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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_ep9_lr3
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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_ep9_lr3
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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: 0.0904
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- Precision: 0.7736
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- Recall: 0.8277
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- F1: 0.7997
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- Accuracy: 0.9699
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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-07
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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: 9
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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 | 0.1271 | 0.6992 | 0.7545 | 0.7258 | 0.9582 |
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| 0.1807 | 2.0 | 934 | 0.1061 | 0.7236 | 0.7831 | 0.7521 | 0.9638 |
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| 0.126 | 3.0 | 1401 | 0.0988 | 0.7443 | 0.8029 | 0.7725 | 0.9663 |
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| 0.113 | 4.0 | 1868 | 0.0954 | 0.7534 | 0.8183 | 0.7845 | 0.9677 |
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| 0.1072 | 5.0 | 2335 | 0.0927 | 0.7634 | 0.8164 | 0.7890 | 0.9688 |
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| 0.1014 | 6.0 | 2802 | 0.0918 | 0.7700 | 0.8255 | 0.7968 | 0.9694 |
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| 0.0982 | 7.0 | 3269 | 0.0910 | 0.7726 | 0.8277 | 0.7992 | 0.9696 |
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| 0.0977 | 8.0 | 3736 | 0.0905 | 0.7739 | 0.8282 | 0.8002 | 0.9698 |
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| 0.0938 | 9.0 | 4203 | 0.0904 | 0.7736 | 0.8277 | 0.7997 | 0.9699 |
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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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