finetuned-distilbert-news-article-categorization

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