<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
bert-finetuned-ner-clinical-plncmm-large-6
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: 0.2564
- Precision: 0.7685
- Recall: 0.8364
- F1: 0.8011
- Accuracy: 0.9350
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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 429 | 0.2349 | 0.7107 | 0.8183 | 0.7607 | 0.9245 |
0.3161 | 2.0 | 858 | 0.2470 | 0.7442 | 0.8238 | 0.7820 | 0.9271 |
0.1608 | 3.0 | 1287 | 0.2427 | 0.7555 | 0.8244 | 0.7885 | 0.9329 |
0.1088 | 4.0 | 1716 | 0.2564 | 0.7685 | 0.8364 | 0.8011 | 0.9350 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3