BERT_ep8_lr5
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: 0.2950
- Precision: 0.6748
- Recall: 0.6332
- F1: 0.6534
- Accuracy: 0.9420
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-09
- 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 | 0.3067 | 0.6768 | 0.6258 | 0.6503 | 0.9415 |
0.2941 | 2.0 | 934 | 0.3029 | 0.6753 | 0.6283 | 0.6510 | 0.9417 |
0.2874 | 3.0 | 1401 | 0.2999 | 0.6764 | 0.6302 | 0.6525 | 0.9418 |
0.2821 | 4.0 | 1868 | 0.2978 | 0.6761 | 0.6316 | 0.6531 | 0.9420 |
0.2828 | 5.0 | 2335 | 0.2963 | 0.6749 | 0.6321 | 0.6528 | 0.9421 |
0.2829 | 6.0 | 2802 | 0.2954 | 0.6748 | 0.6332 | 0.6534 | 0.9421 |
0.2808 | 7.0 | 3269 | 0.2951 | 0.6750 | 0.6332 | 0.6535 | 0.9421 |
0.2841 | 8.0 | 3736 | 0.2950 | 0.6748 | 0.6332 | 0.6534 | 0.9420 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
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