---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: BERT_ep5_lr5
  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_ep5_lr5

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: 0.2959
- Precision: 0.6769
- Recall: 0.6346
- F1: 0.6551
- Accuracy: 0.9424

## 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-09
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 467  | 0.3013          | 0.6775    | 0.6310 | 0.6534 | 0.9421   |
| 0.2977        | 2.0   | 934  | 0.2985          | 0.6764    | 0.6326 | 0.6538 | 0.9423   |
| 0.2958        | 3.0   | 1401 | 0.2967          | 0.6774    | 0.6343 | 0.6551 | 0.9423   |
| 0.2906        | 4.0   | 1868 | 0.2960          | 0.6769    | 0.6346 | 0.6551 | 0.9423   |
| 0.2833        | 5.0   | 2335 | 0.2959          | 0.6769    | 0.6346 | 0.6551 | 0.9424   |


### Framework versions

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