Model Card for Model ID
This model is a fine-tuned version of
distilbert-base-uncased for multi-class news article classification. It was trained to classify Sri Lankan English news excerpts from the Daily Mirror Online into one of five predefined categories.
Model Details
Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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Uses
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How to Get Started with the Model
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Training Details
Training Data
Training Procedure
Preprocessing [optional]
Before fine-tuning, the following text preprocessing steps were applied:
- Lowercase conversion
- URL removal
- Email removal
- Punctuation removal (ASCII + Unicode smart quotes)
- Stopword removal (NLTK English stopwords)
- Numbers and special character removal
- Frequent word removal (top 10)
- Rare word removal (bottom 100)
- Tokenization
- Lemmatization (WordNet, POS-aware)
Training Hyperparameters
The following hyperparameters were used during training:
- train_batch_size: 4
- eval_batch_size: 4
- Evaluation strategy: Every 100 steps
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Evaluation
Testing Data, Factors & Metrics
Testing Data
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Results
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Summary
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Environmental Impact
Carbon emissions can be estimated using the
Machine Learning Impact calculator presented in
Lacoste et al. (2019).
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