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BERT_ep7_lr5_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: 0.2884
- Precision: 0.6752
- Recall: 0.6436
- F1: 0.6590
- Accuracy: 0.9415
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: 7
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 467 | 0.2972 | 0.6754 | 0.6363 | 0.6553 | 0.9413 |
0.2981 | 2.0 | 934 | 0.2939 | 0.6742 | 0.6387 | 0.6560 | 0.9413 |
0.2882 | 3.0 | 1401 | 0.2915 | 0.6747 | 0.6409 | 0.6574 | 0.9414 |
0.2913 | 4.0 | 1868 | 0.2898 | 0.6744 | 0.6422 | 0.6579 | 0.9414 |
0.2852 | 5.0 | 2335 | 0.2889 | 0.6741 | 0.6425 | 0.6579 | 0.9415 |
0.2883 | 6.0 | 2802 | 0.2885 | 0.6752 | 0.6436 | 0.6590 | 0.9415 |
0.2819 | 7.0 | 3269 | 0.2884 | 0.6752 | 0.6436 | 0.6590 | 0.9415 |
Framework versions
- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2