In2Lab_WFU_DETECH_ate_span_biobert_v1

This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.1 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1151
• Precision: 0.7944
• Recall: 0.8041
• F1: 0.7992

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: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 7
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1
No log	1.0	61	0.1674	0.7136	0.6143	0.6602
No log	2.0	122	0.1358	0.7411	0.7674	0.7540
No log	3.0	183	0.1245	0.7599	0.8028	0.7808
No log	4.0	244	0.1162	0.7852	0.7927	0.7889
No log	5.0	305	0.1140	0.7996	0.7976	0.7986
No log	6.0	366	0.1133	0.7943	0.8002	0.7972
No log	7.0	427	0.1151	0.7944	0.8041	0.7992

Framework versions

• Transformers 4.57.6
• Pytorch 2.9.0+cu126
• Datasets 4.0.0
• Tokenizers 0.22.2