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bert-finetuned-ner-clinical-plncmm-10
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: 0.2660
- Precision: 0.7318
- Recall: 0.7997
- F1: 0.7642
- Accuracy: 0.9251
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 | 251 | 0.3015 | 0.6270 | 0.6976 | 0.6604 | 0.9029 |
0.5949 | 2.0 | 502 | 0.2527 | 0.7019 | 0.7870 | 0.7420 | 0.9176 |
0.5949 | 3.0 | 753 | 0.2438 | 0.7211 | 0.8117 | 0.7637 | 0.9239 |
0.1454 | 4.0 | 1004 | 0.2660 | 0.7318 | 0.7997 | 0.7642 | 0.9251 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3