BERT_ep5_lr4
This model is a fine-tuned version of ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2107
- Precision: 0.6683
- Recall: 0.7027
- F1: 0.6851
- Accuracy: 0.9463
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-08
- 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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 467 | 0.2604 | 0.6839 | 0.6767 | 0.6803 | 0.9435 |
0.2766 | 2.0 | 934 | 0.2361 | 0.6769 | 0.6897 | 0.6832 | 0.9448 |
0.2401 | 3.0 | 1401 | 0.2212 | 0.6732 | 0.6994 | 0.6861 | 0.9456 |
0.2253 | 4.0 | 1868 | 0.2131 | 0.6695 | 0.7016 | 0.6852 | 0.9462 |
0.2103 | 5.0 | 2335 | 0.2107 | 0.6683 | 0.7027 | 0.6851 | 0.9463 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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