roberta-base-biomedical-clinical-es-ner

This model is a fine-tuned version of BSC-LT/roberta-base-biomedical-clinical-es on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3813
• Precision: 0.8687
• Recall: 0.8919
• F1: 0.8801
• Accuracy: 0.9374

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	280	0.3201	0.7961	0.8385	0.8167	0.9130
0.5051	2.0	560	0.2833	0.8245	0.8770	0.8500	0.9282
0.5051	3.0	840	0.2717	0.8459	0.8622	0.8540	0.9262
0.1434	4.0	1120	0.2782	0.8477	0.8904	0.8685	0.9324
0.1434	5.0	1400	0.3119	0.8525	0.8993	0.8753	0.9355
0.0804	6.0	1680	0.3146	0.8639	0.8933	0.8784	0.9366
0.0804	7.0	1960	0.3211	0.8637	0.8919	0.8776	0.9346
0.0475	8.0	2240	0.3523	0.8707	0.8978	0.8840	0.9372
0.0347	9.0	2520	0.3651	0.8434	0.8859	0.8642	0.9335
0.0347	10.0	2800	0.3663	0.8706	0.8874	0.8789	0.9360
0.0241	11.0	3080	0.3756	0.8680	0.8963	0.8819	0.9372
0.0241	12.0	3360	0.3692	0.86	0.8919	0.8756	0.9369
0.0201	13.0	3640	0.3782	0.8631	0.8874	0.8751	0.9360
0.0201	14.0	3920	0.3820	0.8698	0.8904	0.8799	0.9374
0.0172	15.0	4200	0.3813	0.8687	0.8919	0.8801	0.9374

Framework versions

• Transformers 4.41.1
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1