bert-biobert2

This model is a fine-tuned version of bert-base-uncased on the biobert_json dataset. It achieves the following results on the evaluation set:

• Loss: 0.1128
• Precision: 0.9261
• Recall: 0.9658
• F1: 0.9455
• Accuracy: 0.9716

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.4693	1.0	612	0.1290	0.9206	0.9524	0.9362	0.9675
0.1562	2.0	1224	0.1128	0.9261	0.9658	0.9455	0.9716

Framework versions

• Transformers 4.46.2
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3