| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - wl-disease |
| | model-index: |
| | - name: WL_DISEASE_NER_v1 |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # WL_DISEASE_NER_v1 |
| | |
| | This model is a fine-tuned version of [PlanTL-GOB-ES/bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es) on the wl-disease dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.1489 |
| | - Diso Precision: 0.7908 |
| | - Diso Recall: 0.8397 |
| | - Diso F1: 0.8145 |
| | - Diso Number: 1765 |
| | - Overall Precision: 0.7908 |
| | - Overall Recall: 0.8397 |
| | - Overall F1: 0.8145 |
| | - Overall Accuracy: 0.9631 |
| | |
| | ## 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 | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------------:|:-----------:|:-------:|:-----------:|:-----------------:|:--------------:|:----------:|:----------------:| |
| | | 0.1199 | 1.0 | 1714 | 0.1187 | 0.7739 | 0.7972 | 0.7854 | 1765 | 0.7739 | 0.7972 | 0.7854 | 0.9610 | |
| | | 0.0916 | 2.0 | 3428 | 0.1237 | 0.7748 | 0.8266 | 0.7999 | 1765 | 0.7748 | 0.8266 | 0.7999 | 0.9620 | |
| | | 0.0625 | 3.0 | 5142 | 0.1343 | 0.7900 | 0.8289 | 0.8090 | 1765 | 0.7900 | 0.8289 | 0.8090 | 0.9630 | |
| | | 0.0485 | 4.0 | 6856 | 0.1489 | 0.7908 | 0.8397 | 0.8145 | 1765 | 0.7908 | 0.8397 | 0.8145 | 0.9631 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.26.0 |
| | - Pytorch 1.13.1+cu116 |
| | - Datasets 2.9.0 |
| | - Tokenizers 0.13.2 |
| | |
