BERT_ep5_lr1_v1
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: 0.1313
- Precision: 0.8697
- Recall: 0.8861
- F1: 0.8778
- Accuracy: 0.9769
Model description
More information needed
Intended uses & limitations
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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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 467 | 0.0936 | 0.8366 | 0.8619 | 0.8491 | 0.9731 |
0.1034 | 2.0 | 934 | 0.0847 | 0.8434 | 0.8761 | 0.8595 | 0.9746 |
0.0538 | 3.0 | 1401 | 0.1063 | 0.8589 | 0.8783 | 0.8685 | 0.9749 |
0.0274 | 4.0 | 1868 | 0.1101 | 0.8607 | 0.8783 | 0.8694 | 0.9757 |
0.0163 | 5.0 | 2335 | 0.1313 | 0.8697 | 0.8861 | 0.8778 | 0.9769 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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