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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_lr5
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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_lr5
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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: 0.2950
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- Precision: 0.6748
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- Recall: 0.6332
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- F1: 0.6534
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- Accuracy: 0.9420
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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-09
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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 | 0.3067 | 0.6768 | 0.6258 | 0.6503 | 0.9415 |
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| 0.2941 | 2.0 | 934 | 0.3029 | 0.6753 | 0.6283 | 0.6510 | 0.9417 |
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| 0.2874 | 3.0 | 1401 | 0.2999 | 0.6764 | 0.6302 | 0.6525 | 0.9418 |
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| 0.2821 | 4.0 | 1868 | 0.2978 | 0.6761 | 0.6316 | 0.6531 | 0.9420 |
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| 0.2828 | 5.0 | 2335 | 0.2963 | 0.6749 | 0.6321 | 0.6528 | 0.9421 |
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| 0.2829 | 6.0 | 2802 | 0.2954 | 0.6748 | 0.6332 | 0.6534 | 0.9421 |
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| 0.2808 | 7.0 | 3269 | 0.2951 | 0.6750 | 0.6332 | 0.6535 | 0.9421 |
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| 0.2841 | 8.0 | 3736 | 0.2950 | 0.6748 | 0.6332 | 0.6534 | 0.9420 |
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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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