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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_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_ep8_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: 0.1511
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- Precision: 0.8632
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- Recall: 0.8810
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- F1: 0.8720
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- Accuracy: 0.9767
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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: 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 | 0.0949 | 0.8056 | 0.8604 | 0.8321 | 0.9704 |
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| 0.101 | 2.0 | 934 | 0.0978 | 0.8174 | 0.8876 | 0.8511 | 0.9725 |
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| 0.0544 | 3.0 | 1401 | 0.0959 | 0.8384 | 0.8785 | 0.8580 | 0.9739 |
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| 0.0331 | 4.0 | 1868 | 0.1018 | 0.8497 | 0.8841 | 0.8665 | 0.9749 |
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| 0.0182 | 5.0 | 2335 | 0.1375 | 0.8658 | 0.8686 | 0.8672 | 0.9758 |
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| 0.0133 | 6.0 | 2802 | 0.1458 | 0.8547 | 0.8843 | 0.8692 | 0.9753 |
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| 0.0064 | 7.0 | 3269 | 0.1418 | 0.8628 | 0.8813 | 0.8719 | 0.9763 |
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| 0.0041 | 8.0 | 3736 | 0.1511 | 0.8632 | 0.8810 | 0.8720 | 0.9767 |
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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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