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--- |
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license: apache-2.0 |
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base_model: PlanTL-GOB-ES/bsc-bio-ehr-es |
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tags: |
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- token-classification |
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- generated_from_trainer |
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datasets: |
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- Rodrigo1771/multi-train-drugtemist-dev-ner |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: output |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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dataset: |
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name: Rodrigo1771/multi-train-drugtemist-dev-ner |
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type: Rodrigo1771/multi-train-drugtemist-dev-ner |
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config: MultiTrainDrugTEMISTDevNER |
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split: validation |
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args: MultiTrainDrugTEMISTDevNER |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.09691960931630353 |
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- name: Recall |
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type: recall |
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value: 0.9485294117647058 |
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- name: F1 |
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type: f1 |
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value: 0.17586912065439672 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8099635429897495 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# output |
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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/multi-train-drugtemist-dev-ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6631 |
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- Precision: 0.0969 |
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- Recall: 0.9485 |
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- F1: 0.1759 |
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- Accuracy: 0.8100 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:------:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.2596 | 0.9997 | 1701 | 0.7913 | 0.0793 | 0.9366 | 0.1462 | 0.7672 | |
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| 0.1853 | 2.0 | 3403 | 0.6631 | 0.0969 | 0.9485 | 0.1759 | 0.8100 | |
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| 0.1254 | 2.9997 | 5104 | 1.0729 | 0.0906 | 0.9421 | 0.1653 | 0.7755 | |
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| 0.0823 | 4.0 | 6806 | 1.2568 | 0.0888 | 0.9504 | 0.1624 | 0.7719 | |
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| 0.0597 | 4.9997 | 8507 | 1.1908 | 0.0941 | 0.9375 | 0.1710 | 0.7837 | |
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| 0.0446 | 6.0 | 10209 | 1.3844 | 0.0944 | 0.9504 | 0.1718 | 0.7812 | |
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| 0.0325 | 6.9997 | 11910 | 1.5515 | 0.0937 | 0.9476 | 0.1705 | 0.7866 | |
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| 0.022 | 8.0 | 13612 | 1.6300 | 0.0926 | 0.9559 | 0.1689 | 0.7843 | |
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| 0.017 | 8.9997 | 15313 | 1.7459 | 0.0929 | 0.9531 | 0.1693 | 0.7845 | |
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| 0.0135 | 9.9971 | 17010 | 1.7861 | 0.0927 | 0.9522 | 0.1690 | 0.7846 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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