---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep9_lr2
  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_lr2

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: 0.0899
- Precision: 0.8601
- Recall: 0.8819
- F1: 0.8709
- Accuracy: 0.9780

## 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-06
- 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  | 0.0847          | 0.8136    | 0.8571 | 0.8348 | 0.9722   |
| 0.1137        | 2.0   | 934  | 0.0748          | 0.8367    | 0.8735 | 0.8547 | 0.9755   |
| 0.0747        | 3.0   | 1401 | 0.0747          | 0.8550    | 0.8702 | 0.8625 | 0.9769   |
| 0.0603        | 4.0   | 1868 | 0.0805          | 0.8485    | 0.8765 | 0.8622 | 0.9769   |
| 0.0479        | 5.0   | 2335 | 0.0830          | 0.8607    | 0.8778 | 0.8692 | 0.9776   |
| 0.0433        | 6.0   | 2802 | 0.0853          | 0.8560    | 0.8803 | 0.8680 | 0.9775   |
| 0.0352        | 7.0   | 3269 | 0.0869          | 0.8567    | 0.8852 | 0.8707 | 0.9778   |
| 0.0329        | 8.0   | 3736 | 0.0884          | 0.8583    | 0.8822 | 0.8701 | 0.9779   |
| 0.0305        | 9.0   | 4203 | 0.0899          | 0.8601    | 0.8819 | 0.8709 | 0.9780   |


### Framework versions

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