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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/distemist-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/distemist-ner |
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type: Rodrigo1771/distemist-ner |
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config: DisTEMIST NER |
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split: validation |
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args: DisTEMIST NER |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.7938948817994033 |
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- name: Recall |
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type: recall |
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value: 0.8093121197941039 |
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- name: F1 |
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type: f1 |
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value: 0.8015293708724366 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9767668584453568 |
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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/distemist-ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1294 |
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- Precision: 0.7939 |
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- Recall: 0.8093 |
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- F1: 0.8015 |
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- Accuracy: 0.9768 |
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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: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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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| No log | 0.9988 | 425 | 0.0738 | 0.7233 | 0.7866 | 0.7536 | 0.9733 | |
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| 0.0996 | 2.0 | 851 | 0.0787 | 0.7364 | 0.8065 | 0.7698 | 0.9743 | |
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| 0.0458 | 2.9988 | 1276 | 0.0788 | 0.7715 | 0.8154 | 0.7929 | 0.9759 | |
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| 0.0279 | 4.0 | 1702 | 0.0922 | 0.7754 | 0.8112 | 0.7929 | 0.9757 | |
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| 0.0169 | 4.9988 | 2127 | 0.0994 | 0.7585 | 0.8163 | 0.7863 | 0.9744 | |
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| 0.0114 | 6.0 | 2553 | 0.1080 | 0.7766 | 0.8058 | 0.7909 | 0.9765 | |
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| 0.0114 | 6.9988 | 2978 | 0.1166 | 0.7792 | 0.8100 | 0.7943 | 0.9760 | |
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| 0.0079 | 8.0 | 3404 | 0.1294 | 0.7939 | 0.8093 | 0.8015 | 0.9768 | |
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| 0.0053 | 8.9988 | 3829 | 0.1340 | 0.7876 | 0.8105 | 0.7989 | 0.9766 | |
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| 0.0038 | 9.9882 | 4250 | 0.1367 | 0.7882 | 0.8098 | 0.7988 | 0.9767 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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