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--- |
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library_name: transformers |
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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-85-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-85-ner |
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type: Rodrigo1771/distemist-85-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: 0.803175344384777 |
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- name: Recall |
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type: recall |
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value: 0.8048666354702855 |
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- name: F1 |
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type: f1 |
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value: 0.8040201005025126 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9764853694371592 |
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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-85-ner dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1424 |
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- Precision: 0.8032 |
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- Recall: 0.8049 |
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- F1: 0.8040 |
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- Accuracy: 0.9765 |
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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 | 0.9990 | 499 | 0.0739 | 0.7271 | 0.7953 | 0.7596 | 0.9731 | |
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| 0.105 | 2.0 | 999 | 0.0908 | 0.7436 | 0.7890 | 0.7656 | 0.9729 | |
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| 0.0448 | 2.9990 | 1498 | 0.0930 | 0.7676 | 0.7990 | 0.7830 | 0.9744 | |
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| 0.0255 | 4.0 | 1998 | 0.1052 | 0.7806 | 0.7983 | 0.7894 | 0.9757 | |
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| 0.0164 | 4.9990 | 2497 | 0.1100 | 0.7756 | 0.8007 | 0.7879 | 0.9750 | |
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| 0.0112 | 6.0 | 2997 | 0.1266 | 0.7869 | 0.8124 | 0.7994 | 0.9768 | |
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| 0.0073 | 6.9990 | 3496 | 0.1288 | 0.7929 | 0.8009 | 0.7969 | 0.9763 | |
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| 0.0054 | 8.0 | 3996 | 0.1424 | 0.8032 | 0.8049 | 0.8040 | 0.9765 | |
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| 0.0038 | 8.9990 | 4495 | 0.1455 | 0.7901 | 0.8042 | 0.7971 | 0.9765 | |
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| 0.0028 | 9.9900 | 4990 | 0.1497 | 0.7898 | 0.8072 | 0.7984 | 0.9768 | |
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### Framework versions |
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- Transformers 4.44.2 |
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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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