BERT_ep5_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: 0.1084
- Precision: 0.7410
- Recall: 0.8133
- F1: 0.7755
- Accuracy: 0.9642
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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 467 | 0.1346 | 0.6944 | 0.7588 | 0.7252 | 0.9561 |
0.1797 | 2.0 | 934 | 0.1167 | 0.7186 | 0.7843 | 0.7500 | 0.9612 |
0.1243 | 3.0 | 1401 | 0.1115 | 0.7299 | 0.8041 | 0.7652 | 0.9631 |
0.1136 | 4.0 | 1868 | 0.1090 | 0.7384 | 0.8125 | 0.7737 | 0.9640 |
0.1081 | 5.0 | 2335 | 0.1084 | 0.7410 | 0.8133 | 0.7755 | 0.9642 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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