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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: BERT_ep8_lr2
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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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# BERT_ep8_lr2
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This model is a fine-tuned version of [ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT](https://huggingface.co/ajtamayoh/NER_EHR_Spanish_model_Mulitlingual_BERT) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0940
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- Precision: 0.8489
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- Recall: 0.8716
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- F1: 0.8601
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- Accuracy: 0.9771
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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-06
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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: 8
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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 | 1.0 | 467 | 0.0850 | 0.8142 | 0.8377 | 0.8257 | 0.9730 |
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| 0.1137 | 2.0 | 934 | 0.0799 | 0.8402 | 0.8534 | 0.8467 | 0.9757 |
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| 0.0746 | 3.0 | 1401 | 0.0825 | 0.8416 | 0.8614 | 0.8514 | 0.9765 |
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| 0.0588 | 4.0 | 1868 | 0.0863 | 0.8560 | 0.8652 | 0.8606 | 0.9769 |
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| 0.0482 | 5.0 | 2335 | 0.0885 | 0.8553 | 0.8646 | 0.8599 | 0.9771 |
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| 0.0402 | 6.0 | 2802 | 0.0893 | 0.8520 | 0.8668 | 0.8593 | 0.9776 |
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| 0.0362 | 7.0 | 3269 | 0.0916 | 0.8480 | 0.8726 | 0.8601 | 0.9772 |
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| 0.0336 | 8.0 | 3736 | 0.0940 | 0.8489 | 0.8716 | 0.8601 | 0.9771 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 2.0.0+cu118
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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