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bert-finetuned-ner-clinical-BETO-uncased-4
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4171
- Precision: 0.7142
- Recall: 0.7722
- F1: 0.7421
- Accuracy: 0.9150
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: 16
- eval_batch_size: 16
- seed: 42
- 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 | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.0602 | 1.0 | 502 | 0.3957 | 0.7006 | 0.7552 | 0.7269 | 0.9089 |
0.0596 | 2.0 | 1004 | 0.3879 | 0.7198 | 0.7629 | 0.7407 | 0.9146 |
0.0575 | 3.0 | 1506 | 0.4171 | 0.7142 | 0.7722 | 0.7421 | 0.9150 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3