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README.md
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---
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license: apache-2.0
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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: roberta-base-biomedical-clinical-es-finetuned-ner-CRAFT_Augmented_ES
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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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# roberta-base-biomedical-clinical-es-finetuned-ner-CRAFT_Augmented_ES
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This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-biomedical-clinical-es](https://huggingface.co/PlanTL-GOB-ES/roberta-base-biomedical-clinical-es) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2224
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- Precision: 0.8298
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- Recall: 0.8306
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- F1: 0.8302
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- Accuracy: 0.9659
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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: 3e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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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: 4
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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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| 0.0624 | 1.0 | 4078 | 0.1844 | 0.8002 | 0.7923 | 0.7963 | 0.9607 |
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| 0.0284 | 2.0 | 8156 | 0.1937 | 0.8394 | 0.7988 | 0.8186 | 0.9637 |
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| 0.0118 | 3.0 | 12234 | 0.2007 | 0.8285 | 0.8232 | 0.8258 | 0.9649 |
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| 0.0043 | 4.0 | 16312 | 0.2224 | 0.8298 | 0.8306 | 0.8302 | 0.9659 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.10.0+cu111
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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