devicebert-base-cased-v1.0

This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.2 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: nan
• Precision: 0.6816
• Recall: 0.6691
• F1: 0.6753
• Accuracy: 0.8547

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: 1e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	101	nan	0.5981	0.5740	0.5858	0.8131
No log	2.0	202	nan	0.6673	0.6197	0.6427	0.8424
No log	3.0	303	nan	0.6926	0.6673	0.6797	0.8498
No log	4.0	404	nan	0.686	0.6271	0.6552	0.8473
0.3891	5.0	505	nan	0.6853	0.6490	0.6667	0.8539
0.3891	6.0	606	nan	0.6857	0.7020	0.6938	0.8563
0.3891	7.0	707	nan	0.6900	0.6673	0.6784	0.8580
0.3891	8.0	808	nan	0.6795	0.6782	0.6789	0.8514
0.3891	9.0	909	nan	0.6906	0.6691	0.6797	0.8571
0.1315	10.0	1010	nan	0.6816	0.6691	0.6753	0.8547

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1