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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_ep6_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_ep6_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: 0.0943
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- Precision: 0.8387
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- Recall: 0.8727
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- F1: 0.8554
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- Accuracy: 0.9748
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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: 6
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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 | 0.0925 | 0.7979 | 0.8341 | 0.8156 | 0.9701 |
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| 0.1097 | 2.0 | 934 | 0.0869 | 0.8285 | 0.8621 | 0.8450 | 0.9730 |
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| 0.0748 | 3.0 | 1401 | 0.0894 | 0.8233 | 0.8770 | 0.8493 | 0.9737 |
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| 0.06 | 4.0 | 1868 | 0.0917 | 0.8240 | 0.8784 | 0.8503 | 0.9735 |
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| 0.0467 | 5.0 | 2335 | 0.0922 | 0.8315 | 0.8748 | 0.8526 | 0.9744 |
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| 0.0442 | 6.0 | 2802 | 0.0943 | 0.8387 | 0.8727 | 0.8554 | 0.9748 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 1.13.1+cu116
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- Datasets 2.11.0
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- Tokenizers 0.13.2
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