 20%|██ | 2/10 [00:18<01:15, 9.44s/it, data_size=240, test_acc=0.712, train_acc=0.849]Test 5: Data size 272: : 20%|██ | 2/10 [00:18<01:15, 9.44s/it, data_size=240, test_acc=0.712, train_acc=0.849]Test 5: Data size 272: : 20%|██ | 2/10 [00:33<01:15, 9.44s/it, data_size=272, test_acc=0.764, train_acc=0.899]Test 5: Data size 272: : 30%|███ | 3/10 [00:33<01:22, 11.78s/it, data_size=272, test_acc=0.764, train_acc=0.899]Test 5: Data size 304: : 30%|███ | 3/10 [00:33<01:22, 11.78s/it, data_size=272, test_acc=0.764, train_acc=0.899]Test 5: Data size 304: : 30%|███ | 3/10 [00:47<01:22, 11.78s/it, data_size=304, test_acc=0.766, train_acc=0.898]Test 5: Data size 304: : 40%|████ | 4/10 [00:47<01:16, 12.81s/it, data_size=304, test_acc=0.766, train_acc=0.898]Test 5: Data size 336: : 40%|████ | 4/10 [00:47<01:16, 12.81s/it, data_size=304, test_acc=0.766, train_acc=0.898]Test 5: Data size 336: : 40%|████ | 4/10 [01:02<01:16, 12.81s/it, data_size=336, test_acc=0.839, train_acc=0.865]Test 5: Data size 336: : 50%|█████ | 5/10 [01:02<01:07, 13.42s/it, data_size=336, test_acc=0.839, train_acc=0.865]Test 5: Data size 368: : 50%|█████ | 5/10 [01:02<01:07, 13.42s/it, data_size=336, test_acc=0.839, train_acc=0.865]Test 5: Data size 368: : 50%|█████ | 5/10 [01:16<01:07, 13.42s/it, data_size=368, test_acc=0.865, train_acc=0.914]Test 5: Data size 368: : 60%|██████ | 6/10 [01:16<00:55, 13.77s/it, data_size=368, test_acc=0.865, train_acc=0.914]Test 5: Data size 400: : 60%|██████ | 6/10 [01:16<00:55, 13.77s/it, data_size=368, test_acc=0.865, train_acc=0.914]Test 5: Data size 400: : 60%|██████ | 6/10 [01:35<00:55, 13.77s/it, data_size=400, test_acc=0.89, train_acc=0.924] Test 5: Data size 400: : 70%|███████ | 7/10 [01:35<00:46, 15.54s/it, data_size=400, test_acc=0.89, train_acc=0.924]Test 5: Data size 432: : 70%|███████ | 7/10 [01:35<00:46, 15.54s/it, data_size=400, test_acc=0.89, train_acc=0.924]Test 5: Data size 432: : 70%|███████ | 7/10 [01:55<00:46, 15.54s/it, data_size=432, test_acc=0.863, train_acc=0.879]Test 5: Data size 432: : 80%|████████ | 8/10 [01:55<00:33, 16.73s/it, data_size=432, test_acc=0.863, train_acc=0.879]Test 5: Data size 464: : 80%|████████ | 8/10 [01:55<00:33, 16.73s/it, data_size=432, test_acc=0.863, train_acc=0.879]Test 5: Data size 464: : 80%|████████ | 8/10 [02:14<00:33, 16.73s/it, data_size=464, test_acc=0.875, train_acc=0.937]Test 5: Data size 464: : 90%|█████████ | 9/10 [02:14<00:17, 17.60s/it, data_size=464, test_acc=0.875, train_acc=0.937]Test 5: Data size 496: : 90%|█████████ | 9/10 [02:14<00:17, 17.60s/it, data_size=464, test_acc=0.875, train_acc=0.937]Test 5: Data size 496: : 90%|█████████ | 9/10 [02:34<00:17, 17.60s/it, data_size=496, test_acc=0.882, train_acc=0.927]Test 5: Data size 496: : 100%|██████████| 10/10 [02:34<00:00, 18.27s/it, data_size=496, test_acc=0.882, train_acc=0.927]Test 5: Data size 496: : 100%|██████████| 10/10 [02:34<00:00, 15.45s/it, data_size=496, test_acc=0.882, train_acc=0.927]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:09<?, ?it/s, data_size=208, test_acc=0.498, train_acc=0.497]Test 6: Data size 208: : 10%|█ | 1/10 [00:09<01:25, 9.49s/it, data_size=208, test_acc=0.498, train_acc=0.497]Test 6: Data size 240: : 10%|█ | 1/10 [00:09<01:25, 9.49s/it, data_size=208, test_acc=0.498, train_acc=0.497]Test 6: Data size 240: : 10%|█ | 1/10 [00:18<01:25, 9.49s/it, data_size=240, test_acc=0.554, train_acc=0.639]Test 6: Data size 240: : 20%|██ | 2/10 [00:18<01:15, 9.47s/it, data_size=240, test_acc=0.554, train_acc=0.639]Test 6: Data size 272: : 20%|██ | 2/10 [00:18<01:15, 9.47s/it, data_size=240, test_acc=0.554, train_acc=0.639]Test 6: Data size 272: : 20%|██ | 2/10 [00:33<01:15, 9.47s/it, data_size=272, test_acc=0.659, train_acc=0.78] Test 6: Data size 272: : 30%|███ | 3/10 [00:33<01:21, 11.66s/it, data_size=272, test_acc=0.659, train_acc=0.78]Test 6: Data size 304: : 30%|███ | 3/10 [00:33<01:21, 11.66s/it, data_size=272, test_acc=0.659, train_acc=0.78]Test 6: Data size 304: : 30%|███ | 3/10 [00:47<01:21, 11.66s/it, data_size=304, test_acc=0.733, train_acc=0.848]Test 6: Data size 304: : 40%|████ | 4/10 [00:47<01:16, 12.80s/it, data_size=304, test_acc=0.733, train_acc=0.848]Test 6: Data size 336: : 40%|████ | 4/10 [00:47<01:16, 12.80s/it, data_size=304, test_acc=0.733, train_acc=0.848]Test 6: Data size 336: : 40%|████ | 4/10 [01:02<01:16, 12.80s/it, data_size=336, test_acc=0.74, train_acc=0.877] Test 6: Data size 336: : 50%|█████ | 5/10 [01:02<01:06, 13.38s/it, data_size=336, test_acc=0.74, train_acc=0.877]Test 6: Data size 368: : 50%|█████ | 5/10 [01:02<01:06, 13.38s/it, data_size=336, test_acc=0.74, train_acc=0.877]Test 6: Data size 368: : 50%|█████ | 5/10 [01:16<01:06, 13.38s/it, data_size=368, test_acc=0.744, train_acc=0.863]Test 6: Data size 368: : 60%|██████ | 6/10 [01:16<00:54, 13.69s/it, data_size=368, test_acc=0.744, train_acc=0.863]Test 6: Data size 400: : 60%|██████ | 6/10 [01:16<00:54, 13.69s/it, data_size=368, test_acc=0.744, train_acc=0.863]Test 6: Data size 400: : 60%|██████ | 6/10 [01:35<00:54, 13.69s/it, data_size=400, test_acc=0.722, train_acc=0.827]Test 6: Data size 400: : 70%|███████ | 7/10 [01:35<00:45, 15.33s/it, data_size=400, test_acc=0.722, train_acc=0.827]Test 6: Data size 432: : 70%|███████ | 7/10 [01:35<00:45, 15.33s/it, data_size=400, test_acc=0.722, train_acc=0.827]Test 6: Data size 432: : 70%|███████ | 7/10 [01:54<00:45, 15.33s/it, data_size=432, test_acc=0.873, train_acc=0.912]Test 6: Data size 432: : 80%|████████ | 8/10 [01:54<00:33, 16.66s/it, data_size=432, test_acc=0.873, train_acc=0.912]Test 6: Data size 464: : 80%|████████ | 8/10 [01:54<00:33, 16.66s/it, data_size=432, test_acc=0.873, train_acc=0.912]Test 6: Data size 464: : 80%|████████ | 8/10 [02:13<00:33, 16.66s/it, data_size=464, test_acc=0.901, train_acc=0.924]Test 6: Data size 464: : 90%|█████████ | 9/10 [02:13<00:17, 17.31s/it, data_size=464, test_acc=0.901, train_acc=0.924]Test 6: Data size 496: : 90%|█████████ | 9/10 [02:13<00:17, 17.31s/it, data_size=464, test_acc=0.901, train_acc=0.924]Test 6: Data size 496: : 90%|█████████ | 9/10 [02:32<00:17, 17.31s/it, data_size=496, test_acc=0.853, train_acc=0.863]Test 6: Data size 496: : 100%|██████████| 10/10 [02:32<00:00, 17.96s/it, data_size=496, test_acc=0.853, train_acc=0.863]Test 6: Data size 496: : 100%|██████████| 10/10 [02:32<00:00, 15.28s/it, data_size=496, test_acc=0.853, train_acc=0.863]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:09<?, ?it/s, data_size=208, test_acc=0.566, train_acc=0.57]Test 7: Data size 208: : 10%|█ | 1/10 [00:09<01:22, 9.16s/it, data_size=208, test_acc=0.566, train_acc=0.57]Test 7: Data size 240: : 10%|█ | 1/10 [00:09<01:22, 9.16s/it, data_size=208, test_acc=0.566, train_acc=0.57]Test 7: Data size 240: : 10%|█ | 1/10 [00:18<01:22, 9.16s/it, data_size=240, test_acc=0.715, train_acc=0.823]Test 7: Data size 240: : 20%|██ | 2/10 [00:18<01:14, 9.35s/it, data_size=240, test_acc=0.715, train_acc=0.823]Test 7: Data size 272: : 20%|██ | 2/10 [00:18<01:14, 9.35s/it, data_size=240, test_acc=0.715, train_acc=0.823]Test 7: Data size 272: : 20%|██ | 2/10 [00:32<01:14, 9.35s/it, data_size=272, test_acc=0.748, train_acc=0.831]Test 7: Data size 272: : 30%|███ | 3/10 [00:32<01:19, 11.37s/it, data_size=272, test_acc=0.748, train_acc=0.831]Test 7: Data size 304: : 30%|███ | 3/10 [00:32<01:19, 11.37s/it, data_size=272, test_acc=0.748, train_acc=0.831]Test 7: Data size 304: : 30%|███ | 3/10 [00:46<01:19, 11.37s/it, data_size=304, test_acc=0.743, train_acc=0.834]Test 7: Data size 304: : 40%|████ | 4/10 [00:46<01:14, 12.50s/it, data_size=304, test_acc=0.743, train_acc=0.834]Test 7: Data size 336: : 40%|████ | 4/10 [00:46<01:14, 12.50s/it, data_size=304, test_acc=0.743, train_acc=0.834]Test 7: Data size 336: : 40%|████ | 4/10 [01:00<01:14, 12.50s/it, data_size=336, test_acc=0.745, train_acc=0.827]Test 7: Data size 336: : 50%|█████ | 5/10 [01:00<01:05, 13.12s/it, data_size=336, test_acc=0.745, train_acc=0.827]Test 7: Data size 368: : 50%|█████ | 5/10 [01:00<01:05, 13.12s/it, data_size=336, test_acc=0.745, train_acc=0.827]Test 7: Data size 368: : 50%|█████ | 5/10 [01:14<01:05, 13.12s/it, data_size=368, test_acc=0.728, train_acc=0.786]Test 7: Data size 368: : 60%|██████ | 6/10 [01:14<00:52, 13.24s/it, data_size=368, test_acc=0.728, train_acc=0.786]Test 7: Data size 400: : 60%|██████ | 6/10 [01:14<00:52, 13.24s/it, data_size=368, test_acc=0.728, train_acc=0.786]Test 7: Data size 400: : 60%|██████ | 6/10 [01:32<00:52, 13.24s/it, data_size=400, test_acc=0.858, train_acc=0.873]Test 7: Data size 400: : 70%|███████ | 7/10 [01:32<00:44, 14.85s/it, data_size=400, test_acc=0.858, train_acc=0.873]Test 7: Data size 432: : 70%|███████ | 7/10 [01:32<00:44, 14.85s/it, data_size=400, test_acc=0.858, train_acc=0.873]Test 7: Data size 432: : 70%|███████ | 7/10 [01:50<00:44, 14.85s/it, data_size=432, test_acc=0.882, train_acc=0.889]Test 7: Data size 432: : 80%|████████ | 8/10 [01:50<00:31, 15.89s/it, data_size=432, test_acc=0.882, train_acc=0.889]Test 7: Data size 464: : 80%|████████ | 8/10 [01:50<00:31, 15.89s/it, data_size=432, test_acc=0.882, train_acc=0.889]Test 7: Data size 464: : 80%|████████ | 8/10 [02:09<00:31, 15.89s/it, data_size=464, test_acc=0.873, train_acc=0.856]Test 7: Data size 464: : 90%|█████████ | 9/10 [02:09<00:16, 16.80s/it, data_size=464, test_acc=0.873, train_acc=0.856]Test 7: Data size 496: : 90%|█████████ | 9/10 [02:09<00:16, 16.80s/it, data_size=464, test_acc=0.873, train_acc=0.856]Test 7: Data size 496: : 90%|█████████ | 9/10 [02:27<00:16, 16.80s/it, data_size=496, test_acc=0.914, train_acc=0.92] Test 7: Data size 496: : 100%|██████████| 10/10 [02:27<00:00, 17.27s/it, data_size=496, test_acc=0.914, train_acc=0.92]Test 7: Data size 496: : 100%|██████████| 10/10 [02:27<00:00, 14.78s/it, data_size=496, test_acc=0.914, train_acc=0.92]
working on model Multimodal-late-fusion-model-based-on-AlexNet with MIN_MARGIN
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:09<?, ?it/s, data_size=208, test_acc=0.492, train_acc=0.492]Test 0: Data size 208: : 10%|█ | 1/10 [00:09<01:27, 9.76s/it, data_size=208, test_acc=0.492, train_acc=0.492]Test 0: Data size 240: : 10%|█ | 1/10 [00:09<01:27, 9.76s/it, data_size=208, test_acc=0.492, train_acc=0.492]Test 0: Data size 240: : 10%|█ | 1/10 [00:19<01:27, 9.76s/it, data_size=240, test_acc=0.751, train_acc=0.803]Test 0: Data size 240: : 20%|██ | 2/10 [00:19<01:17, 9.63s/it, data_size=240, test_acc=0.751, train_acc=0.803]Test 0: Data size 272: : 20%|██ | 2/10 [00:19<01:17, 9.63s/it, data_size=240, test_acc=0.751, train_acc=0.803]Test 0: Data size 272: : 20%|██ | 2/10 [00:33<01:17, 9.63s/it, data_size=272, test_acc=0.747, train_acc=0.788]Test 0: Data size 272: : 30%|███ | 3/10 [00:33<01:22, 11.83s/it, data_size=272, test_acc=0.747, train_acc=0.788]Test 0: Data size 304: : 30%|███ | 3/10 [00:33<01:22, 11.83s/it, data_size=272, test_acc=0.747, train_acc=0.788]Test 0: Data size 304: : 30%|███ | 3/10 [00:48<01:22, 11.83s/it, data_size=304, test_acc=0.804, train_acc=0.813]Test 0: Data size 304: : 40%|████ | 4/10 [00:48<01:17, 12.93s/it, data_size=304, test_acc=0.804, train_acc=0.813]Test 0: Data size 336: : 40%|████ | 4/10 [00:48<01:17, 12.93s/it, data_size=304, test_acc=0.804, train_acc=0.813]Test 0: Data size 336: : 40%|████ | 4/10 [01:02<01:17, 12.93s/it, data_size=336, test_acc=0.846, train_acc=0.857]Test 0: Data size 336: : 50%|█████ | 5/10 [01:02<01:07, 13.50s/it, data_size=336, test_acc=0.846, train_acc=0.857]Test 0: Data size 368: : 50%|█████ | 5/10 [01:02<01:07, 13.50s/it, data_size=336, test_acc=0.846, train_acc=0.857]Test 0: Data size 368: : 50%|█████ | 5/10 [01:17<01:07, 13.50s/it, data_size=368, test_acc=0.846, train_acc=0.841]Test 0: Data size 368: : 60%|██████ | 6/10 [01:17<00:55, 13.79s/it, data_size=368, test_acc=0.846, train_acc=0.841]Test 0: Data size 400: : 60%|██████ | 6/10 [01:17<00:55, 13.79s/it, data_size=368, test_acc=0.846, train_acc=0.841]Test 0: Data size 400: : 60%|██████ | 6/10 [01:36<00:55, 13.79s/it, data_size=400, test_acc=0.879, train_acc=0.86] Test 0: Data size 400: : 70%|███████ | 7/10 [01:36<00:46, 15.57s/it, data_size=400, test_acc=0.879, train_acc=0.86]Test 0: Data size 432: : 70%|███████ | 7/10 [01:36<00:46, 15.57s/it, data_size=400, test_acc=0.879, train_acc=0.86]Test 0: Data size 432: : 70%|███████ | 7/10 [01:55<00:46, 15.57s/it, data_size=432, test_acc=0.838, train_acc=0.852]Test 0: Data size 432: : 80%|████████ | 8/10 [01:55<00:33, 16.71s/it, data_size=432, test_acc=0.838, train_acc=0.852]Test 0: Data size 464: : 80%|████████ | 8/10 [01:55<00:33, 16.71s/it, data_size=432, test_acc=0.838, train_acc=0.852]Test 0: Data size 464: : 80%|████████ | 8/10 [02:14<00:33, 16.71s/it, data_size=464, test_acc=0.878, train_acc=0.856]Test 0: Data size 464: : 90%|█████████ | 9/10 [02:14<00:17, 17.32s/it, data_size=464, test_acc=0.878, train_acc=0.856]Test 0: Data size 496: : 90%|█████████ | 9/10 [02:14<00:17, 17.32s/it, data_size=464, test_acc=0.878, train_acc=0.856]Test 0: Data size 496: : 90%|█████████ | 9/10 [02:33<00:17, 17.32s/it, data_size=496, test_acc=0.885, train_acc=0.885]Test 0: Data size 496: : 100%|██████████| 10/10 [02:33<00:00, 17.84s/it, data_size=496, test_acc=0.885, train_acc=0.885]Test 0: Data size 496: : 100%|██████████| 10/10 [02:33<00:00, 15.33s/it, data_size=496, test_acc=0.885, train_acc=0.885]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:09<?, ?it/s, data_size=208, test_acc=0.498, train_acc=0.49]Test 1: Data size 208: : 10%|█ | 1/10 [00:09<01:25, 9.53s/it, data_size=208, test_acc=0.498, train_acc=0.49]Test 1: Data size 240: : 10%|█ | 1/10 [00:09<01:25, 9.53s/it, data_size=208, test_acc=0.498, train_acc=0.49]Test 1: Data size 240: : 10%|█ | 1/10 [00:19<01:25, 9.53s/it, data_size=240, test_acc=0.721, train_acc=0.731]Test 1: Data size 240: : 20%|██ | 2/10 [00:19<01:16, 9.59s/it, data_size=240, test_acc=0.721, train_acc=0.731]Test 1: Data size 272: : 20%|██ | 2/10 [00:19<01:16, 9.59s/it, data_size=240, test_acc=0.721, train_acc=0.731]Test 1: Data size 272: : 20%|██ | 2/10 [00:33<01:16, 9.59s/it, data_size=272, test_acc=0.771, train_acc=0.815]Test 1: Data size 272: : 30%|███ | 3/10 [00:33<01:22, 11.74s/it, data_size=272, test_acc=0.771, train_acc=0.815]Test 1: Data size 304: : 30%|███ | 3/10 [00:33<01:22, 11.74s/it, data_size=272, test_acc=0.771, train_acc=0.815]Test 1: Data size 304: : 30%|███ | 3/10 [00:47<01:22, 11.74s/it, data_size=304, test_acc=0.773, train_acc=0.795]Test 1: Data size 304: : 40%|████ | 4/10 [00:47<01:16, 12.83s/it, data_size=304, test_acc=0.773, train_acc=0.795]Test 1: Data size 336: : 40%|████ | 4/10 [00:47<01:16, 12.83s/it, data_size=304, test_acc=0.773, train_acc=0.795]Test 1: Data size 336: : 40%|████ | 4/10 [01:02<01:16, 12.83s/it, data_size=336, test_acc=0.892, train_acc=0.882]Test 1: Data size 336: : 50%|█████ | 5/10 [01:02<01:07, 13.43s/it, data_size=336, test_acc=0.892, train_acc=0.882]Test 1: Data size 368: : 50%|█████ | 5/10 [01:02<01:07, 13.43s/it, data_size=336, test_acc=0.892, train_acc=0.882]Test 1: Data size 368: : 50%|█████ | 5/10 [01:16<01:07, 13.43s/it, data_size=368, test_acc=0.911, train_acc=0.869]Test 1: Data size 368: : 60%|██████ | 6/10 [01:16<00:54, 13.59s/it, data_size=368, test_acc=0.911, train_acc=0.869]Test 1: Data size 400: : 60%|██████ | 6/10 [01:16<00:54, 13.59s/it, data_size=368, test_acc=0.911, train_acc=0.869]Test 1: Data size 400: : 60%|██████ | 6/10 [01:34<00:54, 13.59s/it, data_size=400, test_acc=0.905, train_acc=0.873]Test 1: Data size 400: : 70%|███████ | 7/10 [01:35<00:45, 15.27s/it, data_size=400, test_acc=0.905, train_acc=0.873]Test 1: Data size 432: : 70%|███████ | 7/10 [01:35<00:45, 15.27s/it, data_size=400, test_acc=0.905, train_acc=0.873]Test 1: Data size 432: : 70%|███████ | 7/10 [01:54<00:45, 15.27s/it, data_size=432, test_acc=0.901, train_acc=0.87] Test 1: Data size 432: : 80%|████████ | 8/10 [01:54<00:33, 16.50s/it, data_size=432, test_acc=0.901, train_acc=0.87]Test 1: Data size 464: : 80%|████████ | 8/10 [01:54<00:33, 16.50s/it, data_size=432, test_acc=0.901, train_acc=0.87]Test 1: Data size 464: : 80%|████████ | 8/10 [02:12<00:33, 16.50s/it, data_size=464, test_acc=0.923, train_acc=0.881]Test 1: Data size 464: : 90%|█████████ | 9/10 [02:12<00:17, 17.11s/it, data_size=464, test_acc=0.923, train_acc=0.881]Test 1: Data size 496: : 90%|█████████ | 9/10 [02:12<00:17, 17.11s/it, data_size=464, test_acc=0.923, train_acc=0.881]Test 1: Data size 496: : 90%|█████████ | 9/10 [02:31<00:17, 17.11s/it, data_size=496, test_acc=0.918, train_acc=0.877]Test 1: Data size 496: : 100%|██████████| 10/10 [02:31<00:00, 17.63s/it, data_size=496, test_acc=0.918, train_acc=0.877]Test 1: Data size 496: : 100%|██████████| 10/10 [02:31<00:00, 15.15s/it, data_size=496, test_acc=0.918, train_acc=0.877]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:08<?, ?it/s, data_size=208, test_acc=0.497, train_acc=0.5]Test 2: Data size 208: : 10%|█ | 1/10 [00:08<01:18, 8.74s/it, data_size=208, test_acc=0.497, train_acc=0.5]Test 2: Data size 240: : 10%|█ | 1/10 [00:08<01:18, 8.74s/it, data_size=208, test_acc=0.497, train_acc=0.5]Test 2: Data size 240: : 10%|█ | 1/10 [00:17<01:18, 8.74s/it, data_size=240, test_acc=0.537, train_acc=0.641]Test 2: Data size 240: : 20%|██ | 2/10 [00:17<01:10, 8.79s/it, data_size=240, test_acc=0.537, train_acc=0.641]Test 2: Data size 272: : 20%|██ | 2/10 [00:17<01:10, 8.79s/it, data_size=240, test_acc=0.537, train_acc=0.641]Test 2: Data size 272: : 20%|██ | 2/10 [00:30<01:10, 8.79s/it, data_size=272, test_acc=0.73, train_acc=0.855] Test 2: Data size 272: : 30%|███ | 3/10 [00:30<01:16, 10.87s/it, data_size=272, test_acc=0.73, train_acc=0.855]Test 2: Data size 304: : 30%|███ | 3/10 [00:30<01:16, 10.87s/it, data_size=272, test_acc=0.73, train_acc=0.855]Test 2: Data size 304: : 30%|███ | 3/10 [00:44<01:16, 10.87s/it, data_size=304, test_acc=0.747, train_acc=0.872]Test 2: Data size 304: : 40%|████ | 4/10 [00:44<01:11, 11.85s/it, data_size=304, test_acc=0.747, train_acc=0.872]Test 2: Data size 336: : 40%|████ | 4/10 [00:44<01:11, 11.85s/it, data_size=304, test_acc=0.747, train_acc=0.872]Test 2: Data size 336: : 40%|████ | 4/10 [00:57<01:11, 11.85s/it, data_size=336, test_acc=0.854, train_acc=0.92] Test 2: Data size 336: : 50%|█████ | 5/10 [00:57<01:02, 12.47s/it, data_size=336, test_acc=0.854, train_acc=0.92]Test 2: Data size 368: : 50%|█████ | 5/10 [00:57<01:02, 12.47s/it, data_size=336, test_acc=0.854, train_acc=0.92]Test 2: Data size 368: : 50%|█████ | 5/10 [01:11<01:02, 12.47s/it, data_size=368, test_acc=0.872, train_acc=0.913]Test 2: Data size 368: : 60%|██████ | 6/10 [01:11<00:51, 12.93s/it, data_size=368, test_acc=0.872, train_acc=0.913]Test 2: Data size 400: : 60%|██████ | 6/10 [01:11<00:51, 12.93s/it, data_size=368, test_acc=0.872, train_acc=0.913]Test 2: Data size 400: : 60%|██████ | 6/10 [01:29<00:51, 12.93s/it, data_size=400, test_acc=0.882, train_acc=0.946]Test 2: Data size 400: : 70%|███████ | 7/10 [01:29<00:43, 14.65s/it, data_size=400, test_acc=0.882, train_acc=0.946]Test 2: Data size 432: : 70%|███████ | 7/10 [01:29<00:43, 14.65s/it, data_size=400, test_acc=0.882, train_acc=0.946]Test 2: Data size 432: : 70%|███████ | 7/10 [01:48<00:43, 14.65s/it, data_size=432, test_acc=0.905, train_acc=0.951]Test 2: Data size 432: : 80%|████████ | 8/10 [01:48<00:31, 15.89s/it, data_size=432, test_acc=0.905, train_acc=0.951]Test 2: Data size 464: : 80%|████████ | 8/10 [01:48<00:31, 15.89s/it, data_size=432, test_acc=0.905, train_acc=0.951]Test 2: Data size 464: : 80%|████████ | 8/10 [02:06<00:31, 15.89s/it, data_size=464, test_acc=0.896, train_acc=0.94] Test 2: Data size 464: : 90%|█████████ | 9/10 [02:06<00:16, 16.67s/it, data_size=464, test_acc=0.896, train_acc=0.94]Test 2: Data size 496: : 90%|█████████ | 9/10 [02:06<00:16, 16.67s/it, data_size=464, test_acc=0.896, train_acc=0.94]Test 2: Data size 496: : 90%|█████████ | 9/10 [02:25<00:16, 16.67s/it, data_size=496, test_acc=0.895, train_acc=0.922]Test 2: Data size 496: : 100%|██████████| 10/10 [02:25<00:00, 17.46s/it, data_size=496, test_acc=0.895, train_acc=0.922]Test 2: Data size 496: : 100%|██████████| 10/10 [02:25<00:00, 14.60s/it, data_size=496, test_acc=0.895, train_acc=0.922]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:08<?, ?it/s, data_size=208, test_acc=0.491, train_acc=0.476]Test 3: Data size 208: : 10%|█ | 1/10 [00:08<01:18, 8.73s/it, data_size=208, test_acc=0.491, train_acc=0.476]Test 3: Data size 240: : 10%|█ | 1/10 [00:08<01:18, 8.73s/it, data_size=208, test_acc=0.491, train_acc=0.476]Test 3: Data size 240: : 10%|█ | 1/10 [00:17<01:18, 8.73s/it, data_size=240, test_acc=0.612, train_acc=0.714]Test 3: Data size 240: : 20%|██ | 2/10 [00:17<01:10, 8.85s/it, data_size=240, test_acc=0.612, train_acc=0.714]Test 3: Data size 272: : 20%|██ | 2/10 [00:17<01:10, 8.85s/it, data_size=240, test_acc=0.612, train_acc=0.714]Test 3: Data size 272: : 20%|██ | 2/10 [00:30<01:10, 8.85s/it, data_size=272, test_acc=0.757, train_acc=0.83] Test 3: Data size 272: : 30%|███ | 3/10 [00:31<01:16, 10.92s/it, data_size=272, test_acc=0.757, train_acc=0.83]Test 3: Data size 304: : 30%|███ | 3/10 [00:31<01:16, 10.92s/it, data_size=272, test_acc=0.757, train_acc=0.83]Test 3: Data size 304: : 30%|███ | 3/10 [00:44<01:16, 10.92s/it, data_size=304, test_acc=0.86, train_acc=0.862]Test 3: Data size 304: : 40%|████ | 4/10 [00:44<01:11, 11.93s/it, data_size=304, test_acc=0.86, train_acc=0.862]Test 3: Data size 336: : 40%|████ | 4/10 [00:44<01:11, 11.93s/it, data_size=304, test_acc=0.86, train_acc=0.862]Test 3: Data size 336: : 40%|████ | 4/10 [00:58<01:11, 11.93s/it, data_size=336, test_acc=0.842, train_acc=0.805]Test 3: Data size 336: : 50%|█████ | 5/10 [00:58<01:02, 12.58s/it, data_size=336, test_acc=0.842, train_acc=0.805]Test 3: Data size 368: : 50%|█████ | 5/10 [00:58<01:02, 12.58s/it, data_size=336, test_acc=0.842, train_acc=0.805]Test 3: Data size 368: : 50%|█████ | 5/10 [01:11<01:02, 12.58s/it, data_size=368, test_acc=0.897, train_acc=0.909]Test 3: Data size 368: : 60%|██████ | 6/10 [01:11<00:51, 12.94s/it, data_size=368, test_acc=0.897, train_acc=0.909]Test 3: Data size 400: : 60%|██████ | 6/10 [01:11<00:51, 12.94s/it, data_size=368, test_acc=0.897, train_acc=0.909]Test 3: Data size 400: : 60%|██████ | 6/10 [01:30<00:51, 12.94s/it, data_size=400, test_acc=0.909, train_acc=0.914]Test 3: Data size 400: : 70%|███████ | 7/10 [01:30<00:44, 14.74s/it, data_size=400, test_acc=0.909, train_acc=0.914]Test 3: Data size 432: : 70%|███████ | 7/10 [01:30<00:44, 14.74s/it, data_size=400, test_acc=0.909, train_acc=0.914]Test 3: Data size 432: : 70%|███████ | 7/10 [01:48<00:44, 14.74s/it, data_size=432, test_acc=0.891, train_acc=0.839]Test 3: Data size 432: : 80%|████████ | 8/10 [01:48<00:31, 15.85s/it, data_size=432, test_acc=0.891, train_acc=0.839]Test 3: Data size 464: : 80%|████████ | 8/10 [01:48<00:31, 15.85s/it, data_size=432, test_acc=0.891, train_acc=0.839]Test 3: Data size 464: : 80%|████████ | 8/10 [02:07<00:31, 15.85s/it, data_size=464, test_acc=0.911, train_acc=0.911]Test 3: Data size 464: : 90%|█████████ | 9/10 [02:07<00:16, 16.72s/it, data_size=464, test_acc=0.911, train_acc=0.911]Test 3: Data size 496: : 90%|█████████ | 9/10 [02:07<00:16, 16.72s/it, data_size=464, test_acc=0.911, train_acc=0.911]Test 3: Data size 496: : 90%|█████████ | 9/10 [02:25<00:16, 16.72s/it, data_size=496, test_acc=0.923, train_acc=0.898]Test 3: Data size 496: : 100%|██████████| 10/10 [02:25<00:00, 17.35s/it, data_size=496, test_acc=0.923, train_acc=0.898]Test 3: Data size 496: : 100%|██████████| 10/10 [02:25<00:00, 14.60s/it, data_size=496, test_acc=0.923, train_acc=0.898]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:08<?, ?it/s, data_size=208, test_acc=0.545, train_acc=0.551]Test 4: Data size 208: : 10%|█ | 1/10 [00:09<01:21, 9.07s/it, data_size=208, test_acc=0.545, train_acc=0.551]Test 4: Data size 240: : 10%|█ | 1/10 [00:09<01:21, 9.07s/it, data_size=208, test_acc=0.545, train_acc=0.551]Test 4: Data size 240: : 10%|█ | 1/10 [00:18<01:21, 9.07s/it, data_size=240, test_acc=0.658, train_acc=0.658]Test 4: Data size 240: : 20%|██ | 2/10 [00:18<01:13, 9.13s/it, data_size=240, test_acc=0.658, train_acc=0.658]Test 4: Data size 272: : 20%|██ | 2/10 [00:18<01:13, 9.13s/it, data_size=240, test_acc=0.658, train_acc=0.658]Test 4: Data size 272: : 20%|██ | 2/10 [00:32<01:13, 9.13s/it, data_size=272, test_acc=0.785, train_acc=0.864]Test 4: Data size 272: : 30%|███ | 3/10 [00:32<01:19, 11.41s/it, data_size=272, test_acc=0.785, train_acc=0.864]Test 4: Data size 304: : 30%|███ | 3/10 [00:32<01:19, 11.41s/it, data_size=272, test_acc=0.785, train_acc=0.864]Test 4: Data size 304: : 30%|███ | 3/10 [00:46<01:19, 11.41s/it, data_size=304, test_acc=0.791, train_acc=0.837]Test 4: Data size 304: : 40%|████ | 4/10 [00:46<01:15, 12.60s/it, data_size=304, test_acc=0.791, train_acc=0.837]Test 4: Data size 336: : 40%|████ | 4/10 [00:46<01:15, 12.60s/it, data_size=304, test_acc=0.791, train_acc=0.837]Test 4: Data size 336: : 40%|████ | 4/10 [01:00<01:15, 12.60s/it, data_size=336, test_acc=0.849, train_acc=0.896]Test 4: Data size 336: : 50%|█████ | 5/10 [01:00<01:05, 13.16s/it, data_size=336, test_acc=0.849, train_acc=0.896]Test 4: Data size 368: : 50%|█████ | 5/10 [01:00<01:05, 13.16s/it, data_size=336, test_acc=0.849, train_acc=0.896]Test 4: Data size 368: : 50%|█████ | 5/10 [01:14<01:05, 13.16s/it, data_size=368, test_acc=0.861, train_acc=0.892]Test 4: Data size 368: : 60%|██████ | 6/10 [01:15<00:53, 13.47s/it, data_size=368, test_acc=0.861, train_acc=0.892]Test 4: Data size 400: : 60%|██████ | 6/10 [01:15<00:53, 13.47s/it, data_size=368, test_acc=0.861, train_acc=0.892]Test 4: Data size 400: : 60%|██████ | 6/10 [01:34<00:53, 13.47s/it, data_size=400, test_acc=0.871, train_acc=0.909]Test 4: Data size 400: : 70%|███████ | 7/10 [01:34<00:46, 15.37s/it, data_size=400, test_acc=0.871, train_acc=0.909]Test 4: Data size 432: : 70%|███████ | 7/10 [01:34<00:46, 15.37s/it, data_size=400, test_acc=0.871, train_acc=0.909]Test 4: Data size 432: : 70%|███████ | 7/10 [01:53<00:46, 15.37s/it, data_size=432, test_acc=0.89, train_acc=0.912] Test 4: Data size 432: : 80%|████████ | 8/10 [01:53<00:33, 16.51s/it, data_size=432, test_acc=0.89, train_acc=0.912]Test 4: Data size 464: : 80%|████████ | 8/10 [01:53<00:33, 16.51s/it, data_size=432, test_acc=0.89, train_acc=0.912]Test 4: Data size 464: : 80%|████████ | 8/10 [02:11<00:33, 16.51s/it, data_size=464, test_acc=0.89, train_acc=0.897]Test 4: Data size 464: : 90%|█████████ | 9/10 [02:11<00:17, 17.05s/it, data_size=464, test_acc=0.89, train_acc=0.897]Test 4: Data size 496: : 90%|█████████ | 9/10 [02:11<00:17, 17.05s/it, data_size=464, test_acc=0.89, train_acc=0.897]Test 4: Data size 496: : 90%|█████████ | 9/10 [02:30<00:17, 17.05s/it, data_size=496, test_acc=0.9, train_acc=0.87] Test 4: Data size 496: : 100%|██████████| 10/10 [02:30<00:00, 17.63s/it, data_size=496, test_acc=0.9, train_acc=0.87]Test 4: Data size 496: : 100%|██████████| 10/10 [02:30<00:00, 15.04s/it, data_size=496, test_acc=0.9, train_acc=0.87]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:09<?, ?it/s, data_size=208, test_acc=0.495, train_acc=0.5]Test 5: Data size 208: : 10%|█ | 1/10 [00:09<01:24, 9.33s/it, data_size=208, test_acc=0.495, train_acc=0.5]Test 5: Data size 240: : 10%|█ | 1/10 [00:09<01:24, 9.33s/it, data_size=208, test_acc=0.495, train_acc=0.5]Test 5: Data size 240: : 10%|█ | 1/10 [00:18<01:24, 9.33s/it, data_size=240, test_acc=0.695, train_acc=0.766]Test 5: Data size 240: : 20%|██ | 2/10 [00:18<01:15, 9.46s/it, data_size=240, test_acc=0.695, train_acc=0.766]Test 5: Data size 272: : 20%|██ | 2/10 [00:18<01:15, 9.46s/it, data_size=240, test_acc=0.695, train_acc=0.766]Test 5: Data size 272: : 20%|██ | 2/10 [00:32<01:15, 9.46s/it, data_size=272, test_acc=0.76, train_acc=0.875] Test 5: Data size 272: : 30%|███ | 3/10 [00:33<01:21, 11.63s/it, data_size=272, test_acc=0.76, train_acc=0.875]Test 5: Data size 304: : 30%|███ | 3/10 [00:33<01:21, 11.63s/it, data_size=272, test_acc=0.76, train_acc=0.875]Test 5: Data size 304: : 30%|███ | 3/10 [00:46<01:21, 11.63s/it, data_size=304, test_acc=0.775, train_acc=0.873]Test 5: Data size 304: : 40%|████ | 4/10 [00:46<01:15, 12.52s/it, data_size=304, test_acc=0.775, train_acc=0.873]Test 5: Data size 336: : 40%|████ | 4/10 [00:46<01:15, 12.52s/it, data_size=304, test_acc=0.775, train_acc=0.873]Test 5: Data size 336: : 40%|████ | 4/10 [01:01<01:15, 12.52s/it, data_size=336, test_acc=0.825, train_acc=0.873]Test 5: Data size 336: : 50%|█████ | 5/10 [01:01<01:06, 13.24s/it, data_size=336, test_acc=0.825, train_acc=0.873]Test 5: Data size 368: : 50%|█████ | 5/10 [01:01<01:06, 13.24s/it, data_size=336, test_acc=0.825, train_acc=0.873]Test 5: Data size 368: : 50%|█████ | 5/10 [01:15<01:06, 13.24s/it, data_size=368, test_acc=0.87, train_acc=0.92] Test 5: Data size 368: : 60%|██████ | 6/10 [01:15<00:54, 13.55s/it, data_size=368, test_acc=0.87, train_acc=0.92]Test 5: Data size 400: : 60%|██████ | 6/10 [01:15<00:54, 13.55s/it, data_size=368, test_acc=0.87, train_acc=0.92]Test 5: Data size 400: : 60%|██████ | 6/10 [01:34<00:54, 13.55s/it, data_size=400, test_acc=0.869, train_acc=0.935]Test 5: Data size 400: : 70%|███████ | 7/10 [01:34<00:46, 15.38s/it, data_size=400, test_acc=0.869, train_acc=0.935]Test 5: Data size 432: : 70%|███████ | 7/10 [01:34<00:46, 15.38s/it, data_size=400, test_acc=0.869, train_acc=0.935]Test 5: Data size 432: : 70%|███████ | 7/10 [01:53<00:46, 15.38s/it, data_size=432, test_acc=0.876, train_acc=0.952]Test 5: Data size 432: : 80%|████████ | 8/10 [01:54<00:33, 16.64s/it, data_size=432, test_acc=0.876, train_acc=0.952]Test 5: Data size 464: : 80%|████████ | 8/10 [01:54<00:33, 16.64s/it, data_size=432, test_acc=0.876, train_acc=0.952]Test 5: Data size 464: : 80%|████████ | 8/10 [02:13<00:33, 16.64s/it, data_size=464, test_acc=0.857, train_acc=0.905]Test 5: Data size 464: : 90%|█████████ | 9/10 [02:13<00:17, 17.61s/it, data_size=464, test_acc=0.857, train_acc=0.905]Test 5: Data size 496: : 90%|█████████ | 9/10 [02:13<00:17, 17.61s/it, data_size=464, test_acc=0.857, train_acc=0.905]Test 5: Data size 496: : 90%|█████████ | 9/10 [02:33<00:17, 17.61s/it, data_size=496, test_acc=0.875, train_acc=0.916]Test 5: Data size 496: : 100%|██████████| 10/10 [02:33<00:00, 18.19s/it, data_size=496, test_acc=0.875, train_acc=0.916]Test 5: Data size 496: : 100%|██████████| 10/10 [02:33<00:00, 15.34s/it, data_size=496, test_acc=0.875, train_acc=0.916]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:08<?, ?it/s, data_size=208, test_acc=0.498, train_acc=0.497]Test 6: Data size 208: : 10%|█ | 1/10 [00:09<01:21, 9.05s/it, data_size=208, test_acc=0.498, train_acc=0.497]Test 6: Data size 240: : 10%|█ | 1/10 [00:09<01:21, 9.05s/it, data_size=208, test_acc=0.498, train_acc=0.497]Test 6: Data size 240: : 10%|█ | 1/10 [00:18<01:21, 9.05s/it, data_size=240, test_acc=0.569, train_acc=0.631]Test 6: Data size 240: : 20%|██ | 2/10 [00:18<01:13, 9.13s/it, data_size=240, test_acc=0.569, train_acc=0.631]Test 6: Data size 272: : 20%|██ | 2/10 [00:18<01:13, 9.13s/it, data_size=240, test_acc=0.569, train_acc=0.631]Test 6: Data size 272: : 20%|██ | 2/10 [00:32<01:13, 9.13s/it, data_size=272, test_acc=0.738, train_acc=0.841]Test 6: Data size 272: : 30%|███ | 3/10 [00:32<01:19, 11.39s/it, data_size=272, test_acc=0.738, train_acc=0.841]Test 6: Data size 304: : 30%|███ | 3/10 [00:32<01:19, 11.39s/it, data_size=272, test_acc=0.738, train_acc=0.841]Test 6: Data size 304: : 30%|███ | 3/10 [00:45<01:19, 11.39s/it, data_size=304, test_acc=0.73, train_acc=0.806] Test 6: Data size 304: : 40%|████ | 4/10 [00:46<01:13, 12.31s/it, data_size=304, test_acc=0.73, train_acc=0.806]Test 6: Data size 336: : 40%|████ | 4/10 [00:46<01:13, 12.31s/it, data_size=304, test_acc=0.73, train_acc=0.806]Test 6: Data size 336: : 40%|████ | 4/10 [01:00<01:13, 12.31s/it, data_size=336, test_acc=0.753, train_acc=0.841]Test 6: Data size 336: : 50%|█████ | 5/10 [01:00<01:05, 13.01s/it, data_size=336, test_acc=0.753, train_acc=0.841]Test 6: Data size 368: : 50%|█████ | 5/10 [01:00<01:05, 13.01s/it, data_size=336, test_acc=0.753, train_acc=0.841]Test 6: Data size 368: : 50%|█████ | 5/10 [01:14<01:05, 13.01s/it, data_size=368, test_acc=0.759, train_acc=0.851]Test 6: Data size 368: : 60%|██████ | 6/10 [01:14<00:53, 13.34s/it, data_size=368, test_acc=0.759, train_acc=0.851]Test 6: Data size 400: : 60%|██████ | 6/10 [01:14<00:53, 13.34s/it, data_size=368, test_acc=0.759, train_acc=0.851]Test 6: Data size 400: : 60%|██████ | 6/10 [01:33<00:53, 13.34s/it, data_size=400, test_acc=0.866, train_acc=0.893]Test 6: Data size 400: : 70%|███████ | 7/10 [01:33<00:45, 15.15s/it, data_size=400, test_acc=0.866, train_acc=0.893]Test 6: Data size 432: : 70%|███████ | 7/10 [01:33<00:45, 15.15s/it, data_size=400, test_acc=0.866, train_acc=0.893]Test 6: Data size 432: : 70%|███████ | 7/10 [01:51<00:45, 15.15s/it, data_size=432, test_acc=0.903, train_acc=0.932]Test 6: Data size 432: : 80%|████████ | 8/10 [01:51<00:32, 16.28s/it, data_size=432, test_acc=0.903, train_acc=0.932]Test 6: Data size 464: : 80%|████████ | 8/10 [01:51<00:32, 16.28s/it, data_size=432, test_acc=0.903, train_acc=0.932]Test 6: Data size 464: : 80%|████████ | 8/10 [02:10<00:32, 16.28s/it, data_size=464, test_acc=0.903, train_acc=0.905]Test 6: Data size 464: : 90%|█████████ | 9/10 [02:10<00:16, 16.97s/it, data_size=464, test_acc=0.903, train_acc=0.905]Test 6: Data size 496: : 90%|█████████ | 9/10 [02:10<00:16, 16.97s/it, data_size=464, test_acc=0.903, train_acc=0.905]Test 6: Data size 496: : 90%|█████████ | 9/10 [02:28<00:16, 16.97s/it, data_size=496, test_acc=0.845, train_acc=0.821]Test 6: Data size 496: : 100%|██████████| 10/10 [02:28<00:00, 17.35s/it, data_size=496, test_acc=0.845, train_acc=0.821]Test 6: Data size 496: : 100%|██████████| 10/10 [02:28<00:00, 14.85s/it, data_size=496, test_acc=0.845, train_acc=0.821]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:09<?, ?it/s, data_size=208, test_acc=0.5, train_acc=0.5]Test 7: Data size 208: : 10%|█ | 1/10 [00:09<01:25, 9.52s/it, data_size=208, test_acc=0.5, train_acc=0.5]Test 7: Data size 240: : 10%|█ | 1/10 [00:09<01:25, 9.52s/it, data_size=208, test_acc=0.5, train_acc=0.5]Test 7: Data size 240: : 10%|█ | 1/10 [00:19<01:25, 9.52s/it, data_size=240, test_acc=0.679, train_acc=0.79]Test 7: Data size 240: : 20%|██ | 2/10 [00:19<01:16, 9.62s/it, data_size=240, test_acc=0.679, train_acc=0.79]Test 7: Data size 272: : 20%|██ | 2/10 [00:19<01:16, 9.62s/it, data_size=240, test_acc=0.679, train_acc=0.79]Test 7: Data size 272: : 20%|██ | 2/10 [00:33<01:16, 9.62s/it, data_size=272, test_acc=0.695, train_acc=0.807]Test 7: Data size 272: : 30%|███ | 3/10 [00:33<01:23, 11.90s/it, data_size=272, test_acc=0.695, train_acc=0.807]Test 7: Data size 304: : 30%|███ | 3/10 [00:33<01:23, 11.90s/it, data_size=272, test_acc=0.695, train_acc=0.807]Test 7: Data size 304: : 30%|███ | 3/10 [00:47<01:23, 11.90s/it, data_size=304, test_acc=0.734, train_acc=0.849]Test 7: Data size 304: : 40%|████ | 4/10 [00:47<01:16, 12.79s/it, data_size=304, test_acc=0.734, train_acc=0.849]Test 7: Data size 336: : 40%|████ | 4/10 [00:47<01:16, 12.79s/it, data_size=304, test_acc=0.734, train_acc=0.849]Test 7: Data size 336: : 40%|████ | 4/10 [01:02<01:16, 12.79s/it, data_size=336, test_acc=0.86, train_acc=0.881] Test 7: Data size 336: : 50%|█████ | 5/10 [01:02<01:06, 13.36s/it, data_size=336, test_acc=0.86, train_acc=0.881]Test 7: Data size 368: : 50%|█████ | 5/10 [01:02<01:06, 13.36s/it, data_size=336, test_acc=0.86, train_acc=0.881]Test 7: Data size 368: : 50%|█████ | 5/10 [01:16<01:06, 13.36s/it, data_size=368, test_acc=0.889, train_acc=0.894]Test 7: Data size 368: : 60%|██████ | 6/10 [01:16<00:54, 13.74s/it, data_size=368, test_acc=0.889, train_acc=0.894]Test 7: Data size 400: : 60%|██████ | 6/10 [01:16<00:54, 13.74s/it, data_size=368, test_acc=0.889, train_acc=0.894]Test 7: Data size 400: : 60%|██████ | 6/10 [01:35<00:54, 13.74s/it, data_size=400, test_acc=0.881, train_acc=0.857]Test 7: Data size 400: : 70%|███████ | 7/10 [01:36<00:46, 15.52s/it, data_size=400, test_acc=0.881, train_acc=0.857]Test 7: Data size 432: : 70%|███████ | 7/10 [01:36<00:46, 15.52s/it, data_size=400, test_acc=0.881, train_acc=0.857]Test 7: Data size 432: : 70%|███████ | 7/10 [01:55<00:46, 15.52s/it, data_size=432, test_acc=0.916, train_acc=0.907]Test 7: Data size 432: : 80%|████████ | 8/10 [01:55<00:33, 16.79s/it, data_size=432, test_acc=0.916, train_acc=0.907]Test 7: Data size 464: : 80%|████████ | 8/10 [01:55<00:33, 16.79s/it, data_size=432, test_acc=0.916, train_acc=0.907]Test 7: Data size 464: : 80%|████████ | 8/10 [02:14<00:33, 16.79s/it, data_size=464, test_acc=0.915, train_acc=0.919]Test 7: Data size 464: : 90%|█████████ | 9/10 [02:14<00:17, 17.48s/it, data_size=464, test_acc=0.915, train_acc=0.919]Test 7: Data size 496: : 90%|█████████ | 9/10 [02:14<00:17, 17.48s/it, data_size=464, test_acc=0.915, train_acc=0.919]Test 7: Data size 496: : 90%|█████████ | 9/10 [02:34<00:17, 17.48s/it, data_size=496, test_acc=0.917, train_acc=0.913]Test 7: Data size 496: : 100%|██████████| 10/10 [02:34<00:00, 18.16s/it, data_size=496, test_acc=0.917, train_acc=0.913]Test 7: Data size 496: : 100%|██████████| 10/10 [02:34<00:00, 15.42s/it, data_size=496, test_acc=0.917, train_acc=0.913]
working on model Multimodal-late-fusion-model-based-on-AlexNet with MAX_ENTROPY
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:09<?, ?it/s, data_size=208, test_acc=0.492, train_acc=0.492]Test 0: Data size 208: : 10%|█ | 1/10 [00:09<01:24, 9.36s/it, data_size=208, test_acc=0.492, train_acc=0.492]Test 0: Data size 240: : 10%|█ | 1/10 [00:09<01:24, 9.36s/it, data_size=208, test_acc=0.492, train_acc=0.492]Test 0: Data size 240: : 10%|█ | 1/10 [00:18<01:24, 9.36s/it, data_size=240, test_acc=0.739, train_acc=0.777]Test 0: Data size 240: : 20%|██ | 2/10 [00:18<01:16, 9.51s/it, data_size=240, test_acc=0.739, train_acc=0.777]Test 0: Data size 272: : 20%|██ | 2/10 [00:18<01:16, 9.51s/it, data_size=240, test_acc=0.739, train_acc=0.777]Test 0: Data size 272: : 20%|██ | 2/10 [00:33<01:16, 9.51s/it, data_size=272, test_acc=0.768, train_acc=0.836]Test 0: Data size 272: : 30%|███ | 3/10 [00:33<01:22, 11.80s/it, data_size=272, test_acc=0.768, train_acc=0.836]Test 0: Data size 304: : 30%|███ | 3/10 [00:33<01:22, 11.80s/it, data_size=272, test_acc=0.768, train_acc=0.836]Test 0: Data size 304: : 30%|███ | 3/10 [00:47<01:22, 11.80s/it, data_size=304, test_acc=0.805, train_acc=0.848]Test 0: Data size 304: : 40%|████ | 4/10 [00:47<01:17, 12.87s/it, data_size=304, test_acc=0.805, train_acc=0.848]Test 0: Data size 336: : 40%|████ | 4/10 [00:47<01:17, 12.87s/it, data_size=304, test_acc=0.805, train_acc=0.848]Test 0: Data size 336: : 40%|████ | 4/10 [01:02<01:17, 12.87s/it, data_size=336, test_acc=0.812, train_acc=0.852]Test 0: Data size 336: : 50%|█████ | 5/10 [01:02<01:07, 13.50s/it, data_size=336, test_acc=0.812, train_acc=0.852]Test 0: Data size 368: : 50%|█████ | 5/10 [01:02<01:07, 13.50s/it, data_size=336, test_acc=0.812, train_acc=0.852]Test 0: Data size 368: : 50%|█████ | 5/10 [01:16<01:07, 13.50s/it, data_size=368, test_acc=0.845, train_acc=0.862]Test 0: Data size 368: : 60%|██████ | 6/10 [01:17<00:55, 13.82s/it, data_size=368, test_acc=0.845, train_acc=0.862]Test 0: Data size 400: : 60%|██████ | 6/10 [01:17<00:55, 13.82s/it, data_size=368, test_acc=0.845, train_acc=0.862]Test 0: Data size 400: : 60%|██████ | 6/10 [01:36<00:55, 13.82s/it, data_size=400, test_acc=0.881, train_acc=0.918]Test 0: Data size 400: : 70%|███████ | 7/10 [01:36<00:46, 15.55s/it, data_size=400, test_acc=0.881, train_acc=0.918]Test 0: Data size 432: : 70%|███████ | 7/10 [01:36<00:46, 15.55s/it, data_size=400, test_acc=0.881, train_acc=0.918]Test 0: Data size 432: : 70%|███████ | 7/10 [01:55<00:46, 15.55s/it, data_size=432, test_acc=0.896, train_acc=0.918]Test 0: Data size 432: : 80%|████████ | 8/10 [01:55<00:33, 16.74s/it, data_size=432, test_acc=0.896, train_acc=0.918]Test 0: Data size 464: : 80%|████████ | 8/10 [01:55<00:33, 16.74s/it, data_size=432, test_acc=0.896, train_acc=0.918]Test 0: Data size 464: : 80%|████████ | 8/10 [02:14<00:33, 16.74s/it, data_size=464, test_acc=0.868, train_acc=0.892]Test 0: Data size 464: : 90%|█████████ | 9/10 [02:14<00:17, 17.53s/it, data_size=464, test_acc=0.868, train_acc=0.892]Test 0: Data size 496: : 90%|█████████ | 9/10 [02:14<00:17, 17.53s/it, data_size=464, test_acc=0.868, train_acc=0.892]Test 0: Data size 496: : 90%|█████████ | 9/10 [02:33<00:17, 17.53s/it, data_size=496, test_acc=0.902, train_acc=0.883]Test 0: Data size 496: : 100%|██████████| 10/10 [02:33<00:00, 17.87s/it, data_size=496, test_acc=0.902, train_acc=0.883]Test 0: Data size 496: : 100%|██████████| 10/10 [02:33<00:00, 15.34s/it, data_size=496, test_acc=0.902, train_acc=0.883]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:09<?, ?it/s, data_size=208, test_acc=0.497, train_acc=0.49]Test 1: Data size 208: : 10%|█ | 1/10 [00:09<01:23, 9.29s/it, data_size=208, test_acc=0.497, train_acc=0.49]Test 1: Data size 240: : 10%|█ | 1/10 [00:09<01:23, 9.29s/it, data_size=208, test_acc=0.497, train_acc=0.49]Test 1: Data size 240: : 10%|█ | 1/10 [00:18<01:23, 9.29s/it, data_size=240, test_acc=0.616, train_acc=0.69]Test 1: Data size 240: : 20%|██ | 2/10 [00:18<01:16, 9.51s/it, data_size=240, test_acc=0.616, train_acc=0.69]Test 1: Data size 272: : 20%|██ | 2/10 [00:18<01:16, 9.51s/it, data_size=240, test_acc=0.616, train_acc=0.69]Test 1: Data size 272: : 20%|██ | 2/10 [00:33<01:16, 9.51s/it, data_size=272, test_acc=0.77, train_acc=0.852]Test 1: Data size 272: : 30%|███ | 3/10 [00:33<01:22, 11.85s/it, data_size=272, test_acc=0.77, train_acc=0.852]Test 1: Data size 304: : 30%|███ | 3/10 [00:33<01:22, 11.85s/it, data_size=272, test_acc=0.77, train_acc=0.852]Test 1: Data size 304: : 30%|███ | 3/10 [00:47<01:22, 11.85s/it, data_size=304, test_acc=0.796, train_acc=0.846]Test 1: Data size 304: : 40%|████ | 4/10 [00:48<01:17, 12.90s/it, data_size=304, test_acc=0.796, train_acc=0.846]Test 1: Data size 336: : 40%|████ | 4/10 [00:48<01:17, 12.90s/it, data_size=304, test_acc=0.796, train_acc=0.846]Test 1: Data size 336: : 40%|████ | 4/10 [01:02<01:17, 12.90s/it, data_size=336, test_acc=0.797, train_acc=0.87] Test 1: Data size 336: : 50%|█████ | 5/10 [01:02<01:07, 13.48s/it, data_size=336, test_acc=0.797, train_acc=0.87]Test 1: Data size 368: : 50%|█████ | 5/10 [01:02<01:07, 13.48s/it, data_size=336, test_acc=0.797, train_acc=0.87]Test 1: Data size 368: : 50%|█████ | 5/10 [01:16<01:07, 13.48s/it, data_size=368, test_acc=0.777, train_acc=0.862]Test 1: Data size 368: : 60%|██████ | 6/10 [01:16<00:55, 13.78s/it, data_size=368, test_acc=0.777, train_acc=0.862]Test 1: Data size 400: : 60%|██████ | 6/10 [01:16<00:55, 13.78s/it, data_size=368, test_acc=0.777, train_acc=0.862]Test 1: Data size 400: : 60%|██████ | 6/10 [01:36<00:55, 13.78s/it, data_size=400, test_acc=0.784, train_acc=0.856]Test 1: Data size 400: : 70%|███████ | 7/10 [01:36<00:46, 15.65s/it, data_size=400, test_acc=0.784, train_acc=0.856]Test 1: Data size 432: : 70%|███████ | 7/10 [01:36<00:46, 15.65s/it, data_size=400, test_acc=0.784, train_acc=0.856]Test 1: Data size 432: : 70%|███████ | 7/10 [01:55<00:46, 15.65s/it, data_size=432, test_acc=0.884, train_acc=0.895]Test 1: Data size 432: : 80%|████████ | 8/10 [01:55<00:33, 16.63s/it, data_size=432, test_acc=0.884, train_acc=0.895]Test 1: Data size 464: : 80%|████████ | 8/10 [01:55<00:33, 16.63s/it, data_size=432, test_acc=0.884, train_acc=0.895]Test 1: Data size 464: : 80%|████████ | 8/10 [02:13<00:33, 16.63s/it, data_size=464, test_acc=0.868, train_acc=0.891]Test 1: Data size 464: : 90%|█████████ | 9/10 [02:13<00:17, 17.17s/it, data_size=464, test_acc=0.868, train_acc=0.891]Test 1: Data size 496: : 90%|█████████ | 9/10 [02:13<00:17, 17.17s/it, data_size=464, test_acc=0.868, train_acc=0.891]Test 1: Data size 496: : 90%|█████████ | 9/10 [02:32<00:17, 17.17s/it, data_size=496, test_acc=0.893, train_acc=0.909]Test 1: Data size 496: : 100%|██████████| 10/10 [02:32<00:00, 17.83s/it, data_size=496, test_acc=0.893, train_acc=0.909]Test 1: Data size 496: : 100%|██████████| 10/10 [02:32<00:00, 15.29s/it, data_size=496, test_acc=0.893, train_acc=0.909]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:08<?, ?it/s, data_size=208, test_acc=0.498, train_acc=0.5]Test 2: Data size 208: : 10%|█ | 1/10 [00:08<01:18, 8.70s/it, data_size=208, test_acc=0.498, train_acc=0.5]Test 2: Data size 240: : 10%|█ | 1/10 [00:08<01:18, 8.70s/it, data_size=208, test_acc=0.498, train_acc=0.5]Test 2: Data size 240: : 10%|█ | 1/10 [00:17<01:18, 8.70s/it, data_size=240, test_acc=0.498, train_acc=0.497]Test 2: Data size 240: : 20%|██ | 2/10 [00:17<01:10, 8.76s/it, data_size=240, test_acc=0.498, train_acc=0.497]Test 2: Data size 272: : 20%|██ | 2/10 [00:17<01:10, 8.76s/it, data_size=240, test_acc=0.498, train_acc=0.497]Test 2: Data size 272: : 20%|██ | 2/10 [00:30<01:10, 8.76s/it, data_size=272, test_acc=0.742, train_acc=0.872]Test 2: Data size 272: : 30%|███ | 3/10 [00:30<01:15, 10.80s/it, data_size=272, test_acc=0.742, train_acc=0.872]Test 2: Data size 304: : 30%|███ | 3/10 [00:30<01:15, 10.80s/it, data_size=272, test_acc=0.742, train_acc=0.872]Test 2: Data size 304: : 30%|███ | 3/10 [00:43<01:15, 10.80s/it, data_size=304, test_acc=0.759, train_acc=0.884]Test 2: Data size 304: : 40%|████ | 4/10 [00:43<01:10, 11.76s/it, data_size=304, test_acc=0.759, train_acc=0.884]Test 2: Data size 336: : 40%|████ | 4/10 [00:43<01:10, 11.76s/it, data_size=304, test_acc=0.759, train_acc=0.884]Test 2: Data size 336: : 40%|████ | 4/10 [00:57<01:10, 11.76s/it, data_size=336, test_acc=0.875, train_acc=0.909]Test 2: Data size 336: : 50%|█████ | 5/10 [00:57<01:02, 12.42s/it, data_size=336, test_acc=0.875, train_acc=0.909]Test 2: Data size 368: : 50%|█████ | 5/10 [00:57<01:02, 12.42s/it, data_size=336, test_acc=0.875, train_acc=0.909]Test 2: Data size 368: : 50%|█████ | 5/10 [01:10<01:02, 12.42s/it, data_size=368, test_acc=0.877, train_acc=0.95] Test 2: Data size 368: : 60%|██████ | 6/10 [01:11<00:51, 12.78s/it, data_size=368, test_acc=0.877, train_acc=0.95]Test 2: Data size 400: : 60%|██████ | 6/10 [01:11<00:51, 12.78s/it, data_size=368, test_acc=0.877, train_acc=0.95]Test 2: Data size 400: : 60%|██████ | 6/10 [01:29<00:51, 12.78s/it, data_size=400, test_acc=0.915, train_acc=0.958]Test 2: Data size 400: : 70%|███████ | 7/10 [01:29<00:43, 14.52s/it, data_size=400, test_acc=0.915, train_acc=0.958]Test 2: Data size 432: : 70%|███████ | 7/10 [01:29<00:43, 14.52s/it, data_size=400, test_acc=0.915, train_acc=0.958]Test 2: Data size 432: : 70%|███████ | 7/10 [01:47<00:43, 14.52s/it, data_size=432, test_acc=0.912, train_acc=0.975]Test 2: Data size 432: : 80%|████████ | 8/10 [01:47<00:31, 15.79s/it, data_size=432, test_acc=0.912, train_acc=0.975]Test 2: Data size 464: : 80%|████████ | 8/10 [01:47<00:31, 15.79s/it, data_size=432, test_acc=0.912, train_acc=0.975]Test 2: Data size 464: : 80%|████████ | 8/10 [02:06<00:31, 15.79s/it, data_size=464, test_acc=0.916, train_acc=0.958]Test 2: Data size 464: : 90%|█████████ | 9/10 [02:06<00:16, 16.67s/it, data_size=464, test_acc=0.916, train_acc=0.958]Test 2: Data size 496: : 90%|█████████ | 9/10 [02:06<00:16, 16.67s/it, data_size=464, test_acc=0.916, train_acc=0.958]Test 2: Data size 496: : 90%|█████████ | 9/10 [02:25<00:16, 16.67s/it, data_size=496, test_acc=0.868, train_acc=0.912]Test 2: Data size 496: : 100%|██████████| 10/10 [02:25<00:00, 17.47s/it, data_size=496, test_acc=0.868, train_acc=0.912]Test 2: Data size 496: : 100%|██████████| 10/10 [02:25<00:00, 14.55s/it, data_size=496, test_acc=0.868, train_acc=0.912]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:08<?, ?it/s, data_size=208, test_acc=0.607, train_acc=0.632]Test 3: Data size 208: : 10%|█ | 1/10 [00:08<01:18, 8.72s/it, data_size=208, test_acc=0.607, train_acc=0.632]Test 3: Data size 240: : 10%|█ | 1/10 [00:08<01:18, 8.72s/it, data_size=208, test_acc=0.607, train_acc=0.632]Test 3: Data size 240: : 10%|█ | 1/10 [00:17<01:18, 8.72s/it, data_size=240, test_acc=0.748, train_acc=0.784]Test 3: Data size 240: : 20%|██ | 2/10 [00:17<01:10, 8.77s/it, data_size=240, test_acc=0.748, train_acc=0.784]Test 3: Data size 272: : 20%|██ | 2/10 [00:17<01:10, 8.77s/it, data_size=240, test_acc=0.748, train_acc=0.784]Test 3: Data size 272: : 20%|██ | 2/10 [00:30<01:10, 8.77s/it, data_size=272, test_acc=0.813, train_acc=0.892]Test 3: Data size 272: : 30%|███ | 3/10 [00:30<01:16, 10.91s/it, data_size=272, test_acc=0.813, train_acc=0.892]Test 3: Data size 304: : 30%|███ | 3/10 [00:30<01:16, 10.91s/it, data_size=272, test_acc=0.813, train_acc=0.892]Test 3: Data size 304: : 30%|███ | 3/10 [00:44<01:16, 10.91s/it, data_size=304, test_acc=0.856, train_acc=0.929]Test 3: Data size 304: : 40%|████ | 4/10 [00:44<01:11, 11.92s/it, data_size=304, test_acc=0.856, train_acc=0.929]Test 3: Data size 336: : 40%|████ | 4/10 [00:44<01:11, 11.92s/it, data_size=304, test_acc=0.856, train_acc=0.929]Test 3: Data size 336: : 40%|████ | 4/10 [00:58<01:11, 11.92s/it, data_size=336, test_acc=0.843, train_acc=0.926]Test 3: Data size 336: : 50%|█████ | 5/10 [00:58<01:02, 12.57s/it, data_size=336, test_acc=0.843, train_acc=0.926]Test 3: Data size 368: : 50%|█████ | 5/10 [00:58<01:02, 12.57s/it, data_size=336, test_acc=0.843, train_acc=0.926]Test 3: Data size 368: : 50%|█████ | 5/10 [01:11<01:02, 12.57s/it, data_size=368, test_acc=0.876, train_acc=0.931]Test 3: Data size 368: : 60%|██████ | 6/10 [01:11<00:51, 12.98s/it, data_size=368, test_acc=0.876, train_acc=0.931]Test 3: Data size 400: : 60%|██████ | 6/10 [01:11<00:51, 12.98s/it, data_size=368, test_acc=0.876, train_acc=0.931]Test 3: Data size 400: : 60%|██████ | 6/10 [01:30<00:51, 12.98s/it, data_size=400, test_acc=0.878, train_acc=0.926]Test 3: Data size 400: : 70%|███████ | 7/10 [01:30<00:44, 14.72s/it, data_size=400, test_acc=0.878, train_acc=0.926]Test 3: Data size 432: : 70%|███████ | 7/10 [01:30<00:44, 14.72s/it, data_size=400, test_acc=0.878, train_acc=0.926]Test 3: Data size 432: : 70%|███████ | 7/10 [01:48<00:44, 14.72s/it, data_size=432, test_acc=0.893, train_acc=0.937]Test 3: Data size 432: : 80%|████████ | 8/10 [01:48<00:31, 15.93s/it, data_size=432, test_acc=0.893, train_acc=0.937]Test 3: Data size 464: : 80%|████████ | 8/10 [01:48<00:31, 15.93s/it, data_size=432, test_acc=0.893, train_acc=0.937]Test 3: Data size 464: : 80%|████████ | 8/10 [02:08<00:31, 15.93s/it, data_size=464, test_acc=0.883, train_acc=0.917]Test 3: Data size 464: : 90%|█████████ | 9/10 [02:08<00:17, 17.02s/it, data_size=464, test_acc=0.883, train_acc=0.917]Test 3: Data size 496: : 90%|█████████ | 9/10 [02:08<00:17, 17.02s/it, data_size=464, test_acc=0.883, train_acc=0.917]Test 3: Data size 496: : 90%|█████████ | 9/10 [02:27<00:17, 17.02s/it, data_size=496, test_acc=0.905, train_acc=0.939]Test 3: Data size 496: : 100%|██████████| 10/10 [02:27<00:00, 17.67s/it, data_size=496, test_acc=0.905, train_acc=0.939]Test 3: Data size 496: : 100%|██████████| 10/10 [02:27<00:00, 14.73s/it, data_size=496, test_acc=0.905, train_acc=0.939]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:08<?, ?it/s, data_size=208, test_acc=0.543, train_acc=0.524]Test 4: Data size 208: : 10%|█ | 1/10 [00:08<01:20, 8.93s/it, data_size=208, test_acc=0.543, train_acc=0.524]Test 4: Data size 240: : 10%|█ | 1/10 [00:08<01:20, 8.93s/it, data_size=208, test_acc=0.543, train_acc=0.524]Test 4: Data size 240: : 10%|█ | 1/10 [00:17<01:20, 8.93s/it, data_size=240, test_acc=0.726, train_acc=0.817]Test 4: Data size 240: : 20%|██ | 2/10 [00:17<01:11, 8.94s/it, data_size=240, test_acc=0.726, train_acc=0.817]Test 4: Data size 272: : 20%|██ | 2/10 [00:17<01:11, 8.94s/it, data_size=240, test_acc=0.726, train_acc=0.817]Test 4: Data size 272: : 20%|██ | 2/10 [00:31<01:11, 8.94s/it, data_size=272, test_acc=0.762, train_acc=0.845]Test 4: Data size 272: : 30%|███ | 3/10 [00:31<01:17, 11.06s/it, data_size=272, test_acc=0.762, train_acc=0.845]Test 4: Data size 304: : 30%|███ | 3/10 [00:31<01:17, 11.06s/it, data_size=272, test_acc=0.762, train_acc=0.845]Test 4: Data size 304: : 30%|███ | 3/10 [00:44<01:17, 11.06s/it, data_size=304, test_acc=0.875, train_acc=0.897]Test 4: Data size 304: : 40%|████ | 4/10 [00:45<01:12, 12.08s/it, data_size=304, test_acc=0.875, train_acc=0.897]Test 4: Data size 336: : 40%|████ | 4/10 [00:45<01:12, 12.08s/it, data_size=304, test_acc=0.875, train_acc=0.897]Test 4: Data size 336: : 40%|████ | 4/10 [00:58<01:12, 12.08s/it, data_size=336, test_acc=0.915, train_acc=0.92] Test 4: Data size 336: : 50%|█████ | 5/10 [00:59<01:03, 12.77s/it, data_size=336, test_acc=0.915, train_acc=0.92]Test 4: Data size 368: : 50%|█████ | 5/10 [00:59<01:03, 12.77s/it, data_size=336, test_acc=0.915, train_acc=0.92]Test 4: Data size 368: : 50%|█████ | 5/10 [01:12<01:03, 12.77s/it, data_size=368, test_acc=0.91, train_acc=0.916]Test 4: Data size 368: : 60%|██████ | 6/10 [01:12<00:52, 13.14s/it, data_size=368, test_acc=0.91, train_acc=0.916]Test 4: Data size 400: : 60%|██████ | 6/10 [01:12<00:52, 13.14s/it, data_size=368, test_acc=0.91, train_acc=0.916]Test 4: Data size 400: : 60%|██████ | 6/10 [01:31<00:52, 13.14s/it, data_size=400, test_acc=0.879, train_acc=0.902]Test 4: Data size 400: : 70%|███████ | 7/10 [01:31<00:44, 14.95s/it, data_size=400, test_acc=0.879, train_acc=0.902]Test 4: Data size 432: : 70%|███████ | 7/10 [01:31<00:44, 14.95s/it, data_size=400, test_acc=0.879, train_acc=0.902]Test 4: Data size 432: : 70%|███████ | 7/10 [01:50<00:44, 14.95s/it, data_size=432, test_acc=0.926, train_acc=0.891]Test 4: Data size 432: : 80%|████████ | 8/10 [01:51<00:32, 16.38s/it, data_size=432, test_acc=0.926, train_acc=0.891]Test 4: Data size 464: : 80%|████████ | 8/10 [01:51<00:32, 16.38s/it, data_size=432, test_acc=0.926, train_acc=0.891]Test 4: Data size 464: : 80%|████████ | 8/10 [02:09<00:32, 16.38s/it, data_size=464, test_acc=0.909, train_acc=0.905]Test 4: Data size 464: : 90%|█████████ | 9/10 [02:09<00:17, 17.14s/it, data_size=464, test_acc=0.909, train_acc=0.905]Test 4: Data size 496: : 90%|█████████ | 9/10 [02:09<00:17, 17.14s/it, data_size=464, test_acc=0.909, train_acc=0.905]Test 4: Data size 496: : 90%|█████████ | 9/10 [02:28<00:17, 17.14s/it, data_size=496, test_acc=0.919, train_acc=0.885]Test 4: Data size 496: : 100%|██████████| 10/10 [02:29<00:00, 17.78s/it, data_size=496, test_acc=0.919, train_acc=0.885]Test 4: Data size 496: : 100%|██████████| 10/10 [02:29<00:00, 14.91s/it, data_size=496, test_acc=0.919, train_acc=0.885]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:08<?, ?it/s, data_size=208, test_acc=0.495, train_acc=0.5]Test 5: Data size 208: : 10%|█ | 1/10 [00:08<01:18, 8.68s/it, data_size=208, test_acc=0.495, train_acc=0.5]Test 5: Data size 240: : 10%|█ | 1/10 [00:08<01:18, 8.68s/it, data_size=208, test_acc=0.495, train_acc=0.5]Test 5: Data size 240: : 10%|█ | 1/10 [00:17<01:18, 8.68s/it, data_size=240, test_acc=0.589, train_acc=0.703]Test 5: Data size 240: : 20%|██ | 2/10 [00:17<01:10, 8.76s/it, data_size=240, test_acc=0.589, train_acc=0.703]Test 5: Data size 272: : 20%|██ | 2/10 [00:17<01:10, 8.76s/it, data_size=240, test_acc=0.589, train_acc=0.703]Test 5: Data size 272: : 20%|██ | 2/10 [00:30<01:10, 8.76s/it, data_size=272, test_acc=0.763, train_acc=0.889]Test 5: Data size 272: : 30%|███ | 3/10 [00:30<01:15, 10.86s/it, data_size=272, test_acc=0.763, train_acc=0.889]Test 5: Data size 304: : 30%|███ | 3/10 [00:30<01:15, 10.86s/it, data_size=272, test_acc=0.763, train_acc=0.889]Test 5: Data size 304: : 30%|███ | 3/10 [00:44<01:15, 10.86s/it, data_size=304, test_acc=0.796, train_acc=0.898]Test 5: Data size 304: : 40%|████ | 4/10 [00:44<01:11, 11.89s/it, data_size=304, test_acc=0.796, train_acc=0.898]Test 5: Data size 336: : 40%|████ | 4/10 [00:44<01:11, 11.89s/it, data_size=304, test_acc=0.796, train_acc=0.898]Test 5: Data size 336: : 40%|████ | 4/10 [00:57<01:11, 11.89s/it, data_size=336, test_acc=0.858, train_acc=0.937]Test 5: Data size 336: : 50%|█████ | 5/10 [00:58<01:02, 12.55s/it, data_size=336, test_acc=0.858, train_acc=0.937]Test 5: Data size 368: : 50%|█████ | 5/10 [00:58<01:02, 12.55s/it, data_size=336, test_acc=0.858, train_acc=0.937]Test 5: Data size 368: : 50%|█████ | 5/10 [01:11<01:02, 12.55s/it, data_size=368, test_acc=0.858, train_acc=0.908]Test 5: Data size 368: : 60%|██████ | 6/10 [01:11<00:51, 12.96s/it, data_size=368, test_acc=0.858, train_acc=0.908]Test 5: Data size 400: : 60%|██████ | 6/10 [01:11<00:51, 12.96s/it, data_size=368, test_acc=0.858, train_acc=0.908]Test 5: Data size 400: : 60%|██████ | 6/10 [01:30<00:51, 12.96s/it, data_size=400, test_acc=0.882, train_acc=0.931]Test 5: Data size 400: : 70%|███████ | 7/10 [01:30<00:44, 14.94s/it, data_size=400, test_acc=0.882, train_acc=0.931]Test 5: Data size 432: : 70%|███████ | 7/10 [01:30<00:44, 14.94s/it, data_size=400, test_acc=0.882, train_acc=0.931]Test 5: Data size 432: : 70%|███████ | 7/10 [01:49<00:44, 14.94s/it, data_size=432, test_acc=0.88, train_acc=0.934] Test 5: Data size 432: : 80%|████████ | 8/10 [01:49<00:32, 16.02s/it, data_size=432, test_acc=0.88, train_acc=0.934]Test 5: Data size 464: : 80%|████████ | 8/10 [01:49<00:32, 16.02s/it, data_size=432, test_acc=0.88, train_acc=0.934]Test 5: Data size 464: : 80%|████████ | 8/10 [02:08<00:32, 16.02s/it, data_size=464, test_acc=0.877, train_acc=0.929]Test 5: Data size 464: : 90%|█████████ | 9/10 [02:08<00:17, 17.18s/it, data_size=464, test_acc=0.877, train_acc=0.929]Test 5: Data size 496: : 90%|█████████ | 9/10 [02:08<00:17, 17.18s/it, data_size=464, test_acc=0.877, train_acc=0.929]Test 5: Data size 496: : 90%|█████████ | 9/10 [02:27<00:17, 17.18s/it, data_size=496, test_acc=0.881, train_acc=0.92] Test 5: Data size 496: : 100%|██████████| 10/10 [02:27<00:00, 17.77s/it, data_size=496, test_acc=0.881, train_acc=0.92]Test 5: Data size 496: : 100%|██████████| 10/10 [02:27<00:00, 14.80s/it, data_size=496, test_acc=0.881, train_acc=0.92]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:08<?, ?it/s, data_size=208, test_acc=0.498, train_acc=0.497]Test 6: Data size 208: : 10%|█ | 1/10 [00:08<01:18, 8.73s/it, data_size=208, test_acc=0.498, train_acc=0.497]Test 6: Data size 240: : 10%|█ | 1/10 [00:08<01:18, 8.73s/it, data_size=208, test_acc=0.498, train_acc=0.497]Test 6: Data size 240: : 10%|█ | 1/10 [00:17<01:18, 8.73s/it, data_size=240, test_acc=0.686, train_acc=0.761]Test 6: Data size 240: : 20%|██ | 2/10 [00:17<01:09, 8.74s/it, data_size=240, test_acc=0.686, train_acc=0.761]Test 6: Data size 272: : 20%|██ | 2/10 [00:17<01:09, 8.74s/it, data_size=240, test_acc=0.686, train_acc=0.761]Test 6: Data size 272: : 20%|██ | 2/10 [00:30<01:09, 8.74s/it, data_size=272, test_acc=0.743, train_acc=0.848]Test 6: Data size 272: : 30%|███ | 3/10 [00:30<01:15, 10.83s/it, data_size=272, test_acc=0.743, train_acc=0.848]Test 6: Data size 304: : 30%|███ | 3/10 [00:30<01:15, 10.83s/it, data_size=272, test_acc=0.743, train_acc=0.848]Test 6: Data size 304: : 30%|███ | 3/10 [00:44<01:15, 10.83s/it, data_size=304, test_acc=0.725, train_acc=0.832]Test 6: Data size 304: : 40%|████ | 4/10 [00:44<01:10, 11.82s/it, data_size=304, test_acc=0.725, train_acc=0.832]Test 6: Data size 336: : 40%|████ | 4/10 [00:44<01:10, 11.82s/it, data_size=304, test_acc=0.725, train_acc=0.832]Test 6: Data size 336: : 40%|████ | 4/10 [00:58<01:10, 11.82s/it, data_size=336, test_acc=0.753, train_acc=0.872]Test 6: Data size 336: : 50%|█████ | 5/10 [00:58<01:03, 12.67s/it, data_size=336, test_acc=0.753, train_acc=0.872]Test 6: Data size 368: : 50%|█████ | 5/10 [00:58<01:03, 12.67s/it, data_size=336, test_acc=0.753, train_acc=0.872]Test 6: Data size 368: : 50%|█████ | 5/10 [01:12<01:03, 12.67s/it, data_size=368, test_acc=0.87, train_acc=0.928] Test 6: Data size 368: : 60%|██████ | 6/10 [01:12<00:52, 13.21s/it, data_size=368, test_acc=0.87, train_acc=0.928]Test 6: Data size 400: : 60%|██████ | 6/10 [01:12<00:52, 13.21s/it, data_size=368, test_acc=0.87, train_acc=0.928]Test 6: Data size 400: : 60%|██████ | 6/10 [01:31<00:52, 13.21s/it, data_size=400, test_acc=0.882, train_acc=0.909]Test 6: Data size 400: : 70%|███████ | 7/10 [01:31<00:45, 15.11s/it, data_size=400, test_acc=0.882, train_acc=0.909]Test 6: Data size 432: : 70%|███████ | 7/10 [01:31<00:45, 15.11s/it, data_size=400, test_acc=0.882, train_acc=0.909]Test 6: Data size 432: : 70%|███████ | 7/10 [01:50<00:45, 15.11s/it, data_size=432, test_acc=0.903, train_acc=0.923]Test 6: Data size 432: : 80%|████████ | 8/10 [01:50<00:32, 16.29s/it, data_size=432, test_acc=0.903, train_acc=0.923]Test 6: Data size 464: : 80%|████████ | 8/10 [01:50<00:32, 16.29s/it, data_size=432, test_acc=0.903, train_acc=0.923]Test 6: Data size 464: : 80%|████████ | 8/10 [02:09<00:32, 16.29s/it, data_size=464, test_acc=0.902, train_acc=0.912]Test 6: Data size 464: : 90%|█████████ | 9/10 [02:09<00:17, 17.13s/it, data_size=464, test_acc=0.902, train_acc=0.912]Test 6: Data size 496: : 90%|█████████ | 9/10 [02:09<00:17, 17.13s/it, data_size=464, test_acc=0.902, train_acc=0.912]Test 6: Data size 496: : 90%|█████████ | 9/10 [02:28<00:17, 17.13s/it, data_size=496, test_acc=0.912, train_acc=0.915]Test 6: Data size 496: : 100%|██████████| 10/10 [02:28<00:00, 17.78s/it, data_size=496, test_acc=0.912, train_acc=0.915]Test 6: Data size 496: : 100%|██████████| 10/10 [02:28<00:00, 14.86s/it, data_size=496, test_acc=0.912, train_acc=0.915]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:09<?, ?it/s, data_size=208, test_acc=0.5, train_acc=0.5]Test 7: Data size 208: : 10%|█ | 1/10 [00:09<01:24, 9.36s/it, data_size=208, test_acc=0.5, train_acc=0.5]Test 7: Data size 240: : 10%|█ | 1/10 [00:09<01:24, 9.36s/it, data_size=208, test_acc=0.5, train_acc=0.5]Test 7: Data size 240: : 10%|█ | 1/10 [00:18<01:24, 9.36s/it, data_size=240, test_acc=0.691, train_acc=0.754]Test 7: Data size 240: : 20%|██ | 2/10 [00:18<01:14, 9.33s/it, data_size=240, test_acc=0.691, train_acc=0.754]Test 7: Data size 272: : 20%|██ | 2/10 [00:18<01:14, 9.33s/it, data_size=240, test_acc=0.691, train_acc=0.754]Test 7: Data size 272: : 20%|██ | 2/10 [00:33<01:14, 9.33s/it, data_size=272, test_acc=0.73, train_acc=0.799] Test 7: Data size 272: : 30%|███ | 3/10 [00:33<01:21, 11.69s/it, data_size=272, test_acc=0.73, train_acc=0.799]Test 7: Data size 304: : 30%|███ | 3/10 [00:33<01:21, 11.69s/it, data_size=272, test_acc=0.73, train_acc=0.799]Test 7: Data size 304: : 30%|███ | 3/10 [00:47<01:21, 11.69s/it, data_size=304, test_acc=0.746, train_acc=0.776]Test 7: Data size 304: : 40%|████ | 4/10 [00:47<01:15, 12.66s/it, data_size=304, test_acc=0.746, train_acc=0.776]Test 7: Data size 336: : 40%|████ | 4/10 [00:47<01:15, 12.66s/it, data_size=304, test_acc=0.746, train_acc=0.776]Test 7: Data size 336: : 40%|████ | 4/10 [01:01<01:15, 12.66s/it, data_size=336, test_acc=0.715, train_acc=0.793]Test 7: Data size 336: : 50%|█████ | 5/10 [01:01<01:06, 13.23s/it, data_size=336, test_acc=0.715, train_acc=0.793]Test 7: Data size 368: : 50%|█████ | 5/10 [01:01<01:06, 13.23s/it, data_size=336, test_acc=0.715, train_acc=0.793]Test 7: Data size 368: : 50%|█████ | 5/10 [01:15<01:06, 13.23s/it, data_size=368, test_acc=0.73, train_acc=0.837] Test 7: Data size 368: : 60%|██████ | 6/10 [01:15<00:54, 13.64s/it, data_size=368, test_acc=0.73, train_acc=0.837]Test 7: Data size 400: : 60%|██████ | 6/10 [01:15<00:54, 13.64s/it, data_size=368, test_acc=0.73, train_acc=0.837]Test 7: Data size 400: : 60%|██████ | 6/10 [01:34<00:54, 13.64s/it, data_size=400, test_acc=0.862, train_acc=0.908]Test 7: Data size 400: : 70%|███████ | 7/10 [01:34<00:46, 15.34s/it, data_size=400, test_acc=0.862, train_acc=0.908]Test 7: Data size 432: : 70%|███████ | 7/10 [01:34<00:46, 15.34s/it, data_size=400, test_acc=0.862, train_acc=0.908]Test 7: Data size 432: : 70%|███████ | 7/10 [01:53<00:46, 15.34s/it, data_size=432, test_acc=0.888, train_acc=0.934]Test 7: Data size 432: : 80%|████████ | 8/10 [01:53<00:32, 16.49s/it, data_size=432, test_acc=0.888, train_acc=0.934]Test 7: Data size 464: : 80%|████████ | 8/10 [01:53<00:32, 16.49s/it, data_size=432, test_acc=0.888, train_acc=0.934]Test 7: Data size 464: : 80%|████████ | 8/10 [02:12<00:32, 16.49s/it, data_size=464, test_acc=0.9, train_acc=0.911] Test 7: Data size 464: : 90%|█████████ | 9/10 [02:12<00:17, 17.27s/it, data_size=464, test_acc=0.9, train_acc=0.911]Test 7: Data size 496: : 90%|█████████ | 9/10 [02:12<00:17, 17.27s/it, data_size=464, test_acc=0.9, train_acc=0.911]Test 7: Data size 496: : 90%|█████████ | 9/10 [02:31<00:17, 17.27s/it, data_size=496, test_acc=0.904, train_acc=0.927]Test 7: Data size 496: : 100%|██████████| 10/10 [02:31<00:00, 17.61s/it, data_size=496, test_acc=0.904, train_acc=0.927]Test 7: Data size 496: : 100%|██████████| 10/10 [02:31<00:00, 15.11s/it, data_size=496, test_acc=0.904, train_acc=0.927]
working on model Multimodal-late-fusion-model-based-on-AlexNet with CLUSTER_MARGIN
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:21<?, ?it/s, data_size=208, test_acc=0.481, train_acc=0.482]Test 0: Data size 208: : 10%|█ | 1/10 [00:21<03:12, 21.35s/it, data_size=208, test_acc=0.481, train_acc=0.482]Test 0: Data size 240: : 10%|█ | 1/10 [00:21<03:12, 21.35s/it, data_size=208, test_acc=0.481, train_acc=0.482]Test 0: Data size 240: : 10%|█ | 1/10 [00:30<03:12, 21.35s/it, data_size=240, test_acc=0.637, train_acc=0.719]Test 0: Data size 240: : 20%|██ | 2/10 [00:30<01:54, 14.37s/it, data_size=240, test_acc=0.637, train_acc=0.719]Test 0: Data size 272: : 20%|██ | 2/10 [00:30<01:54, 14.37s/it, data_size=240, test_acc=0.637, train_acc=0.719]Test 0: Data size 272: : 20%|██ | 2/10 [00:45<01:54, 14.37s/it, data_size=272, test_acc=0.739, train_acc=0.817]Test 0: Data size 272: : 30%|███ | 3/10 [00:45<01:40, 14.42s/it, data_size=272, test_acc=0.739, train_acc=0.817]Test 0: Data size 304: : 30%|███ | 3/10 [00:45<01:40, 14.42s/it, data_size=272, test_acc=0.739, train_acc=0.817]Test 0: Data size 304: : 30%|███ | 3/10 [00:59<01:40, 14.42s/it, data_size=304, test_acc=0.797, train_acc=0.851]Test 0: Data size 304: : 40%|████ | 4/10 [00:59<01:26, 14.44s/it, data_size=304, test_acc=0.797, train_acc=0.851]Test 0: Data size 336: : 40%|████ | 4/10 [00:59<01:26, 14.44s/it, data_size=304, test_acc=0.797, train_acc=0.851]Test 0: Data size 336: : 40%|████ | 4/10 [01:14<01:26, 14.44s/it, data_size=336, test_acc=0.782, train_acc=0.81] Test 0: Data size 336: : 50%|█████ | 5/10 [01:14<01:12, 14.42s/it, data_size=336, test_acc=0.782, train_acc=0.81]Test 0: Data size 368: : 50%|█████ | 5/10 [01:14<01:12, 14.42s/it, data_size=336, test_acc=0.782, train_acc=0.81]Test 0: Data size 368: : 50%|█████ | 5/10 [01:28<01:12, 14.42s/it, data_size=368, test_acc=0.805, train_acc=0.854]Test 0: Data size 368: : 60%|██████ | 6/10 [01:28<00:58, 14.55s/it, data_size=368, test_acc=0.805, train_acc=0.854]Test 0: Data size 400: : 60%|██████ | 6/10 [01:28<00:58, 14.55s/it, data_size=368, test_acc=0.805, train_acc=0.854]Test 0: Data size 400: : 60%|██████ | 6/10 [01:48<00:58, 14.55s/it, data_size=400, test_acc=0.873, train_acc=0.895]Test 0: Data size 400: : 70%|███████ | 7/10 [01:48<00:48, 16.14s/it, data_size=400, test_acc=0.873, train_acc=0.895]Test 0: Data size 432: : 70%|███████ | 7/10 [01:48<00:48, 16.14s/it, data_size=400, test_acc=0.873, train_acc=0.895]Test 0: Data size 432: : 70%|███████ | 7/10 [02:07<00:48, 16.14s/it, data_size=432, test_acc=0.888, train_acc=0.903]Test 0: Data size 432: : 80%|████████ | 8/10 [02:07<00:34, 17.09s/it, data_size=432, test_acc=0.888, train_acc=0.903]Test 0: Data size 464: : 80%|████████ | 8/10 [02:07<00:34, 17.09s/it, data_size=432, test_acc=0.888, train_acc=0.903]Test 0: Data size 464: : 80%|████████ | 8/10 [02:26<00:34, 17.09s/it, data_size=464, test_acc=0.858, train_acc=0.862]Test 0: Data size 464: : 90%|█████████ | 9/10 [02:26<00:17, 17.73s/it, data_size=464, test_acc=0.858, train_acc=0.862]Test 0: Data size 496: : 90%|█████████ | 9/10 [02:26<00:17, 17.73s/it, data_size=464, test_acc=0.858, train_acc=0.862]Test 0: Data size 496: : 90%|█████████ | 9/10 [02:46<00:17, 17.73s/it, data_size=496, test_acc=0.911, train_acc=0.899]Test 0: Data size 496: : 100%|██████████| 10/10 [02:46<00:00, 18.30s/it, data_size=496, test_acc=0.911, train_acc=0.899]Test 0: Data size 496: : 100%|██████████| 10/10 [02:46<00:00, 16.62s/it, data_size=496, test_acc=0.911, train_acc=0.899]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:21<?, ?it/s, data_size=208, test_acc=0.497, train_acc=0.49]Test 1: Data size 208: : 10%|█ | 1/10 [00:21<03:13, 21.45s/it, data_size=208, test_acc=0.497, train_acc=0.49]Test 1: Data size 240: : 10%|█ | 1/10 [00:21<03:13, 21.45s/it, data_size=208, test_acc=0.497, train_acc=0.49]Test 1: Data size 240: : 10%|█ | 1/10 [00:30<03:13, 21.45s/it, data_size=240, test_acc=0.658, train_acc=0.761]Test 1: Data size 240: : 20%|██ | 2/10 [00:31<01:56, 14.50s/it, data_size=240, test_acc=0.658, train_acc=0.761]Test 1: Data size 272: : 20%|██ | 2/10 [00:31<01:56, 14.50s/it, data_size=240, test_acc=0.658, train_acc=0.761]Test 1: Data size 272: : 20%|██ | 2/10 [00:45<01:56, 14.50s/it, data_size=272, test_acc=0.77, train_acc=0.834] Test 1: Data size 272: : 30%|███ | 3/10 [00:45<01:41, 14.47s/it, data_size=272, test_acc=0.77, train_acc=0.834]Test 1: Data size 304: : 30%|███ | 3/10 [00:45<01:41, 14.47s/it, data_size=272, test_acc=0.77, train_acc=0.834]Test 1: Data size 304: : 30%|███ | 3/10 [00:59<01:41, 14.47s/it, data_size=304, test_acc=0.771, train_acc=0.839]Test 1: Data size 304: : 40%|████ | 4/10 [00:59<01:26, 14.40s/it, data_size=304, test_acc=0.771, train_acc=0.839]Test 1: Data size 336: : 40%|████ | 4/10 [00:59<01:26, 14.40s/it, data_size=304, test_acc=0.771, train_acc=0.839]Test 1: Data size 336: : 40%|████ | 4/10 [01:13<01:26, 14.40s/it, data_size=336, test_acc=0.773, train_acc=0.84] Test 1: Data size 336: : 50%|█████ | 5/10 [01:14<01:11, 14.34s/it, data_size=336, test_acc=0.773, train_acc=0.84]Test 1: Data size 368: : 50%|█████ | 5/10 [01:14<01:11, 14.34s/it, data_size=336, test_acc=0.773, train_acc=0.84]Test 1: Data size 368: : 50%|█████ | 5/10 [01:28<01:11, 14.34s/it, data_size=368, test_acc=0.772, train_acc=0.801]Test 1: Data size 368: : 60%|██████ | 6/10 [01:28<00:57, 14.35s/it, data_size=368, test_acc=0.772, train_acc=0.801]Test 1: Data size 400: : 60%|██████ | 6/10 [01:28<00:57, 14.35s/it, data_size=368, test_acc=0.772, train_acc=0.801]Test 1: Data size 400: : 60%|██████ | 6/10 [01:47<00:57, 14.35s/it, data_size=400, test_acc=0.86, train_acc=0.876] Test 1: Data size 400: : 70%|███████ | 7/10 [01:47<00:47, 15.83s/it, data_size=400, test_acc=0.86, train_acc=0.876]Test 1: Data size 432: : 70%|███████ | 7/10 [01:47<00:47, 15.83s/it, data_size=400, test_acc=0.86, train_acc=0.876]Test 1: Data size 432: : 70%|███████ | 7/10 [02:06<00:47, 15.83s/it, data_size=432, test_acc=0.884, train_acc=0.866]Test 1: Data size 432: : 80%|████████ | 8/10 [02:06<00:33, 16.95s/it, data_size=432, test_acc=0.884, train_acc=0.866]Test 1: Data size 464: : 80%|████████ | 8/10 [02:06<00:33, 16.95s/it, data_size=432, test_acc=0.884, train_acc=0.866]Test 1: Data size 464: : 80%|████████ | 8/10 [02:25<00:33, 16.95s/it, data_size=464, test_acc=0.894, train_acc=0.893]Test 1: Data size 464: : 90%|█████████ | 9/10 [02:25<00:17, 17.45s/it, data_size=464, test_acc=0.894, train_acc=0.893]Test 1: Data size 496: : 90%|█████████ | 9/10 [02:25<00:17, 17.45s/it, data_size=464, test_acc=0.894, train_acc=0.893]Test 1: Data size 496: : 90%|█████████ | 9/10 [02:44<00:17, 17.45s/it, data_size=496, test_acc=0.903, train_acc=0.902]Test 1: Data size 496: : 100%|██████████| 10/10 [02:44<00:00, 18.02s/it, data_size=496, test_acc=0.903, train_acc=0.902]Test 1: Data size 496: : 100%|██████████| 10/10 [02:44<00:00, 16.45s/it, data_size=496, test_acc=0.903, train_acc=0.902]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:21<?, ?it/s, data_size=208, test_acc=0.498, train_acc=0.5]Test 2: Data size 208: : 10%|█ | 1/10 [00:21<03:14, 21.56s/it, data_size=208, test_acc=0.498, train_acc=0.5]Test 2: Data size 240: : 10%|█ | 1/10 [00:21<03:14, 21.56s/it, data_size=208, test_acc=0.498, train_acc=0.5]Test 2: Data size 240: : 10%|█ | 1/10 [00:30<03:14, 21.56s/it, data_size=240, test_acc=0.513, train_acc=0.588]Test 2: Data size 240: : 20%|██ | 2/10 [00:31<01:55, 14.48s/it, data_size=240, test_acc=0.513, train_acc=0.588]Test 2: Data size 272: : 20%|██ | 2/10 [00:31<01:55, 14.48s/it, data_size=240, test_acc=0.513, train_acc=0.588]Test 2: Data size 272: : 20%|██ | 2/10 [00:45<01:55, 14.48s/it, data_size=272, test_acc=0.746, train_acc=0.857]Test 2: Data size 272: : 30%|███ | 3/10 [00:45<01:41, 14.43s/it, data_size=272, test_acc=0.746, train_acc=0.857]Test 2: Data size 304: : 30%|███ | 3/10 [00:45<01:41, 14.43s/it, data_size=272, test_acc=0.746, train_acc=0.857]Test 2: Data size 304: : 30%|███ | 3/10 [00:59<01:41, 14.43s/it, data_size=304, test_acc=0.682, train_acc=0.8] Test 2: Data size 304: : 40%|████ | 4/10 [00:59<01:26, 14.39s/it, data_size=304, test_acc=0.682, train_acc=0.8]Test 2: Data size 336: : 40%|████ | 4/10 [00:59<01:26, 14.39s/it, data_size=304, test_acc=0.682, train_acc=0.8]Test 2: Data size 336: : 40%|████ | 4/10 [01:13<01:26, 14.39s/it, data_size=336, test_acc=0.764, train_acc=0.81]Test 2: Data size 336: : 50%|█████ | 5/10 [01:14<01:11, 14.35s/it, data_size=336, test_acc=0.764, train_acc=0.81]Test 2: Data size 368: : 50%|█████ | 5/10 [01:14<01:11, 14.35s/it, data_size=336, test_acc=0.764, train_acc=0.81]Test 2: Data size 368: : 50%|█████ | 5/10 [01:28<01:11, 14.35s/it, data_size=368, test_acc=0.873, train_acc=0.851]Test 2: Data size 368: : 60%|██████ | 6/10 [01:28<00:57, 14.33s/it, data_size=368, test_acc=0.873, train_acc=0.851]Test 2: Data size 400: : 60%|██████ | 6/10 [01:28<00:57, 14.33s/it, data_size=368, test_acc=0.873, train_acc=0.851]Test 2: Data size 400: : 60%|██████ | 6/10 [01:47<00:57, 14.33s/it, data_size=400, test_acc=0.837, train_acc=0.848]Test 2: Data size 400: : 70%|███████ | 7/10 [01:47<00:47, 15.95s/it, data_size=400, test_acc=0.837, train_acc=0.848]Test 2: Data size 432: : 70%|███████ | 7/10 [01:47<00:47, 15.95s/it, data_size=400, test_acc=0.837, train_acc=0.848]Test 2: Data size 432: : 70%|███████ | 7/10 [02:06<00:47, 15.95s/it, data_size=432, test_acc=0.842, train_acc=0.862]Test 2: Data size 432: : 80%|████████ | 8/10 [02:06<00:33, 16.94s/it, data_size=432, test_acc=0.842, train_acc=0.862]Test 2: Data size 464: : 80%|████████ | 8/10 [02:06<00:33, 16.94s/it, data_size=432, test_acc=0.842, train_acc=0.862]Test 2: Data size 464: : 80%|████████ | 8/10 [02:25<00:33, 16.94s/it, data_size=464, test_acc=0.872, train_acc=0.861]Test 2: Data size 464: : 90%|█████████ | 9/10 [02:25<00:17, 17.68s/it, data_size=464, test_acc=0.872, train_acc=0.861]Test 2: Data size 496: : 90%|█████████ | 9/10 [02:25<00:17, 17.68s/it, data_size=464, test_acc=0.872, train_acc=0.861]Test 2: Data size 496: : 90%|█████████ | 9/10 [02:45<00:17, 17.68s/it, data_size=496, test_acc=0.906, train_acc=0.913]Test 2: Data size 496: : 100%|██████████| 10/10 [02:45<00:00, 18.25s/it, data_size=496, test_acc=0.906, train_acc=0.913]Test 2: Data size 496: : 100%|██████████| 10/10 [02:45<00:00, 16.55s/it, data_size=496, test_acc=0.906, train_acc=0.913]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:21<?, ?it/s, data_size=208, test_acc=0.496, train_acc=0.489]Test 3: Data size 208: : 10%|█ | 1/10 [00:21<03:10, 21.17s/it, data_size=208, test_acc=0.496, train_acc=0.489]Test 3: Data size 240: : 10%|█ | 1/10 [00:21<03:10, 21.17s/it, data_size=208, test_acc=0.496, train_acc=0.489]Test 3: Data size 240: : 10%|█ | 1/10 [00:30<03:10, 21.17s/it, data_size=240, test_acc=0.74, train_acc=0.825] Test 3: Data size 240: : 20%|██ | 2/10 [00:30<01:53, 14.20s/it, data_size=240, test_acc=0.74, train_acc=0.825]Test 3: Data size 272: : 20%|██ | 2/10 [00:30<01:53, 14.20s/it, data_size=240, test_acc=0.74, train_acc=0.825]Test 3: Data size 272: : 20%|██ | 2/10 [00:44<01:53, 14.20s/it, data_size=272, test_acc=0.786, train_acc=0.846]Test 3: Data size 272: : 30%|███ | 3/10 [00:44<01:39, 14.18s/it, data_size=272, test_acc=0.786, train_acc=0.846]Test 3: Data size 304: : 30%|███ | 3/10 [00:44<01:39, 14.18s/it, data_size=272, test_acc=0.786, train_acc=0.846]Test 3: Data size 304: : 30%|███ | 3/10 [00:58<01:39, 14.18s/it, data_size=304, test_acc=0.793, train_acc=0.856]Test 3: Data size 304: : 40%|████ | 4/10 [00:58<01:25, 14.20s/it, data_size=304, test_acc=0.793, train_acc=0.856]Test 3: Data size 336: : 40%|████ | 4/10 [00:58<01:25, 14.20s/it, data_size=304, test_acc=0.793, train_acc=0.856]Test 3: Data size 336: : 40%|████ | 4/10 [01:13<01:25, 14.20s/it, data_size=336, test_acc=0.782, train_acc=0.864]Test 3: Data size 336: : 50%|█████ | 5/10 [01:13<01:11, 14.29s/it, data_size=336, test_acc=0.782, train_acc=0.864]Test 3: Data size 368: : 50%|█████ | 5/10 [01:13<01:11, 14.29s/it, data_size=336, test_acc=0.782, train_acc=0.864]Test 3: Data size 368: : 50%|█████ | 5/10 [01:28<01:11, 14.29s/it, data_size=368, test_acc=0.833, train_acc=0.885]Test 3: Data size 368: : 60%|██████ | 6/10 [01:28<00:57, 14.50s/it, data_size=368, test_acc=0.833, train_acc=0.885]Test 3: Data size 400: : 60%|██████ | 6/10 [01:28<00:57, 14.50s/it, data_size=368, test_acc=0.833, train_acc=0.885]Test 3: Data size 400: : 60%|██████ | 6/10 [01:47<00:57, 14.50s/it, data_size=400, test_acc=0.877, train_acc=0.923]Test 3: Data size 400: : 70%|███████ | 7/10 [01:47<00:48, 16.16s/it, data_size=400, test_acc=0.877, train_acc=0.923]Test 3: Data size 432: : 70%|███████ | 7/10 [01:47<00:48, 16.16s/it, data_size=400, test_acc=0.877, train_acc=0.923]Test 3: Data size 432: : 70%|███████ | 7/10 [02:06<00:48, 16.16s/it, data_size=432, test_acc=0.884, train_acc=0.936]Test 3: Data size 432: : 80%|████████ | 8/10 [02:06<00:33, 16.93s/it, data_size=432, test_acc=0.884, train_acc=0.936]Test 3: Data size 464: : 80%|████████ | 8/10 [02:06<00:33, 16.93s/it, data_size=432, test_acc=0.884, train_acc=0.936]Test 3: Data size 464: : 80%|████████ | 8/10 [02:25<00:33, 16.93s/it, data_size=464, test_acc=0.89, train_acc=0.896] Test 3: Data size 464: : 90%|█████████ | 9/10 [02:25<00:17, 17.67s/it, data_size=464, test_acc=0.89, train_acc=0.896]Test 3: Data size 496: : 90%|█████████ | 9/10 [02:25<00:17, 17.67s/it, data_size=464, test_acc=0.89, train_acc=0.896]Test 3: Data size 496: : 90%|█████████ | 9/10 [02:44<00:17, 17.67s/it, data_size=496, test_acc=0.893, train_acc=0.886]Test 3: Data size 496: : 100%|██████████| 10/10 [02:45<00:00, 18.19s/it, data_size=496, test_acc=0.893, train_acc=0.886]Test 3: Data size 496: : 100%|██████████| 10/10 [02:45<00:00, 16.50s/it, data_size=496, test_acc=0.893, train_acc=0.886]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:21<?, ?it/s, data_size=208, test_acc=0.493, train_acc=0.485]Test 4: Data size 208: : 10%|█ | 1/10 [00:21<03:16, 21.85s/it, data_size=208, test_acc=0.493, train_acc=0.485]Test 4: Data size 240: : 10%|█ | 1/10 [00:21<03:16, 21.85s/it, data_size=208, test_acc=0.493, train_acc=0.485]Test 4: Data size 240: : 10%|█ | 1/10 [00:31<03:16, 21.85s/it, data_size=240, test_acc=0.689, train_acc=0.697]Test 4: Data size 240: : 20%|██ | 2/10 [00:31<01:57, 14.65s/it, data_size=240, test_acc=0.689, train_acc=0.697]Test 4: Data size 272: : 20%|██ | 2/10 [00:31<01:57, 14.65s/it, data_size=240, test_acc=0.689, train_acc=0.697]Test 4: Data size 272: : 20%|██ | 2/10 [00:45<01:57, 14.65s/it, data_size=272, test_acc=0.813, train_acc=0.888]Test 4: Data size 272: : 30%|███ | 3/10 [00:46<01:42, 14.60s/it, data_size=272, test_acc=0.813, train_acc=0.888]Test 4: Data size 304: : 30%|███ | 3/10 [00:46<01:42, 14.60s/it, data_size=272, test_acc=0.813, train_acc=0.888]Test 4: Data size 304: : 30%|███ | 3/10 [01:00<01:42, 14.60s/it, data_size=304, test_acc=0.816, train_acc=0.868]Test 4: Data size 304: : 40%|████ | 4/10 [01:00<01:27, 14.57s/it, data_size=304, test_acc=0.816, train_acc=0.868]Test 4: Data size 336: : 40%|████ | 4/10 [01:00<01:27, 14.57s/it, data_size=304, test_acc=0.816, train_acc=0.868]Test 4: Data size 336: : 40%|████ | 4/10 [01:14<01:27, 14.57s/it, data_size=336, test_acc=0.834, train_acc=0.863]Test 4: Data size 336: : 50%|█████ | 5/10 [01:15<01:12, 14.56s/it, data_size=336, test_acc=0.834, train_acc=0.863]Test 4: Data size 368: : 50%|█████ | 5/10 [01:15<01:12, 14.56s/it, data_size=336, test_acc=0.834, train_acc=0.863]Test 4: Data size 368: : 50%|█████ | 5/10 [01:29<01:12, 14.56s/it, data_size=368, test_acc=0.852, train_acc=0.913]Test 4: Data size 368: : 60%|██████ | 6/10 [01:29<00:58, 14.52s/it, data_size=368, test_acc=0.852, train_acc=0.913]Test 4: Data size 400: : 60%|██████ | 6/10 [01:29<00:58, 14.52s/it, data_size=368, test_acc=0.852, train_acc=0.913]Test 4: Data size 400: : 60%|██████ | 6/10 [01:48<00:58, 14.52s/it, data_size=400, test_acc=0.866, train_acc=0.902]Test 4: Data size 400: : 70%|███████ | 7/10 [01:49<00:48, 16.17s/it, data_size=400, test_acc=0.866, train_acc=0.902]Test 4: Data size 432: : 70%|███████ | 7/10 [01:49<00:48, 16.17s/it, data_size=400, test_acc=0.866, train_acc=0.902]Test 4: Data size 432: : 70%|███████ | 7/10 [02:08<00:48, 16.17s/it, data_size=432, test_acc=0.882, train_acc=0.93] Test 4: Data size 432: : 80%|████████ | 8/10 [02:08<00:34, 17.13s/it, data_size=432, test_acc=0.882, train_acc=0.93]Test 4: Data size 464: : 80%|████████ | 8/10 [02:08<00:34, 17.13s/it, data_size=432, test_acc=0.882, train_acc=0.93]Test 4: Data size 464: : 80%|████████ | 8/10 [02:27<00:34, 17.13s/it, data_size=464, test_acc=0.89, train_acc=0.927]Test 4: Data size 464: : 90%|█████████ | 9/10 [02:27<00:17, 17.88s/it, data_size=464, test_acc=0.89, train_acc=0.927]Test 4: Data size 496: : 90%|█████████ | 9/10 [02:27<00:17, 17.88s/it, data_size=464, test_acc=0.89, train_acc=0.927]Test 4: Data size 496: : 90%|█████████ | 9/10 [02:47<00:17, 17.88s/it, data_size=496, test_acc=0.862, train_acc=0.894]Test 4: Data size 496: : 100%|██████████| 10/10 [02:47<00:00, 18.38s/it, data_size=496, test_acc=0.862, train_acc=0.894]Test 4: Data size 496: : 100%|██████████| 10/10 [02:47<00:00, 16.73s/it, data_size=496, test_acc=0.862, train_acc=0.894]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:21<?, ?it/s, data_size=208, test_acc=0.495, train_acc=0.5]Test 5: Data size 208: : 10%|█ | 1/10 [00:21<03:15, 21.70s/it, data_size=208, test_acc=0.495, train_acc=0.5]Test 5: Data size 240: : 10%|█ | 1/10 [00:21<03:15, 21.70s/it, data_size=208, test_acc=0.495, train_acc=0.5]Test 5: Data size 240: : 10%|█ | 1/10 [00:31<03:15, 21.70s/it, data_size=240, test_acc=0.638, train_acc=0.738]Test 5: Data size 240: : 20%|██ | 2/10 [00:31<01:56, 14.56s/it, data_size=240, test_acc=0.638, train_acc=0.738]Test 5: Data size 272: : 20%|██ | 2/10 [00:31<01:56, 14.56s/it, data_size=240, test_acc=0.638, train_acc=0.738]Test 5: Data size 272: : 20%|██ | 2/10 [00:45<01:56, 14.56s/it, data_size=272, test_acc=0.758, train_acc=0.849]Test 5: Data size 272: : 30%|███ | 3/10 [00:45<01:41, 14.57s/it, data_size=272, test_acc=0.758, train_acc=0.849]Test 5: Data size 304: : 30%|███ | 3/10 [00:45<01:41, 14.57s/it, data_size=272, test_acc=0.758, train_acc=0.849]Test 5: Data size 304: : 30%|███ | 3/10 [01:00<01:41, 14.57s/it, data_size=304, test_acc=0.772, train_acc=0.873]Test 5: Data size 304: : 40%|████ | 4/10 [01:00<01:27, 14.61s/it, data_size=304, test_acc=0.772, train_acc=0.873]Test 5: Data size 336: : 40%|████ | 4/10 [01:00<01:27, 14.61s/it, data_size=304, test_acc=0.772, train_acc=0.873]Test 5: Data size 336: : 40%|████ | 4/10 [01:14<01:27, 14.61s/it, data_size=336, test_acc=0.786, train_acc=0.878]Test 5: Data size 336: : 50%|█████ | 5/10 [01:15<01:12, 14.58s/it, data_size=336, test_acc=0.786, train_acc=0.878]Test 5: Data size 368: : 50%|█████ | 5/10 [01:15<01:12, 14.58s/it, data_size=336, test_acc=0.786, train_acc=0.878]Test 5: Data size 368: : 50%|█████ | 5/10 [01:29<01:12, 14.58s/it, data_size=368, test_acc=0.759, train_acc=0.803]Test 5: Data size 368: : 60%|██████ | 6/10 [01:29<00:58, 14.57s/it, data_size=368, test_acc=0.759, train_acc=0.803]Test 5: Data size 400: : 60%|██████ | 6/10 [01:29<00:58, 14.57s/it, data_size=368, test_acc=0.759, train_acc=0.803]Test 5: Data size 400: : 60%|██████ | 6/10 [01:48<00:58, 14.57s/it, data_size=400, test_acc=0.85, train_acc=0.883] Test 5: Data size 400: : 70%|███████ | 7/10 [01:48<00:48, 16.06s/it, data_size=400, test_acc=0.85, train_acc=0.883]Test 5: Data size 432: : 70%|███████ | 7/10 [01:48<00:48, 16.06s/it, data_size=400, test_acc=0.85, train_acc=0.883]Test 5: Data size 432: : 70%|███████ | 7/10 [02:08<00:48, 16.06s/it, data_size=432, test_acc=0.882, train_acc=0.906]Test 5: Data size 432: : 80%|████████ | 8/10 [02:08<00:34, 17.18s/it, data_size=432, test_acc=0.882, train_acc=0.906]Test 5: Data size 464: : 80%|████████ | 8/10 [02:08<00:34, 17.18s/it, data_size=432, test_acc=0.882, train_acc=0.906]Test 5: Data size 464: : 80%|████████ | 8/10 [02:27<00:34, 17.18s/it, data_size=464, test_acc=0.88, train_acc=0.893] Test 5: Data size 464: : 90%|█████████ | 9/10 [02:27<00:17, 17.72s/it, data_size=464, test_acc=0.88, train_acc=0.893]Test 5: Data size 496: : 90%|█████████ | 9/10 [02:27<00:17, 17.72s/it, data_size=464, test_acc=0.88, train_acc=0.893]Test 5: Data size 496: : 90%|█████████ | 9/10 [02:47<00:17, 17.72s/it, data_size=496, test_acc=0.883, train_acc=0.927]Test 5: Data size 496: : 100%|██████████| 10/10 [02:47<00:00, 18.41s/it, data_size=496, test_acc=0.883, train_acc=0.927]Test 5: Data size 496: : 100%|██████████| 10/10 [02:47<00:00, 16.72s/it, data_size=496, test_acc=0.883, train_acc=0.927]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:21<?, ?it/s, data_size=208, test_acc=0.497, train_acc=0.497]Test 6: Data size 208: : 10%|█ | 1/10 [00:21<03:11, 21.32s/it, data_size=208, test_acc=0.497, train_acc=0.497]Test 6: Data size 240: : 10%|█ | 1/10 [00:21<03:11, 21.32s/it, data_size=208, test_acc=0.497, train_acc=0.497]Test 6: Data size 240: : 10%|█ | 1/10 [00:30<03:11, 21.32s/it, data_size=240, test_acc=0.592, train_acc=0.665]Test 6: Data size 240: : 20%|██ | 2/10 [00:30<01:54, 14.36s/it, data_size=240, test_acc=0.592, train_acc=0.665]Test 6: Data size 272: : 20%|██ | 2/10 [00:30<01:54, 14.36s/it, data_size=240, test_acc=0.592, train_acc=0.665]Test 6: Data size 272: : 20%|██ | 2/10 [00:44<01:54, 14.36s/it, data_size=272, test_acc=0.756, train_acc=0.829]Test 6: Data size 272: : 30%|███ | 3/10 [00:45<01:40, 14.33s/it, data_size=272, test_acc=0.756, train_acc=0.829]Test 6: Data size 304: : 30%|███ | 3/10 [00:45<01:40, 14.33s/it, data_size=272, test_acc=0.756, train_acc=0.829]Test 6: Data size 304: : 30%|███ | 3/10 [00:59<01:40, 14.33s/it, data_size=304, test_acc=0.725, train_acc=0.79] Test 6: Data size 304: : 40%|████ | 4/10 [00:59<01:25, 14.32s/it, data_size=304, test_acc=0.725, train_acc=0.79]Test 6: Data size 336: : 40%|████ | 4/10 [00:59<01:25, 14.32s/it, data_size=304, test_acc=0.725, train_acc=0.79]Test 6: Data size 336: : 40%|████ | 4/10 [01:13<01:25, 14.32s/it, data_size=336, test_acc=0.692, train_acc=0.819]Test 6: Data size 336: : 50%|█████ | 5/10 [01:13<01:11, 14.31s/it, data_size=336, test_acc=0.692, train_acc=0.819]Test 6: Data size 368: : 50%|█████ | 5/10 [01:13<01:11, 14.31s/it, data_size=336, test_acc=0.692, train_acc=0.819]Test 6: Data size 368: : 50%|█████ | 5/10 [01:27<01:11, 14.31s/it, data_size=368, test_acc=0.749, train_acc=0.859]Test 6: Data size 368: : 60%|██████ | 6/10 [01:27<00:57, 14.29s/it, data_size=368, test_acc=0.749, train_acc=0.859]Test 6: Data size 400: : 60%|██████ | 6/10 [01:27<00:57, 14.29s/it, data_size=368, test_acc=0.749, train_acc=0.859]Test 6: Data size 400: : 60%|██████ | 6/10 [01:47<00:57, 14.29s/it, data_size=400, test_acc=0.765, train_acc=0.822]Test 6: Data size 400: : 70%|███████ | 7/10 [01:47<00:47, 15.92s/it, data_size=400, test_acc=0.765, train_acc=0.822]Test 6: Data size 432: : 70%|███████ | 7/10 [01:47<00:47, 15.92s/it, data_size=400, test_acc=0.765, train_acc=0.822]Test 6: Data size 432: : 70%|███████ | 7/10 [02:06<00:47, 15.92s/it, data_size=432, test_acc=0.834, train_acc=0.874]Test 6: Data size 432: : 80%|████████ | 8/10 [02:06<00:33, 16.89s/it, data_size=432, test_acc=0.834, train_acc=0.874]Test 6: Data size 464: : 80%|████████ | 8/10 [02:06<00:33, 16.89s/it, data_size=432, test_acc=0.834, train_acc=0.874]Test 6: Data size 464: : 80%|████████ | 8/10 [02:25<00:33, 16.89s/it, data_size=464, test_acc=0.89, train_acc=0.908] Test 6: Data size 464: : 90%|█████████ | 9/10 [02:25<00:17, 17.61s/it, data_size=464, test_acc=0.89, train_acc=0.908]Test 6: Data size 496: : 90%|█████████ | 9/10 [02:25<00:17, 17.61s/it, data_size=464, test_acc=0.89, train_acc=0.908]Test 6: Data size 496: : 90%|█████████ | 9/10 [02:44<00:17, 17.61s/it, data_size=496, test_acc=0.899, train_acc=0.921]Test 6: Data size 496: : 100%|██████████| 10/10 [02:44<00:00, 18.18s/it, data_size=496, test_acc=0.899, train_acc=0.921]Test 6: Data size 496: : 100%|██████████| 10/10 [02:44<00:00, 16.48s/it, data_size=496, test_acc=0.899, train_acc=0.921]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:20<?, ?it/s, data_size=208, test_acc=0.5, train_acc=0.494]Test 7: Data size 208: : 10%|█ | 1/10 [00:21<03:09, 21.07s/it, data_size=208, test_acc=0.5, train_acc=0.494]Test 7: Data size 240: : 10%|█ | 1/10 [00:21<03:09, 21.07s/it, data_size=208, test_acc=0.5, train_acc=0.494]Test 7: Data size 240: : 10%|█ | 1/10 [00:30<03:09, 21.07s/it, data_size=240, test_acc=0.582, train_acc=0.663]Test 7: Data size 240: : 20%|██ | 2/10 [00:30<01:52, 14.03s/it, data_size=240, test_acc=0.582, train_acc=0.663]Test 7: Data size 272: : 20%|██ | 2/10 [00:30<01:52, 14.03s/it, data_size=240, test_acc=0.582, train_acc=0.663]Test 7: Data size 272: : 20%|██ | 2/10 [00:43<01:52, 14.03s/it, data_size=272, test_acc=0.683, train_acc=0.767]Test 7: Data size 272: : 30%|███ | 3/10 [00:43<01:37, 13.86s/it, data_size=272, test_acc=0.683, train_acc=0.767]Test 7: Data size 304: : 30%|███ | 3/10 [00:43<01:37, 13.86s/it, data_size=272, test_acc=0.683, train_acc=0.767]Test 7: Data size 304: : 30%|███ | 3/10 [00:57<01:37, 13.86s/it, data_size=304, test_acc=0.742, train_acc=0.827]Test 7: Data size 304: : 40%|████ | 4/10 [00:57<01:23, 13.84s/it, data_size=304, test_acc=0.742, train_acc=0.827]Test 7: Data size 336: : 40%|████ | 4/10 [00:57<01:23, 13.84s/it, data_size=304, test_acc=0.742, train_acc=0.827]Test 7: Data size 336: : 40%|████ | 4/10 [01:11<01:23, 13.84s/it, data_size=336, test_acc=0.813, train_acc=0.816]Test 7: Data size 336: : 50%|█████ | 5/10 [01:11<01:09, 13.98s/it, data_size=336, test_acc=0.813, train_acc=0.816]Test 7: Data size 368: : 50%|█████ | 5/10 [01:11<01:09, 13.98s/it, data_size=336, test_acc=0.813, train_acc=0.816]Test 7: Data size 368: : 50%|█████ | 5/10 [01:25<01:09, 13.98s/it, data_size=368, test_acc=0.892, train_acc=0.857]Test 7: Data size 368: : 60%|██████ | 6/10 [01:25<00:55, 13.95s/it, data_size=368, test_acc=0.892, train_acc=0.857]Test 7: Data size 400: : 60%|██████ | 6/10 [01:25<00:55, 13.95s/it, data_size=368, test_acc=0.892, train_acc=0.857]Test 7: Data size 400: : 60%|██████ | 6/10 [01:44<00:55, 13.95s/it, data_size=400, test_acc=0.888, train_acc=0.902]Test 7: Data size 400: : 70%|███████ | 7/10 [01:44<00:46, 15.44s/it, data_size=400, test_acc=0.888, train_acc=0.902]Test 7: Data size 432: : 70%|███████ | 7/10 [01:44<00:46, 15.44s/it, data_size=400, test_acc=0.888, train_acc=0.902]Test 7: Data size 432: : 70%|███████ | 7/10 [02:02<00:46, 15.44s/it, data_size=432, test_acc=0.904, train_acc=0.885]Test 7: Data size 432: : 80%|████████ | 8/10 [02:02<00:32, 16.46s/it, data_size=432, test_acc=0.904, train_acc=0.885]Test 7: Data size 464: : 80%|████████ | 8/10 [02:02<00:32, 16.46s/it, data_size=432, test_acc=0.904, train_acc=0.885]Test 7: Data size 464: : 80%|████████ | 8/10 [02:21<00:32, 16.46s/it, data_size=464, test_acc=0.877, train_acc=0.828]Test 7: Data size 464: : 90%|█████████ | 9/10 [02:21<00:17, 17.23s/it, data_size=464, test_acc=0.877, train_acc=0.828]Test 7: Data size 496: : 90%|█████████ | 9/10 [02:21<00:17, 17.23s/it, data_size=464, test_acc=0.877, train_acc=0.828]Test 7: Data size 496: : 90%|█████████ | 9/10 [02:41<00:17, 17.23s/it, data_size=496, test_acc=0.897, train_acc=0.885]Test 7: Data size 496: : 100%|██████████| 10/10 [02:41<00:00, 17.92s/it, data_size=496, test_acc=0.897, train_acc=0.885]Test 7: Data size 496: : 100%|██████████| 10/10 [02:41<00:00, 16.13s/it, data_size=496, test_acc=0.897, train_acc=0.885]
working on model Multimodal-late-fusion-model-based-on-AlexNet with BADGE
0%| | 0/10 [00:00<?, ?it/s]Test 0: 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 0: Data size 208: : 0%| | 0/10 [00:17<?, ?it/s, data_size=208, test_acc=0.49, train_acc=0.488]Test 0: Data size 208: : 10%|█ | 1/10 [00:17<02:38, 17.61s/it, data_size=208, test_acc=0.49, train_acc=0.488]Test 0: Data size 239: : 10%|█ | 1/10 [00:17<02:38, 17.61s/it, data_size=208, test_acc=0.49, train_acc=0.488]Test 0: Data size 239: : 10%|█ | 1/10 [00:34<02:38, 17.61s/it, data_size=239, test_acc=0.575, train_acc=0.586]Test 0: Data size 239: : 20%|██ | 2/10 [00:35<02:20, 17.53s/it, data_size=239, test_acc=0.575, train_acc=0.586]Test 0: Data size 270: : 20%|██ | 2/10 [00:35<02:20, 17.53s/it, data_size=239, test_acc=0.575, train_acc=0.586]Test 0: Data size 270: : 20%|██ | 2/10 [00:57<02:20, 17.53s/it, data_size=270, test_acc=0.739, train_acc=0.815]Test 0: Data size 270: : 30%|███ | 3/10 [00:57<02:17, 19.68s/it, data_size=270, test_acc=0.739, train_acc=0.815]Test 0: Data size 301: : 30%|███ | 3/10 [00:57<02:17, 19.68s/it, data_size=270, test_acc=0.739, train_acc=0.815]Test 0: Data size 301: : 30%|███ | 3/10 [01:19<02:17, 19.68s/it, data_size=301, test_acc=0.836, train_acc=0.88] Test 0: Data size 301: : 40%|████ | 4/10 [01:19<02:04, 20.68s/it, data_size=301, test_acc=0.836, train_acc=0.88]Test 0: Data size 332: : 40%|████ | 4/10 [01:19<02:04, 20.68s/it, data_size=301, test_acc=0.836, train_acc=0.88]Test 0: Data size 332: : 40%|████ | 4/10 [01:41<02:04, 20.68s/it, data_size=332, test_acc=0.828, train_acc=0.865]Test 0: Data size 332: : 50%|█████ | 5/10 [01:41<01:46, 21.23s/it, data_size=332, test_acc=0.828, train_acc=0.865]Test 0: Data size 363: : 50%|█████ | 5/10 [01:41<01:46, 21.23s/it, data_size=332, test_acc=0.828, train_acc=0.865]Test 0: Data size 363: : 50%|█████ | 5/10 [02:03<01:46, 21.23s/it, data_size=363, test_acc=0.875, train_acc=0.902]Test 0: Data size 363: : 60%|██████ | 6/10 [02:03<01:26, 21.51s/it, data_size=363, test_acc=0.875, train_acc=0.902]Test 0: Data size 394: : 60%|██████ | 6/10 [02:03<01:26, 21.51s/it, data_size=363, test_acc=0.875, train_acc=0.902]Test 0: Data size 394: : 60%|██████ | 6/10 [02:30<01:26, 21.51s/it, data_size=394, test_acc=0.893, train_acc=0.92] Test 0: Data size 394: : 70%|███████ | 7/10 [02:30<01:09, 23.25s/it, data_size=394, test_acc=0.893, train_acc=0.92]Test 0: Data size 425: : 70%|███████ | 7/10 [02:30<01:09, 23.25s/it, data_size=394, test_acc=0.893, train_acc=0.92]Test 0: Data size 425: : 70%|███████ | 7/10 [02:57<01:09, 23.25s/it, data_size=425, test_acc=0.886, train_acc=0.934]Test 0: Data size 425: : 80%|████████ | 8/10 [02:57<00:48, 24.46s/it, data_size=425, test_acc=0.886, train_acc=0.934]Test 0: Data size 456: : 80%|████████ | 8/10 [02:57<00:48, 24.46s/it, data_size=425, test_acc=0.886, train_acc=0.934]Test 0: Data size 456: : 80%|████████ | 8/10 [03:24<00:48, 24.46s/it, data_size=456, test_acc=0.887, train_acc=0.928]Test 0: Data size 456: : 90%|█████████ | 9/10 [03:24<00:25, 25.12s/it, data_size=456, test_acc=0.887, train_acc=0.928]Test 0: Data size 487: : 90%|█████████ | 9/10 [03:24<00:25, 25.12s/it, data_size=456, test_acc=0.887, train_acc=0.928]Test 0: Data size 487: : 90%|█████████ | 9/10 [03:50<00:25, 25.12s/it, data_size=487, test_acc=0.894, train_acc=0.936]Test 0: Data size 487: : 100%|██████████| 10/10 [03:50<00:00, 25.54s/it, data_size=487, test_acc=0.894, train_acc=0.936]Test 0: Data size 487: : 100%|██████████| 10/10 [03:50<00:00, 23.07s/it, data_size=487, test_acc=0.894, train_acc=0.936]
0%| | 0/10 [00:00<?, ?it/s]Test 1: 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 1: Data size 208: : 0%| | 0/10 [00:17<?, ?it/s, data_size=208, test_acc=0.526, train_acc=0.506]Test 1: Data size 208: : 10%|█ | 1/10 [00:17<02:37, 17.50s/it, data_size=208, test_acc=0.526, train_acc=0.506]Test 1: Data size 239: : 10%|█ | 1/10 [00:17<02:37, 17.50s/it, data_size=208, test_acc=0.526, train_acc=0.506]Test 1: Data size 239: : 10%|█ | 1/10 [00:35<02:37, 17.50s/it, data_size=239, test_acc=0.664, train_acc=0.686]Test 1: Data size 239: : 20%|██ | 2/10 [00:35<02:20, 17.59s/it, data_size=239, test_acc=0.664, train_acc=0.686]Test 1: Data size 270: : 20%|██ | 2/10 [00:35<02:20, 17.59s/it, data_size=239, test_acc=0.664, train_acc=0.686]Test 1: Data size 270: : 20%|██ | 2/10 [00:57<02:20, 17.59s/it, data_size=270, test_acc=0.776, train_acc=0.786]Test 1: Data size 270: : 30%|███ | 3/10 [00:57<02:17, 19.70s/it, data_size=270, test_acc=0.776, train_acc=0.786]Test 1: Data size 301: : 30%|███ | 3/10 [00:57<02:17, 19.70s/it, data_size=270, test_acc=0.776, train_acc=0.786]Test 1: Data size 301: : 30%|███ | 3/10 [01:19<02:17, 19.70s/it, data_size=301, test_acc=0.831, train_acc=0.835]Test 1: Data size 301: : 40%|████ | 4/10 [01:19<02:04, 20.77s/it, data_size=301, test_acc=0.831, train_acc=0.835]Test 1: Data size 332: : 40%|████ | 4/10 [01:19<02:04, 20.77s/it, data_size=301, test_acc=0.831, train_acc=0.835]Test 1: Data size 332: : 40%|████ | 4/10 [01:41<02:04, 20.77s/it, data_size=332, test_acc=0.795, train_acc=0.78] Test 1: Data size 332: : 50%|█████ | 5/10 [01:42<01:46, 21.33s/it, data_size=332, test_acc=0.795, train_acc=0.78]Test 1: Data size 363: : 50%|█████ | 5/10 [01:42<01:46, 21.33s/it, data_size=332, test_acc=0.795, train_acc=0.78]Test 1: Data size 363: : 50%|█████ | 5/10 [02:04<01:46, 21.33s/it, data_size=363, test_acc=0.835, train_acc=0.852]Test 1: Data size 363: : 60%|██████ | 6/10 [02:04<01:26, 21.65s/it, data_size=363, test_acc=0.835, train_acc=0.852]Test 1: Data size 394: : 60%|██████ | 6/10 [02:04<01:26, 21.65s/it, data_size=363, test_acc=0.835, train_acc=0.852]Test 1: Data size 394: : 60%|██████ | 6/10 [02:31<01:26, 21.65s/it, data_size=394, test_acc=0.843, train_acc=0.863]Test 1: Data size 394: : 70%|███████ | 7/10 [02:31<01:10, 23.39s/it, data_size=394, test_acc=0.843, train_acc=0.863]Test 1: Data size 425: : 70%|███████ | 7/10 [02:31<01:10, 23.39s/it, data_size=394, test_acc=0.843, train_acc=0.863]Test 1: Data size 425: : 70%|███████ | 7/10 [02:57<01:10, 23.39s/it, data_size=425, test_acc=0.893, train_acc=0.896]Test 1: Data size 425: : 80%|████████ | 8/10 [02:58<00:48, 24.45s/it, data_size=425, test_acc=0.893, train_acc=0.896]Test 1: Data size 456: : 80%|████████ | 8/10 [02:58<00:48, 24.45s/it, data_size=425, test_acc=0.893, train_acc=0.896]Test 1: Data size 456: : 80%|████████ | 8/10 [03:24<00:48, 24.45s/it, data_size=456, test_acc=0.895, train_acc=0.918]Test 1: Data size 456: : 90%|█████████ | 9/10 [03:25<00:25, 25.26s/it, data_size=456, test_acc=0.895, train_acc=0.918]Test 1: Data size 487: : 90%|█████████ | 9/10 [03:25<00:25, 25.26s/it, data_size=456, test_acc=0.895, train_acc=0.918]Test 1: Data size 487: : 90%|█████████ | 9/10 [03:51<00:25, 25.26s/it, data_size=487, test_acc=0.895, train_acc=0.92] Test 1: Data size 487: : 100%|██████████| 10/10 [03:51<00:00, 25.74s/it, data_size=487, test_acc=0.895, train_acc=0.92]Test 1: Data size 487: : 100%|██████████| 10/10 [03:51<00:00, 23.19s/it, data_size=487, test_acc=0.895, train_acc=0.92]
0%| | 0/10 [00:00<?, ?it/s]Test 2: 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 2: Data size 208: : 0%| | 0/10 [00:16<?, ?it/s, data_size=208, test_acc=0.497, train_acc=0.5]Test 2: Data size 208: : 10%|█ | 1/10 [00:17<02:33, 17.03s/it, data_size=208, test_acc=0.497, train_acc=0.5]Test 2: Data size 239: : 10%|█ | 1/10 [00:17<02:33, 17.03s/it, data_size=208, test_acc=0.497, train_acc=0.5]Test 2: Data size 239: : 10%|█ | 1/10 [00:33<02:33, 17.03s/it, data_size=239, test_acc=0.503, train_acc=0.505]Test 2: Data size 239: : 20%|██ | 2/10 [00:34<02:16, 17.04s/it, data_size=239, test_acc=0.503, train_acc=0.505]Test 2: Data size 270: : 20%|██ | 2/10 [00:34<02:16, 17.04s/it, data_size=239, test_acc=0.503, train_acc=0.505]Test 2: Data size 270: : 20%|██ | 2/10 [00:55<02:16, 17.04s/it, data_size=270, test_acc=0.761, train_acc=0.83] Test 2: Data size 270: : 30%|███ | 3/10 [00:55<02:14, 19.22s/it, data_size=270, test_acc=0.761, train_acc=0.83]Test 2: Data size 301: : 30%|███ | 3/10 [00:55<02:14, 19.22s/it, data_size=270, test_acc=0.761, train_acc=0.83]Test 2: Data size 301: : 30%|███ | 3/10 [01:17<02:14, 19.22s/it, data_size=301, test_acc=0.761, train_acc=0.839]Test 2: Data size 301: : 40%|████ | 4/10 [01:17<02:01, 20.27s/it, data_size=301, test_acc=0.761, train_acc=0.839]Test 2: Data size 332: : 40%|████ | 4/10 [01:17<02:01, 20.27s/it, data_size=301, test_acc=0.761, train_acc=0.839]Test 2: Data size 332: : 40%|████ | 4/10 [01:39<02:01, 20.27s/it, data_size=332, test_acc=0.85, train_acc=0.893] Test 2: Data size 332: : 50%|█████ | 5/10 [01:39<01:44, 20.85s/it, data_size=332, test_acc=0.85, train_acc=0.893]Test 2: Data size 363: : 50%|█████ | 5/10 [01:39<01:44, 20.85s/it, data_size=332, test_acc=0.85, train_acc=0.893]Test 2: Data size 363: : 50%|█████ | 5/10 [02:01<01:44, 20.85s/it, data_size=363, test_acc=0.853, train_acc=0.895]Test 2: Data size 363: : 60%|██████ | 6/10 [02:01<01:24, 21.14s/it, data_size=363, test_acc=0.853, train_acc=0.895]Test 2: Data size 394: : 60%|██████ | 6/10 [02:01<01:24, 21.14s/it, data_size=363, test_acc=0.853, train_acc=0.895]Test 2: Data size 394: : 60%|██████ | 6/10 [02:27<01:24, 21.14s/it, data_size=394, test_acc=0.88, train_acc=0.887] Test 2: Data size 394: : 70%|███████ | 7/10 [02:27<01:08, 22.86s/it, data_size=394, test_acc=0.88, train_acc=0.887]Test 2: Data size 425: : 70%|███████ | 7/10 [02:27<01:08, 22.86s/it, data_size=394, test_acc=0.88, train_acc=0.887]Test 2: Data size 425: : 70%|███████ | 7/10 [02:53<01:08, 22.86s/it, data_size=425, test_acc=0.915, train_acc=0.922]Test 2: Data size 425: : 80%|████████ | 8/10 [02:53<00:47, 23.85s/it, data_size=425, test_acc=0.915, train_acc=0.922]Test 2: Data size 456: : 80%|████████ | 8/10 [02:53<00:47, 23.85s/it, data_size=425, test_acc=0.915, train_acc=0.922]Test 2: Data size 456: : 80%|████████ | 8/10 [03:19<00:47, 23.85s/it, data_size=456, test_acc=0.913, train_acc=0.94] Test 2: Data size 456: : 90%|█████████ | 9/10 [03:19<00:24, 24.59s/it, data_size=456, test_acc=0.913, train_acc=0.94]Test 2: Data size 487: : 90%|█████████ | 9/10 [03:19<00:24, 24.59s/it, data_size=456, test_acc=0.913, train_acc=0.94]Test 2: Data size 487: : 90%|█████████ | 9/10 [03:45<00:24, 24.59s/it, data_size=487, test_acc=0.935, train_acc=0.945]Test 2: Data size 487: : 100%|██████████| 10/10 [03:46<00:00, 25.06s/it, data_size=487, test_acc=0.935, train_acc=0.945]Test 2: Data size 487: : 100%|██████████| 10/10 [03:46<00:00, 22.61s/it, data_size=487, test_acc=0.935, train_acc=0.945]
0%| | 0/10 [00:00<?, ?it/s]Test 3: 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 3: Data size 208: : 0%| | 0/10 [00:17<?, ?it/s, data_size=208, test_acc=0.572, train_acc=0.639]Test 3: Data size 208: : 10%|█ | 1/10 [00:17<02:35, 17.29s/it, data_size=208, test_acc=0.572, train_acc=0.639]Test 3: Data size 239: : 10%|█ | 1/10 [00:17<02:35, 17.29s/it, data_size=208, test_acc=0.572, train_acc=0.639]Test 3: Data size 239: : 10%|█ | 1/10 [00:34<02:35, 17.29s/it, data_size=239, test_acc=0.704, train_acc=0.734]Test 3: Data size 239: : 20%|██ | 2/10 [00:34<02:18, 17.26s/it, data_size=239, test_acc=0.704, train_acc=0.734]Test 3: Data size 270: : 20%|██ | 2/10 [00:34<02:18, 17.26s/it, data_size=239, test_acc=0.704, train_acc=0.734]Test 3: Data size 270: : 20%|██ | 2/10 [00:56<02:18, 17.26s/it, data_size=270, test_acc=0.781, train_acc=0.802]Test 3: Data size 270: : 30%|███ | 3/10 [00:56<02:16, 19.49s/it, data_size=270, test_acc=0.781, train_acc=0.802]Test 3: Data size 301: : 30%|███ | 3/10 [00:56<02:16, 19.49s/it, data_size=270, test_acc=0.781, train_acc=0.802]Test 3: Data size 301: : 30%|███ | 3/10 [01:18<02:16, 19.49s/it, data_size=301, test_acc=0.799, train_acc=0.809]Test 3: Data size 301: : 40%|████ | 4/10 [01:18<02:03, 20.52s/it, data_size=301, test_acc=0.799, train_acc=0.809]Test 3: Data size 332: : 40%|████ | 4/10 [01:18<02:03, 20.52s/it, data_size=301, test_acc=0.799, train_acc=0.809]Test 3: Data size 332: : 40%|████ | 4/10 [01:40<02:03, 20.52s/it, data_size=332, test_acc=0.854, train_acc=0.866]Test 3: Data size 332: : 50%|█████ | 5/10 [01:40<01:45, 21.12s/it, data_size=332, test_acc=0.854, train_acc=0.866]Test 3: Data size 363: : 50%|█████ | 5/10 [01:40<01:45, 21.12s/it, data_size=332, test_acc=0.854, train_acc=0.866]Test 3: Data size 363: : 50%|█████ | 5/10 [02:02<01:45, 21.12s/it, data_size=363, test_acc=0.834, train_acc=0.856]Test 3: Data size 363: : 60%|██████ | 6/10 [02:02<01:25, 21.43s/it, data_size=363, test_acc=0.834, train_acc=0.856]Test 3: Data size 394: : 60%|██████ | 6/10 [02:02<01:25, 21.43s/it, data_size=363, test_acc=0.834, train_acc=0.856]Test 3: Data size 394: : 60%|██████ | 6/10 [02:29<01:25, 21.43s/it, data_size=394, test_acc=0.873, train_acc=0.906]Test 3: Data size 394: : 70%|███████ | 7/10 [02:29<01:09, 23.19s/it, data_size=394, test_acc=0.873, train_acc=0.906]Test 3: Data size 425: : 70%|███████ | 7/10 [02:29<01:09, 23.19s/it, data_size=394, test_acc=0.873, train_acc=0.906]Test 3: Data size 425: : 70%|███████ | 7/10 [02:56<01:09, 23.19s/it, data_size=425, test_acc=0.884, train_acc=0.905]Test 3: Data size 425: : 80%|████████ | 8/10 [02:56<00:48, 24.24s/it, data_size=425, test_acc=0.884, train_acc=0.905]Test 3: Data size 456: : 80%|████████ | 8/10 [02:56<00:48, 24.24s/it, data_size=425, test_acc=0.884, train_acc=0.905]Test 3: Data size 456: : 80%|████████ | 8/10 [03:22<00:48, 24.24s/it, data_size=456, test_acc=0.89, train_acc=0.883] Test 3: Data size 456: : 90%|█████████ | 9/10 [03:22<00:25, 25.01s/it, data_size=456, test_acc=0.89, train_acc=0.883]Test 3: Data size 487: : 90%|█████████ | 9/10 [03:22<00:25, 25.01s/it, data_size=456, test_acc=0.89, train_acc=0.883]Test 3: Data size 487: : 90%|█████████ | 9/10 [03:49<00:25, 25.01s/it, data_size=487, test_acc=0.915, train_acc=0.91]Test 3: Data size 487: : 100%|██████████| 10/10 [03:49<00:00, 25.47s/it, data_size=487, test_acc=0.915, train_acc=0.91]Test 3: Data size 487: : 100%|██████████| 10/10 [03:49<00:00, 22.95s/it, data_size=487, test_acc=0.915, train_acc=0.91]
0%| | 0/10 [00:00<?, ?it/s]Test 4: 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 4: Data size 208: : 0%| | 0/10 [00:17<?, ?it/s, data_size=208, test_acc=0.492, train_acc=0.498]Test 4: Data size 208: : 10%|█ | 1/10 [00:17<02:35, 17.32s/it, data_size=208, test_acc=0.492, train_acc=0.498]Test 4: Data size 239: : 10%|█ | 1/10 [00:17<02:35, 17.32s/it, data_size=208, test_acc=0.492, train_acc=0.498]Test 4: Data size 239: : 10%|█ | 1/10 [00:34<02:35, 17.32s/it, data_size=239, test_acc=0.641, train_acc=0.679]Test 4: Data size 239: : 20%|██ | 2/10 [00:34<02:17, 17.25s/it, data_size=239, test_acc=0.641, train_acc=0.679]Test 4: Data size 270: : 20%|██ | 2/10 [00:34<02:17, 17.25s/it, data_size=239, test_acc=0.641, train_acc=0.679]Test 4: Data size 270: : 20%|██ | 2/10 [00:56<02:17, 17.25s/it, data_size=270, test_acc=0.746, train_acc=0.792]Test 4: Data size 270: : 30%|███ | 3/10 [00:56<02:15, 19.40s/it, data_size=270, test_acc=0.746, train_acc=0.792]Test 4: Data size 301: : 30%|███ | 3/10 [00:56<02:15, 19.40s/it, data_size=270, test_acc=0.746, train_acc=0.792]Test 4: Data size 301: : 30%|███ | 3/10 [01:18<02:15, 19.40s/it, data_size=301, test_acc=0.848, train_acc=0.901]Test 4: Data size 301: : 40%|████ | 4/10 [01:18<02:02, 20.43s/it, data_size=301, test_acc=0.848, train_acc=0.901]Test 4: Data size 332: : 40%|████ | 4/10 [01:18<02:02, 20.43s/it, data_size=301, test_acc=0.848, train_acc=0.901]Test 4: Data size 332: : 40%|████ | 4/10 [01:39<02:02, 20.43s/it, data_size=332, test_acc=0.864, train_acc=0.911]Test 4: Data size 332: : 50%|█████ | 5/10 [01:39<01:43, 20.75s/it, data_size=332, test_acc=0.864, train_acc=0.911]Test 4: Data size 363: : 50%|█████ | 5/10 [01:39<01:43, 20.75s/it, data_size=332, test_acc=0.864, train_acc=0.911]Test 4: Data size 363: : 50%|█████ | 5/10 [02:01<01:43, 20.75s/it, data_size=363, test_acc=0.866, train_acc=0.896]Test 4: Data size 363: : 60%|██████ | 6/10 [02:01<01:23, 20.96s/it, data_size=363, test_acc=0.866, train_acc=0.896]Test 4: Data size 394: : 60%|██████ | 6/10 [02:01<01:23, 20.96s/it, data_size=363, test_acc=0.866, train_acc=0.896]Test 4: Data size 394: : 60%|██████ | 6/10 [02:26<01:23, 20.96s/it, data_size=394, test_acc=0.834, train_acc=0.899]Test 4: Data size 394: : 70%|███████ | 7/10 [02:26<01:07, 22.50s/it, data_size=394, test_acc=0.834, train_acc=0.899]Test 4: Data size 425: : 70%|███████ | 7/10 [02:26<01:07, 22.50s/it, data_size=394, test_acc=0.834, train_acc=0.899]Test 4: Data size 425: : 70%|███████ | 7/10 [02:52<01:07, 22.50s/it, data_size=425, test_acc=0.875, train_acc=0.934]Test 4: Data size 425: : 80%|████████ | 8/10 [02:53<00:47, 23.67s/it, data_size=425, test_acc=0.875, train_acc=0.934]Test 4: Data size 456: : 80%|████████ | 8/10 [02:53<00:47, 23.67s/it, data_size=425, test_acc=0.875, train_acc=0.934]Test 4: Data size 456: : 80%|████████ | 8/10 [03:19<00:47, 23.67s/it, data_size=456, test_acc=0.878, train_acc=0.92] Test 4: Data size 456: : 90%|█████████ | 9/10 [03:19<00:24, 24.46s/it, data_size=456, test_acc=0.878, train_acc=0.92]Test 4: Data size 487: : 90%|█████████ | 9/10 [03:19<00:24, 24.46s/it, data_size=456, test_acc=0.878, train_acc=0.92]Test 4: Data size 487: : 90%|█████████ | 9/10 [03:45<00:24, 24.46s/it, data_size=487, test_acc=0.881, train_acc=0.897]Test 4: Data size 487: : 100%|██████████| 10/10 [03:45<00:00, 25.07s/it, data_size=487, test_acc=0.881, train_acc=0.897]Test 4: Data size 487: : 100%|██████████| 10/10 [03:45<00:00, 22.57s/it, data_size=487, test_acc=0.881, train_acc=0.897]
0%| | 0/10 [00:00<?, ?it/s]Test 5: 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 5: Data size 208: : 0%| | 0/10 [00:17<?, ?it/s, data_size=208, test_acc=0.495, train_acc=0.5]Test 5: Data size 208: : 10%|█ | 1/10 [00:17<02:36, 17.36s/it, data_size=208, test_acc=0.495, train_acc=0.5]Test 5: Data size 239: : 10%|█ | 1/10 [00:17<02:36, 17.36s/it, data_size=208, test_acc=0.495, train_acc=0.5]Test 5: Data size 239: : 10%|█ | 1/10 [00:34<02:36, 17.36s/it, data_size=239, test_acc=0.635, train_acc=0.669]Test 5: Data size 239: : 20%|██ | 2/10 [00:34<02:18, 17.36s/it, data_size=239, test_acc=0.635, train_acc=0.669]Test 5: Data size 270: : 20%|██ | 2/10 [00:34<02:18, 17.36s/it, data_size=239, test_acc=0.635, train_acc=0.669]Test 5: Data size 270: : 20%|██ | 2/10 [00:56<02:18, 17.36s/it, data_size=270, test_acc=0.771, train_acc=0.855]Test 5: Data size 270: : 30%|███ | 3/10 [00:56<02:17, 19.60s/it, data_size=270, test_acc=0.771, train_acc=0.855]Test 5: Data size 301: : 30%|███ | 3/10 [00:56<02:17, 19.60s/it, data_size=270, test_acc=0.771, train_acc=0.855]Test 5: Data size 301: : 30%|███ | 3/10 [01:19<02:17, 19.60s/it, data_size=301, test_acc=0.778, train_acc=0.88] Test 5: Data size 301: : 40%|████ | 4/10 [01:19<02:03, 20.61s/it, data_size=301, test_acc=0.778, train_acc=0.88]Test 5: Data size 332: : 40%|████ | 4/10 [01:19<02:03, 20.61s/it, data_size=301, test_acc=0.778, train_acc=0.88]Test 5: Data size 332: : 40%|████ | 4/10 [01:41<02:03, 20.61s/it, data_size=332, test_acc=0.773, train_acc=0.861]Test 5: Data size 332: : 50%|█████ | 5/10 [01:41<01:45, 21.12s/it, data_size=332, test_acc=0.773, train_acc=0.861]Test 5: Data size 363: : 50%|█████ | 5/10 [01:41<01:45, 21.12s/it, data_size=332, test_acc=0.773, train_acc=0.861]Test 5: Data size 363: : 50%|█████ | 5/10 [02:03<01:45, 21.12s/it, data_size=363, test_acc=0.884, train_acc=0.922]Test 5: Data size 363: : 60%|██████ | 6/10 [02:03<01:25, 21.42s/it, data_size=363, test_acc=0.884, train_acc=0.922]Test 5: Data size 394: : 60%|██████ | 6/10 [02:03<01:25, 21.42s/it, data_size=363, test_acc=0.884, train_acc=0.922]Test 5: Data size 394: : 60%|██████ | 6/10 [02:29<01:25, 21.42s/it, data_size=394, test_acc=0.874, train_acc=0.891]Test 5: Data size 394: : 70%|███████ | 7/10 [02:29<01:09, 23.17s/it, data_size=394, test_acc=0.874, train_acc=0.891]Test 5: Data size 425: : 70%|███████ | 7/10 [02:29<01:09, 23.17s/it, data_size=394, test_acc=0.874, train_acc=0.891]Test 5: Data size 425: : 70%|███████ | 7/10 [02:56<01:09, 23.17s/it, data_size=425, test_acc=0.873, train_acc=0.924]Test 5: Data size 425: : 80%|████████ | 8/10 [02:56<00:48, 24.18s/it, data_size=425, test_acc=0.873, train_acc=0.924]Test 5: Data size 456: : 80%|████████ | 8/10 [02:56<00:48, 24.18s/it, data_size=425, test_acc=0.873, train_acc=0.924]Test 5: Data size 456: : 80%|████████ | 8/10 [03:23<00:48, 24.18s/it, data_size=456, test_acc=0.878, train_acc=0.899]Test 5: Data size 456: : 90%|█████████ | 9/10 [03:23<00:25, 25.07s/it, data_size=456, test_acc=0.878, train_acc=0.899]Test 5: Data size 487: : 90%|█████████ | 9/10 [03:23<00:25, 25.07s/it, data_size=456, test_acc=0.878, train_acc=0.899]Test 5: Data size 487: : 90%|█████████ | 9/10 [03:49<00:25, 25.07s/it, data_size=487, test_acc=0.886, train_acc=0.915]Test 5: Data size 487: : 100%|██████████| 10/10 [03:49<00:00, 25.37s/it, data_size=487, test_acc=0.886, train_acc=0.915]Test 5: Data size 487: : 100%|██████████| 10/10 [03:49<00:00, 22.94s/it, data_size=487, test_acc=0.886, train_acc=0.915]
0%| | 0/10 [00:00<?, ?it/s]Test 6: 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 6: Data size 208: : 0%| | 0/10 [00:17<?, ?it/s, data_size=208, test_acc=0.497, train_acc=0.497]Test 6: Data size 208: : 10%|█ | 1/10 [00:17<02:35, 17.25s/it, data_size=208, test_acc=0.497, train_acc=0.497]Test 6: Data size 239: : 10%|█ | 1/10 [00:17<02:35, 17.25s/it, data_size=208, test_acc=0.497, train_acc=0.497]Test 6: Data size 239: : 10%|█ | 1/10 [00:34<02:35, 17.25s/it, data_size=239, test_acc=0.664, train_acc=0.756]Test 6: Data size 239: : 20%|██ | 2/10 [00:34<02:17, 17.16s/it, data_size=239, test_acc=0.664, train_acc=0.756]Test 6: Data size 270: : 20%|██ | 2/10 [00:34<02:17, 17.16s/it, data_size=239, test_acc=0.664, train_acc=0.756]Test 6: Data size 270: : 20%|██ | 2/10 [00:56<02:17, 17.16s/it, data_size=270, test_acc=0.746, train_acc=0.782]Test 6: Data size 270: : 30%|███ | 3/10 [00:56<02:15, 19.32s/it, data_size=270, test_acc=0.746, train_acc=0.782]Test 6: Data size 301: : 30%|███ | 3/10 [00:56<02:15, 19.32s/it, data_size=270, test_acc=0.746, train_acc=0.782]Test 6: Data size 301: : 30%|███ | 3/10 [01:17<02:15, 19.32s/it, data_size=301, test_acc=0.846, train_acc=0.828]Test 6: Data size 301: : 40%|████ | 4/10 [01:17<02:01, 20.28s/it, data_size=301, test_acc=0.846, train_acc=0.828]Test 6: Data size 332: : 40%|████ | 4/10 [01:17<02:01, 20.28s/it, data_size=301, test_acc=0.846, train_acc=0.828]Test 6: Data size 332: : 40%|████ | 4/10 [01:39<02:01, 20.28s/it, data_size=332, test_acc=0.873, train_acc=0.861]Test 6: Data size 332: : 50%|█████ | 5/10 [01:39<01:44, 20.83s/it, data_size=332, test_acc=0.873, train_acc=0.861]Test 6: Data size 363: : 50%|█████ | 5/10 [01:39<01:44, 20.83s/it, data_size=332, test_acc=0.873, train_acc=0.861]Test 6: Data size 363: : 50%|█████ | 5/10 [02:01<01:44, 20.83s/it, data_size=363, test_acc=0.894, train_acc=0.859]Test 6: Data size 363: : 60%|██████ | 6/10 [02:01<01:24, 21.15s/it, data_size=363, test_acc=0.894, train_acc=0.859]Test 6: Data size 394: : 60%|██████ | 6/10 [02:01<01:24, 21.15s/it, data_size=363, test_acc=0.894, train_acc=0.859]Test 6: Data size 394: : 60%|██████ | 6/10 [02:27<01:24, 21.15s/it, data_size=394, test_acc=0.881, train_acc=0.894]Test 6: Data size 394: : 70%|███████ | 7/10 [02:27<01:08, 22.78s/it, data_size=394, test_acc=0.881, train_acc=0.894]Test 6: Data size 425: : 70%|███████ | 7/10 [02:27<01:08, 22.78s/it, data_size=394, test_acc=0.881, train_acc=0.894]Test 6: Data size 425: : 70%|███████ | 7/10 [02:53<01:08, 22.78s/it, data_size=425, test_acc=0.907, train_acc=0.888]Test 6: Data size 425: : 80%|████████ | 8/10 [02:54<00:47, 23.93s/it, data_size=425, test_acc=0.907, train_acc=0.888]Test 6: Data size 456: : 80%|████████ | 8/10 [02:54<00:47, 23.93s/it, data_size=425, test_acc=0.907, train_acc=0.888]Test 6: Data size 456: : 80%|████████ | 8/10 [03:20<00:47, 23.93s/it, data_size=456, test_acc=0.893, train_acc=0.905]Test 6: Data size 456: : 90%|█████████ | 9/10 [03:20<00:24, 24.64s/it, data_size=456, test_acc=0.893, train_acc=0.905]Test 6: Data size 487: : 90%|█████████ | 9/10 [03:20<00:24, 24.64s/it, data_size=456, test_acc=0.893, train_acc=0.905]Test 6: Data size 487: : 90%|█████████ | 9/10 [03:46<00:24, 24.64s/it, data_size=487, test_acc=0.902, train_acc=0.928]Test 6: Data size 487: : 100%|██████████| 10/10 [03:46<00:00, 25.18s/it, data_size=487, test_acc=0.902, train_acc=0.928]Test 6: Data size 487: : 100%|██████████| 10/10 [03:46<00:00, 22.67s/it, data_size=487, test_acc=0.902, train_acc=0.928]
0%| | 0/10 [00:00<?, ?it/s]Test 7: 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:00<?, ?it/s]Test 7: Data size 208: : 0%| | 0/10 [00:17<?, ?it/s, data_size=208, test_acc=0.5, train_acc=0.5]Test 7: Data size 208: : 10%|█ | 1/10 [00:17<02:35, 17.32s/it, data_size=208, test_acc=0.5, train_acc=0.5]Test 7: Data size 239: : 10%|█ | 1/10 [00:17<02:35, 17.32s/it, data_size=208, test_acc=0.5, train_acc=0.5]Test 7: Data size 239: : 10%|█ | 1/10 [00:34<02:35, 17.32s/it, data_size=239, test_acc=0.599, train_acc=0.642]Test 7: Data size 239: : 20%|██ | 2/10 [00:34<02:18, 17.33s/it, data_size=239, test_acc=0.599, train_acc=0.642]Test 7: Data size 270: : 20%|██ | 2/10 [00:34<02:18, 17.33s/it, data_size=239, test_acc=0.599, train_acc=0.642]Test 7: Data size 270: : 20%|██ | 2/10 [00:56<02:18, 17.33s/it, data_size=270, test_acc=0.744, train_acc=0.833]Test 7: Data size 270: : 30%|███ | 3/10 [00:56<02:17, 19.58s/it, data_size=270, test_acc=0.744, train_acc=0.833]Test 7: Data size 301: : 30%|███ | 3/10 [00:56<02:17, 19.58s/it, data_size=270, test_acc=0.744, train_acc=0.833]Test 7: Data size 301: : 30%|███ | 3/10 [01:19<02:17, 19.58s/it, data_size=301, test_acc=0.75, train_acc=0.851] Test 7: Data size 301: : 40%|████ | 4/10 [01:19<02:03, 20.66s/it, data_size=301, test_acc=0.75, train_acc=0.851]Test 7: Data size 332: : 40%|████ | 4/10 [01:19<02:03, 20.66s/it, data_size=301, test_acc=0.75, train_acc=0.851]Test 7: Data size 332: : 40%|████ | 4/10 [01:41<02:03, 20.66s/it, data_size=332, test_acc=0.895, train_acc=0.899]Test 7: Data size 332: : 50%|█████ | 5/10 [01:41<01:46, 21.21s/it, data_size=332, test_acc=0.895, train_acc=0.899]Test 7: Data size 363: : 50%|█████ | 5/10 [01:41<01:46, 21.21s/it, data_size=332, test_acc=0.895, train_acc=0.899]Test 7: Data size 363: : 50%|█████ | 5/10 [02:03<01:46, 21.21s/it, data_size=363, test_acc=0.915, train_acc=0.904]Test 7: Data size 363: : 60%|██████ | 6/10 [02:03<01:25, 21.50s/it, data_size=363, test_acc=0.915, train_acc=0.904]Test 7: Data size 394: : 60%|██████ | 6/10 [02:03<01:25, 21.50s/it, data_size=363, test_acc=0.915, train_acc=0.904]Test 7: Data size 394: : 60%|██████ | 6/10 [02:30<01:25, 21.50s/it, data_size=394, test_acc=0.906, train_acc=0.88] Test 7: Data size 394: : 70%|███████ | 7/10 [02:30<01:09, 23.27s/it, data_size=394, test_acc=0.906, train_acc=0.88]Test 7: Data size 425: : 70%|███████ | 7/10 [02:30<01:09, 23.27s/it, data_size=394, test_acc=0.906, train_acc=0.88]Test 7: Data size 425: : 70%|███████ | 7/10 [02:56<01:09, 23.27s/it, data_size=425, test_acc=0.915, train_acc=0.918]Test 7: Data size 425: : 80%|████████ | 8/10 [02:56<00:48, 24.32s/it, data_size=425, test_acc=0.915, train_acc=0.918]Test 7: Data size 456: : 80%|████████ | 8/10 [02:56<00:48, 24.32s/it, data_size=425, test_acc=0.915, train_acc=0.918]Test 7: Data size 456: : 80%|████████ | 8/10 [03:23<00:48, 24.32s/it, data_size=456, test_acc=0.911, train_acc=0.906]Test 7: Data size 456: : 90%|█████████ | 9/10 [03:23<00:25, 25.10s/it, data_size=456, test_acc=0.911, train_acc=0.906]Test 7: Data size 487: : 90%|█████████ | 9/10 [03:23<00:25, 25.10s/it, data_size=456, test_acc=0.911, train_acc=0.906]Test 7: Data size 487: : 90%|█████████ | 9/10 [03:50<00:25, 25.10s/it, data_size=487, test_acc=0.93, train_acc=0.882] Test 7: Data size 487: : 100%|██████████| 10/10 [03:50<00:00, 25.62s/it, data_size=487, test_acc=0.93, train_acc=0.882]Test 7: Data size 487: : 100%|██████████| 10/10 [03:50<00:00, 23.06s/it, data_size=487, test_acc=0.93, train_acc=0.882]
Traceback (most recent call last):
File "main.py", line 122, in <module>
cluster_margin_cluster_methods_experiments()
File "main.py", line 95, in cluster_margin_cluster_methods_experiments
experiment_configs=BASELINE_CONFIGS
TypeError: __init__() got an unexpected keyword argument 'options'