<!-- 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-4
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: 0.2677
- Precision: 0.7664
- Recall: 0.8337
- F1: 0.7986
- Accuracy: 0.9369
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: 16
- 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 |
---|---|---|---|---|---|---|---|
0.6626 | 1.0 | 857 | 0.2329 | 0.7139 | 0.8068 | 0.7575 | 0.9251 |
0.1834 | 2.0 | 1714 | 0.2479 | 0.7246 | 0.8216 | 0.7701 | 0.9268 |
0.1162 | 3.0 | 2571 | 0.2504 | 0.7616 | 0.8310 | 0.7948 | 0.9336 |
0.0862 | 4.0 | 3428 | 0.2677 | 0.7664 | 0.8337 | 0.7986 | 0.9369 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3