---
license: cc-by-4.0
base_model: NazaGara/NER-fine-tuned-BETO
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: NER-finetuning-BETO
  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. -->

# NER-finetuning-BETO

Este es el modelo de BETO para NER [NazaGara/NER-fine-tuned-BETO](https://huggingface.co/NazaGara/NER-fine-tuned-BETO) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2140
- Precision: 0.8424
- Recall: 0.8545
- F1: 0.8484
- Accuracy: 0.9691

## 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: 2e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0482        | 1.0   | 1041 | 0.1522          | 0.8309    | 0.8481 | 0.8394 | 0.9687   |
| 0.0302        | 2.0   | 2082 | 0.1661          | 0.8293    | 0.8527 | 0.8408 | 0.9696   |
| 0.0164        | 3.0   | 3123 | 0.1691          | 0.8403    | 0.8536 | 0.8469 | 0.9696   |
| 0.011         | 4.0   | 4164 | 0.2026          | 0.8427    | 0.8516 | 0.8471 | 0.9693   |
| 0.0073        | 5.0   | 5205 | 0.2140          | 0.8424    | 0.8545 | 0.8484 | 0.9691   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1