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distemist_NER_test
This model is a fine-tuned version of PlanTL-GOB-ES/bsc-bio-ehr-es on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0927
- Diso Precision: 0.7135
- Diso Recall: 0.7799
- Diso F1: 0.7452
- Diso Number: 1440
- Overall Precision: 0.7135
- Overall Recall: 0.7799
- Overall F1: 0.7452
- Overall Accuracy: 0.9760
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: 2e-05
- 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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Diso Precision | Diso Recall | Diso F1 | Diso Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.0992 | 1.0 | 1169 | 0.0778 | 0.6166 | 0.7639 | 0.6824 | 1440 | 0.6166 | 0.7639 | 0.6824 | 0.9705 |
| 0.0603 | 2.0 | 2338 | 0.0721 | 0.6867 | 0.7840 | 0.7322 | 1440 | 0.6867 | 0.7840 | 0.7322 | 0.9757 |
| 0.0371 | 3.0 | 3507 | 0.0812 | 0.7182 | 0.7736 | 0.7449 | 1440 | 0.7182 | 0.7736 | 0.7449 | 0.9764 |
| 0.0198 | 4.0 | 4676 | 0.0927 | 0.7135 | 0.7799 | 0.7452 | 1440 | 0.7135 | 0.7799 | 0.7452 | 0.9760 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2
