---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep8_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_ep8_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: 0.1048
- Precision: 0.7641
- Recall: 0.8235
- F1: 0.7927
- Accuracy: 0.9666

## 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 467  | 0.1361          | 0.6936    | 0.7475 | 0.7195 | 0.9568   |
| 0.1814        | 2.0   | 934  | 0.1187          | 0.7168    | 0.7849 | 0.7493 | 0.9613   |
| 0.1202        | 3.0   | 1401 | 0.1118          | 0.7361    | 0.7990 | 0.7662 | 0.9635   |
| 0.1109        | 4.0   | 1868 | 0.1088          | 0.7508    | 0.8072 | 0.7780 | 0.9650   |
| 0.1006        | 5.0   | 2335 | 0.1069          | 0.7570    | 0.8158 | 0.7853 | 0.9657   |
| 0.0987        | 6.0   | 2802 | 0.1056          | 0.7604    | 0.8191 | 0.7887 | 0.9662   |
| 0.0969        | 7.0   | 3269 | 0.1050          | 0.7651    | 0.8224 | 0.7927 | 0.9665   |
| 0.0993        | 8.0   | 3736 | 0.1048          | 0.7641    | 0.8235 | 0.7927 | 0.9666   |


### Framework versions

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