add the classification process for EN WIKI #96
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Thanks! I'll look at it after we close the other open PRs, possibly next week. |
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| # -*- coding: utf-8 -*- | |||
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It's good to think about why you want this directory to be in the root folder. Is it related to the Database? Maybe that would be a more appropriate location.
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| *** This is the classification process for English Wikipedia articles related to climate disasters.*** | |||
| #Files description | |||
| [] Classfication_wikipedia.py is a script used for training the BERT model, and the training data is shuffled_training_dataset.csv | |||
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Use - instead of [] for markdown to how bullets
| ```shell | ||
| poetry run python3 BERT_Classification_EN_Wikipedia/Classifier_implement.py --filename wikipedia_dataset_preforclassify_20240229.csv --file_dir BERT_Classification_EN_Wikipedia | ||
| ``` | ||
| It takes long time to run for the all articles we collected, and we recommand to run it for new articles in Wikipedia after day 20240229. |
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Use properly written dates rather than timestamps (which are harder to read)
| [] wikipedia_dataset_preforclassify_20240229.csv contains all articles we collected using the keywords searching | ||
| [] Classifier_implement.py is a script to implement the classification model, the command you can refer to use this model is: | ||
| ```shell | ||
| poetry run python3 BERT_Classification_EN_Wikipedia/Classifier_implement.py --filename wikipedia_dataset_preforclassify_20240229.csv --file_dir BERT_Classification_EN_Wikipedia |
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Correct the directory name:
| poetry run python3 BERT_Classification_EN_Wikipedia/Classifier_implement.py --filename wikipedia_dataset_preforclassify_20240229.csv --file_dir BERT_Classification_EN_Wikipedia | |
| poetry run python3 BERT_Classification_EN_WIKI/Classifier_implement.py --filename wikipedia_dataset_preforclassify_20240229.csv --file_dir BERT_Classification_EN_WIKI |
| model = AutoModelForSequenceClassification.from_pretrained( | ||
| "liniiiiii/DistilBertForSequenceClassification_WIKI_Natural_disaster" | ||
| ) | ||
| tokenizer = AutoTokenizer.from_pretrained("liniiiiii/DistilBertForSequenceClassification_WIKI_Natural_disaster") |
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Great job pushing the model to HF :)
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| # -*- coding: utf-8 -*- | |||
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The script names Classifier_implement.py and Classification_wikipedia.py could have more descriptive names, such as classifier.py or trainer.py.
| text = str(text) # Convert to string if not already | ||
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| # Split the text into segments of 512 tokens | ||
| tokenized_text = tokenizer.encode_plus(text, add_special_tokens=True, truncation=True, max_length=512) |
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This variable is never used anywhere. Maybe check why?
| from Database.scr.normalize_utils import Logging | ||
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| if __name__ == "__main__": | ||
| logger = Logging.get_logger("classification training") |
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It could help to add more useful logs to both .py files
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Why is the name of this file BERT_Classification_EN_WIKI/wikipedia_dataset_preforclassify_20240229.csv? What does prefor mean?
| tokenizer = AutoTokenizer.from_pretrained("liniiiiii/DistilBertForSequenceClassification_WIKI_Natural_disaster") | ||
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| from Database.scr.normalize_utils import Logging |
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It's much better to keep all imports at the top to make the code easy to read
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| # Classify each text in the dataset | ||
| results = [] | ||
| for _, row in df.iterrows(): |
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To show the progress to users:
| for _, row in df.iterrows(): | |
| for _, row in tqdm(df.iterrows(), total=df.shape[0]): |
from tqdm import tqdmThat way you get a visual progress bar:
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Did you also mean to push wikipedia_dataset_preforclassify_20240229_classified.csv? I have it since I ran the script to test it, so let me know and I can push it to the branch.
@i-be-snek , this is in low priority, if you have time, just have a look of the code, and I want to add it in the main branch because we have it described in the paper, thanks!