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bert-finetuned-ner-clinical-BETO-uncased-2
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: 0.3403
- Precision: 0.6910
- Recall: 0.7475
- F1: 0.7182
- Accuracy: 0.9141
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 251 | 0.2860 | 0.6709 | 0.7585 | 0.7120 | 0.9106 |
0.1602 | 2.0 | 502 | 0.2931 | 0.7025 | 0.7453 | 0.7233 | 0.9138 |
0.1602 | 3.0 | 753 | 0.3166 | 0.7044 | 0.7415 | 0.7225 | 0.9143 |
0.093 | 4.0 | 1004 | 0.3403 | 0.6910 | 0.7475 | 0.7182 | 0.9141 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3