metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: Negation_Scope_Detection_NubEs_Training_Development_mBERT_fine_tuned
    results: []
widget:
  - text: >-
      Paciente con diagnóstico de ELA en abril de 2015 que presenta desde hace
      más de dos meses disfagia progresiva, para líquidos preferentemente, con
      dos neumonías por aspiración, por lo que se programa ingreso para
      colocación de sonda de gastrostomía, realizándose el día 31 de diciembre,
      sin complicaciones y tolerando posteriormente la dieta por gastrostomía.

Negation_Scope_Detection_NubEs_Training_Development_mBERT_fine_tuned

This model is a fine-tuned version of bert-base-multilingual-cased on NubEs (Training + Development) dataset. It achieves the following results on the evaluation set:

Loss: 0.1712
Precision: 0.8970
Recall: 0.9177
F1: 0.9072
Accuracy: 0.9722

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: 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: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1805	1.0	1726	0.1542	0.8408	0.8600	0.8503	0.9591
0.126	2.0	3452	0.1271	0.8652	0.8774	0.8713	0.9640
0.0814	3.0	5178	0.1395	0.8715	0.8881	0.8797	0.9662
0.0447	4.0	6904	0.1326	0.8893	0.9068	0.8979	0.9696
0.0247	5.0	8630	0.1805	0.9012	0.9020	0.9016	0.9708
0.0156	6.0	10356	0.1524	0.8972	0.9120	0.9045	0.9706
0.0056	7.0	12082	0.1712	0.8970	0.9177	0.9072	0.9722

Framework versions

Transformers 4.27.3
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2