finetuned-distilbert-news-article-catgorization
This model is a fine-tuned version of distilbert-base-uncased on the news_article_categorization dataset. It achieves the following results on the evaluation set:
- Loss: 0.1548
- F1_score(weighted): 0.96
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
The model was trained on some subset of the news_article_categorization dataset and it was validated on the remaining subset of the data
Training procedure
More information needed
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-5
- train_batch_size: 3
- eval_batch_size: 3
- seed: 17
- optimizer: AdamW(lr=1e-5 and epsilon=1e-08)
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0
- num_epochs: 2
Training results
| Training Loss | Epoch | Validation Loss | f1 score |
|---|---|---|---|
| 0.6359 | 1.0 | 0.1739 | 0.9619 |
| 0.1548 | 2.0 | 0.1898 | 0.9648 |
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