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license: apache-2.0 |
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base_model: PlanTL-GOB-ES/roberta-base-biomedical-es |
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tags: |
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- generated_from_trainer |
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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: biomedical-roberta-finetuned-iomed_task |
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results: [] |
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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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# biomedical-roberta-finetuned-iomed_task |
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This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-biomedical-es](https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-es) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0582 |
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- Precision: 0.2269 |
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- Recall: 0.4283 |
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- F1: 0.2966 |
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- Accuracy: 0.7695 |
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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: 2.1e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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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: 20 |
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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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| 1.2536 | 2.0 | 1520 | 1.2135 | 0.1082 | 0.2685 | 0.1542 | 0.7422 | |
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| 1.0249 | 4.0 | 3040 | 1.0510 | 0.1448 | 0.3244 | 0.2002 | 0.7650 | |
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| 0.9 | 6.0 | 4560 | 1.0098 | 0.1587 | 0.3512 | 0.2186 | 0.7694 | |
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| 0.8002 | 8.0 | 6080 | 1.0143 | 0.1835 | 0.3795 | 0.2474 | 0.7664 | |
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| 0.7195 | 10.0 | 7600 | 1.0173 | 0.2007 | 0.4055 | 0.2685 | 0.7691 | |
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| 0.693 | 12.0 | 9120 | 1.0218 | 0.1991 | 0.4079 | 0.2676 | 0.7683 | |
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| 0.6139 | 14.0 | 10640 | 1.0394 | 0.2063 | 0.4071 | 0.2738 | 0.7672 | |
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| 0.616 | 16.0 | 12160 | 1.0376 | 0.2141 | 0.4142 | 0.2823 | 0.7695 | |
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| 0.5911 | 18.0 | 13680 | 1.0491 | 0.2240 | 0.4268 | 0.2938 | 0.7697 | |
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| 0.6042 | 20.0 | 15200 | 1.0582 | 0.2269 | 0.4283 | 0.2966 | 0.7695 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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