---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep9_lr3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# BERT_ep9_lr3

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.
It achieves the following results on the evaluation set:
- Loss: 0.0904
- Precision: 0.7736
- Recall: 0.8277
- F1: 0.7997
- Accuracy: 0.9699

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 467  | 0.1271          | 0.6992    | 0.7545 | 0.7258 | 0.9582   |
| 0.1807        | 2.0   | 934  | 0.1061          | 0.7236    | 0.7831 | 0.7521 | 0.9638   |
| 0.126         | 3.0   | 1401 | 0.0988          | 0.7443    | 0.8029 | 0.7725 | 0.9663   |
| 0.113         | 4.0   | 1868 | 0.0954          | 0.7534    | 0.8183 | 0.7845 | 0.9677   |
| 0.1072        | 5.0   | 2335 | 0.0927          | 0.7634    | 0.8164 | 0.7890 | 0.9688   |
| 0.1014        | 6.0   | 2802 | 0.0918          | 0.7700    | 0.8255 | 0.7968 | 0.9694   |
| 0.0982        | 7.0   | 3269 | 0.0910          | 0.7726    | 0.8277 | 0.7992 | 0.9696   |
| 0.0977        | 8.0   | 3736 | 0.0905          | 0.7739    | 0.8282 | 0.8002 | 0.9698   |
| 0.0938        | 9.0   | 4203 | 0.0904          | 0.7736    | 0.8277 | 0.7997 | 0.9699   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3