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bert-finetuned-ner-clinical-plncmm-11
This model is a fine-tuned version of plncmm/beto-clinical-wl-es on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2494
- Precision: 0.7577
- Recall: 0.8238
- F1: 0.7894
- Accuracy: 0.9335
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 429 | 0.2466 | 0.6776 | 0.7728 | 0.7221 | 0.9190 |
0.6369 | 2.0 | 858 | 0.2398 | 0.7437 | 0.8156 | 0.7780 | 0.9290 |
0.195 | 3.0 | 1287 | 0.2366 | 0.7515 | 0.8150 | 0.7820 | 0.9329 |
0.1223 | 4.0 | 1716 | 0.2494 | 0.7577 | 0.8238 | 0.7894 | 0.9335 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3