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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_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_ep6_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: 0.2877
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- Precision: 0.6804
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- Recall: 0.6408
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- F1: 0.6600
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- Accuracy: 0.9429
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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: 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 | 0.2952 | 0.6845 | 0.6360 | 0.6593 | 0.9425 |
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| 0.2949 | 2.0 | 934 | 0.2919 | 0.6823 | 0.6379 | 0.6594 | 0.9428 |
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| 0.2961 | 3.0 | 1401 | 0.2897 | 0.6819 | 0.6395 | 0.6600 | 0.9428 |
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| 0.2845 | 4.0 | 1868 | 0.2884 | 0.6809 | 0.6406 | 0.6601 | 0.9428 |
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| 0.29 | 5.0 | 2335 | 0.2878 | 0.6799 | 0.6406 | 0.6597 | 0.9429 |
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| 0.2835 | 6.0 | 2802 | 0.2877 | 0.6804 | 0.6408 | 0.6600 | 0.9429 |
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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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