BERT_ep8_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: 0.1754
- Precision: 0.6822
- Recall: 0.7097
- F1: 0.6957
- Accuracy: 0.9504
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: 8
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 467 | 0.2549 | 0.6812 | 0.6660 | 0.6735 | 0.9454 |
0.2775 | 2.0 | 934 | 0.2278 | 0.6778 | 0.6814 | 0.6796 | 0.9469 |
0.2438 | 3.0 | 1401 | 0.2086 | 0.6772 | 0.6935 | 0.6852 | 0.9481 |
0.2135 | 4.0 | 1868 | 0.1949 | 0.6780 | 0.7001 | 0.6889 | 0.9489 |
0.2058 | 5.0 | 2335 | 0.1856 | 0.6808 | 0.7057 | 0.6931 | 0.9496 |
0.1937 | 6.0 | 2802 | 0.1796 | 0.6810 | 0.7073 | 0.6939 | 0.9499 |
0.1818 | 7.0 | 3269 | 0.1763 | 0.6831 | 0.7097 | 0.6962 | 0.9503 |
0.1835 | 8.0 | 3736 | 0.1754 | 0.6822 | 0.7097 | 0.6957 | 0.9504 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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