prueba4

This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es-pharmaconer on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.2044
• Precision: 0.7288
• Recall: 0.6853
• F1: 0.7064
• Accuracy: 0.9752

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: 2.75e-05
• train_batch_size: 16
• 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	57	0.2361	0.6504	0.6892	0.6692	0.9694
No log	2.0	114	0.2441	0.6190	0.6733	0.6450	0.9671
No log	3.0	171	0.2064	0.6013	0.7211	0.6558	0.9699
No log	4.0	228	0.2241	0.7004	0.6335	0.6653	0.9720
No log	5.0	285	0.1992	0.6578	0.6892	0.6732	0.9727
No log	6.0	342	0.2149	0.6073	0.7331	0.6643	0.9694
No log	7.0	399	0.2099	0.7466	0.6574	0.6992	0.9755
No log	8.0	456	0.2039	0.7293	0.6653	0.6958	0.9747
0.0017	9.0	513	0.2185	0.7342	0.6494	0.6892	0.9742
0.0017	10.0	570	0.2074	0.688	0.6853	0.6866	0.9732
0.0017	11.0	627	0.2010	0.7073	0.6932	0.7002	0.9745
0.0017	12.0	684	0.2030	0.7126	0.7012	0.7068	0.9749
0.0017	13.0	741	0.2045	0.7173	0.6773	0.6967	0.9745
0.0017	14.0	798	0.2040	0.7185	0.6813	0.6994	0.9747
0.0017	15.0	855	0.2044	0.7288	0.6853	0.7064	0.9752

Framework versions

• Transformers 4.27.3
• Pytorch 1.13.1+cu116
• Datasets 2.10.1
• Tokenizers 0.13.2