| --- |
| license: apache-2.0 |
| base_model: PlanTL-GOB-ES/bsc-bio-ehr-es |
| tags: |
| - token-classification |
| - generated_from_trainer |
| datasets: |
| - Rodrigo1771/combined-train-distemist-dev-ner |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: output |
| results: |
| - task: |
| name: Token Classification |
| type: token-classification |
| dataset: |
| name: Rodrigo1771/combined-train-distemist-dev-ner |
| type: Rodrigo1771/combined-train-distemist-dev-ner |
| config: CombinedTrainDisTEMISTDevNER |
| split: validation |
| args: CombinedTrainDisTEMISTDevNER |
| metrics: |
| - name: Precision |
| type: precision |
| value: 0.32197630636422075 |
| - name: Recall |
| type: recall |
| value: 0.8203088441740758 |
| - name: F1 |
| type: f1 |
| value: 0.4624414693662204 |
| - name: Accuracy |
| type: accuracy |
| value: 0.8601754843670617 |
| --- |
| |
| <!-- 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. --> |
|
|
| # output |
|
|
| 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 Rodrigo1771/combined-train-distemist-dev-ner dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6266 |
| - Precision: 0.3220 |
| - Recall: 0.8203 |
| - F1: 0.4624 |
| - Accuracy: 0.8602 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - gradient_accumulation_steps: 2 |
| - total_train_batch_size: 64 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10.0 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | No log | 0.9988 | 425 | 0.3834 | 0.2920 | 0.7819 | 0.4252 | 0.8517 | |
| | 0.3349 | 2.0 | 851 | 0.5730 | 0.2681 | 0.8070 | 0.4025 | 0.8221 | |
| | 0.1788 | 2.9988 | 1276 | 0.5796 | 0.2848 | 0.8009 | 0.4202 | 0.8338 | |
| | 0.1227 | 4.0 | 1702 | 0.6591 | 0.2996 | 0.8109 | 0.4376 | 0.8388 | |
| | 0.0856 | 4.9988 | 2127 | 0.6266 | 0.3220 | 0.8203 | 0.4624 | 0.8602 | |
| | 0.0597 | 6.0 | 2553 | 0.7859 | 0.3075 | 0.8112 | 0.4460 | 0.8476 | |
| | 0.0597 | 6.9988 | 2978 | 0.8297 | 0.3137 | 0.8166 | 0.4532 | 0.8508 | |
| | 0.0458 | 8.0 | 3404 | 0.8468 | 0.3135 | 0.8205 | 0.4536 | 0.8532 | |
| | 0.0343 | 8.9988 | 3829 | 0.9241 | 0.3085 | 0.8182 | 0.4481 | 0.8494 | |
| | 0.0292 | 9.9882 | 4250 | 0.9384 | 0.3100 | 0.8163 | 0.4494 | 0.8499 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.4 |
| - Pytorch 2.4.0+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
| |
