This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es on the Rodrigo1771/symptemist-8-ner dataset. It achieves the following results on the evaluation set:

Loss: 0.3003
Precision: 0.6832
Recall: 0.7083
F1: 0.6955
Accuracy: 0.9498

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: 5e-05
train_batch_size: 32
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.9976	209	0.1511	0.5818	0.6694	0.6226	0.9457
No log	2.0	419	0.1794	0.6113	0.7017	0.6534	0.9465
0.1282	2.9976	628	0.2102	0.6572	0.6979	0.6769	0.9470
0.1282	4.0	838	0.2329	0.6605	0.6984	0.6789	0.9489
0.0255	4.9976	1047	0.2591	0.6646	0.6973	0.6806	0.9491
0.0255	6.0	1257	0.2737	0.6599	0.6968	0.6778	0.9491
0.0255	6.9976	1466	0.2876	0.6687	0.7094	0.6884	0.9492
0.0085	8.0	1676	0.3003	0.6832	0.7083	0.6955	0.9498
0.0085	8.9976	1885	0.3072	0.6697	0.7170	0.6926	0.9492
0.004	9.9761	2090	0.3125	0.6711	0.7137	0.6918	0.9492

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1

Rodrigo1771/bsc-bio-ehr-es-symptemist-word2vec-8-ner

output

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Rodrigo1771/
bsc-bio-ehr-es-symptemist-word2vec-8-ner