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bastianchinchon/
nominal-groups-recognition-beto-clinical-wl-es

Name: nominal-groups-recognition-beto-clinical-wl-es
Availability: InStock

generated_from_trainer

bastianchinchon/spanish_nominal_groups_conll2003

autotrain_compatible

endpoints_compatible

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nominal-groups-recognition-beto-clinical-wl-es

This model is a fine-tuned version of plncmm/beto-clinical-wl-es on the bastianchinchon/spanish_nominal_groups_conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.2338
Body Part Precision: 0.7894
Body Part Recall: 0.8257
Body Part F1: 0.8071
Body Part Number: 413
Disease Precision: 0.7790
Disease Recall: 0.8133
Disease F1: 0.7958
Disease Number: 975
Family Member Precision: 0.8286
Family Member Recall: 0.9667
Family Member F1: 0.8923
Family Member Number: 30
Medication Precision: 0.8913
Medication Recall: 0.8817
Medication F1: 0.8865
Medication Number: 93
Procedure Precision: 0.7130
Procedure Recall: 0.7910
Procedure F1: 0.75
Procedure Number: 311
Overall Precision: 0.7758
Overall Recall: 0.8183
Overall F1: 0.7965
Overall Accuracy: 0.9382

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: 13
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Body Part Precision	Body Part Recall	Body Part F1	Body Part Number	Disease Precision	Disease Recall	Disease F1	Disease Number	Family Member Precision	Family Member Recall	Family Member F1	Family Member Number	Medication Precision	Medication Recall	Medication F1	Medication Number	Procedure Precision	Procedure Recall	Procedure F1	Procedure Number	Overall Precision	Overall Recall	Overall F1	Overall Accuracy
0.2998	1.0	1004	0.2127	0.7460	0.7893	0.7671	413	0.7612	0.7815	0.7713	975	0.9062	0.9667	0.9355	30	0.8462	0.8280	0.8370	93	0.6583	0.7556	0.7036	311	0.7450	0.7843	0.7642	0.9331
0.1566	2.0	2008	0.2278	0.7780	0.8232	0.8	413	0.7847	0.8	0.7923	975	0.8529	0.9667	0.9062	30	0.8710	0.8710	0.8710	93	0.7346	0.7653	0.7496	311	0.7800	0.8057	0.7927	0.9367
0.1089	3.0	3012	0.2338	0.7894	0.8257	0.8071	413	0.7790	0.8133	0.7958	975	0.8286	0.9667	0.8923	30	0.8913	0.8817	0.8865	93	0.7130	0.7910	0.75	311	0.7758	0.8183	0.7965	0.9382

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

bastianchinchon/nominal-groups-recognition-beto-clinical-wl-es

nominal-groups-recognition-beto-clinical-wl-es

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

bastianchinchon/
nominal-groups-recognition-beto-clinical-wl-es