---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep7_lr4
  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_ep7_lr4

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: 0.1921
- Precision: 0.6693
- Recall: 0.7023
- F1: 0.6854
- Accuracy: 0.9474

## 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-08
- 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 467  | 0.2637          | 0.6599    | 0.6468 | 0.6533 | 0.9429   |
| 0.2761        | 2.0   | 934  | 0.2367          | 0.6611    | 0.6683 | 0.6647 | 0.9440   |
| 0.2405        | 3.0   | 1401 | 0.2181          | 0.6579    | 0.6814 | 0.6694 | 0.9452   |
| 0.2172        | 4.0   | 1868 | 0.2057          | 0.6656    | 0.6928 | 0.6789 | 0.9462   |
| 0.2004        | 5.0   | 2335 | 0.1978          | 0.6698    | 0.6999 | 0.6845 | 0.9470   |
| 0.1935        | 6.0   | 2802 | 0.1934          | 0.6701    | 0.7020 | 0.6857 | 0.9473   |
| 0.1947        | 7.0   | 3269 | 0.1921          | 0.6693    | 0.7023 | 0.6854 | 0.9474   |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2