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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_ep7_lr1
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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_ep7_lr1
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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: 0.1449
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- Precision: 0.8612
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- Recall: 0.8723
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- F1: 0.8667
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- Accuracy: 0.9764
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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-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: 7
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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 | 0.0884 | 0.8278 | 0.8351 | 0.8314 | 0.9737 |
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| 0.1032 | 2.0 | 934 | 0.0841 | 0.8327 | 0.8591 | 0.8457 | 0.9739 |
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| 0.0556 | 3.0 | 1401 | 0.0941 | 0.8699 | 0.8654 | 0.8677 | 0.9762 |
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| 0.0317 | 4.0 | 1868 | 0.1146 | 0.8697 | 0.8654 | 0.8676 | 0.9764 |
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| 0.0202 | 5.0 | 2335 | 0.1323 | 0.8736 | 0.8621 | 0.8678 | 0.9767 |
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| 0.0114 | 6.0 | 2802 | 0.1385 | 0.8563 | 0.8766 | 0.8663 | 0.9758 |
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| 0.0064 | 7.0 | 3269 | 0.1449 | 0.8612 | 0.8723 | 0.8667 | 0.9764 |
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### Framework versions
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- Transformers 4.27.3
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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