---
library_name: transformers
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-fine-tuned-BETO-finetuned-ner
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# NER-fine-tuned-BETO-finetuned-ner

This model is a fine-tuned version of [NazaGara/NER-fine-tuned-BETO](https://huggingface.co/NazaGara/NER-fine-tuned-BETO) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2509
- Precision: 0.7185
- Recall: 0.6715
- F1: 0.6942
- Accuracy: 0.8935

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.8944        | 1.0   | 777  | 0.3823          | 0.6589    | 0.5547 | 0.6023 | 0.8467   |
| 0.4465        | 2.0   | 1554 | 0.2852          | 0.6810    | 0.6399 | 0.6598 | 0.8775   |
| 0.3745        | 3.0   | 2331 | 0.2509          | 0.7185    | 0.6715 | 0.6942 | 0.8935   |


### Framework versions

- Transformers 4.52.2
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1