BERT_ep7_lr3
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: 0.1056
- Precision: 0.7587
- Recall: 0.8152
- F1: 0.7859
- Accuracy: 0.9660
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-07
- 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 |
---|---|---|---|---|---|---|---|
No log | 1.0 | 467 | 0.1336 | 0.7056 | 0.7382 | 0.7215 | 0.9572 |
0.1804 | 2.0 | 934 | 0.1171 | 0.7285 | 0.7769 | 0.7519 | 0.9617 |
0.1226 | 3.0 | 1401 | 0.1116 | 0.7354 | 0.7995 | 0.7661 | 0.9637 |
0.1118 | 4.0 | 1868 | 0.1084 | 0.7478 | 0.8044 | 0.7750 | 0.9648 |
0.103 | 5.0 | 2335 | 0.1066 | 0.7564 | 0.8120 | 0.7832 | 0.9656 |
0.1003 | 6.0 | 2802 | 0.1061 | 0.7566 | 0.8144 | 0.7844 | 0.9658 |
0.1035 | 7.0 | 3269 | 0.1056 | 0.7587 | 0.8152 | 0.7859 | 0.9660 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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