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SU-FMI-AI/
multiclinner-enigma-es-procedure-xlm-roberta-large

Name: multiclinner-enigma-es-procedure-xlm-roberta-large
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xlm-roberta-large-spanish-clinical_es_procedure

This model is a fine-tuned version of llange/xlm-roberta-large-spanish-clinical on an unknown dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 10

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1125	1.0	739	0.0442	0.8994	0.8897	0.8945	0.9826
0.0660	2.0	1478	0.0300	0.9071	0.9356	0.9211	0.9879
0.0382	3.0	2217	0.0199	0.9235	0.9649	0.9437	0.9923
0.0314	4.0	2956	0.0137	0.9530	0.9724	0.9626	0.9947
0.0182	5.0	3695	0.0085	0.9764	0.9829	0.9797	0.9973
0.0140	6.0	4434	0.0059	0.9811	0.9903	0.9857	0.9980
0.0088	7.0	5173	0.0033	0.9888	0.9939	0.9913	0.9989
0.0069	8.0	5912	0.0023	0.9915	0.9971	0.9943	0.9993
0.0042	9.0	6651	0.0014	0.9958	0.9967	0.9962	0.9995
0.0033	10.0	7390	0.0013	0.9958	0.9979	0.9969	0.9996