---
base_model: dccuchile/tulio-chilean-spanish-bert
license: cc-by-4.0
metrics:
- accuracy
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: not-ner-v2
  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. -->

# not-ner-v2

This model is a fine-tuned version of [dccuchile/tulio-chilean-spanish-bert](https://huggingface.co/dccuchile/tulio-chilean-spanish-bert) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0838
- Accuracy: 0.9727
- Precision: 0.9723
- Recall: 0.9727
- F1: 0.9724

## 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-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1679        | 0.1595 | 250  | 0.1431          | 0.9555   | 0.9546    | 0.9555 | 0.9549 |
| 0.1291        | 0.3191 | 500  | 0.1328          | 0.9595   | 0.9583    | 0.9595 | 0.9586 |
| 0.1055        | 0.4786 | 750  | 0.0925          | 0.9653   | 0.9648    | 0.9653 | 0.9650 |
| 0.1044        | 0.6382 | 1000 | 0.1415          | 0.9630   | 0.9619    | 0.9630 | 0.9615 |
| 0.1094        | 0.7977 | 1250 | 0.1030          | 0.9630   | 0.9624    | 0.9630 | 0.9612 |
| 0.0927        | 0.9572 | 1500 | 0.0878          | 0.9710   | 0.9706    | 0.9710 | 0.9707 |
| 0.0836        | 1.1168 | 1750 | 0.1265          | 0.9663   | 0.9666    | 0.9663 | 0.9665 |
| 0.0651        | 1.2763 | 2000 | 0.1025          | 0.9709   | 0.9702    | 0.9709 | 0.9704 |
| 0.0637        | 1.4359 | 2250 | 0.0998          | 0.9676   | 0.9668    | 0.9676 | 0.9667 |
| 0.0713        | 1.5954 | 2500 | 0.0838          | 0.9727   | 0.9723    | 0.9727 | 0.9724 |
| 0.0561        | 1.7549 | 2750 | 0.0905          | 0.9722   | 0.9722    | 0.9722 | 0.9722 |
| 0.058         | 1.9145 | 3000 | 0.1030          | 0.9707   | 0.9701    | 0.9707 | 0.9702 |
| 0.0531        | 2.0740 | 3250 | 0.1066          | 0.9714   | 0.9710    | 0.9714 | 0.9711 |
| 0.0398        | 2.2336 | 3500 | 0.1035          | 0.9722   | 0.9721    | 0.9722 | 0.9721 |
| 0.0444        | 2.3931 | 3750 | 0.1009          | 0.9728   | 0.9725    | 0.9728 | 0.9726 |
| 0.037         | 2.5526 | 4000 | 0.1068          | 0.9725   | 0.9721    | 0.9725 | 0.9722 |
| 0.0261        | 2.7122 | 4250 | 0.1192          | 0.9735   | 0.9731    | 0.9735 | 0.9732 |
| 0.0266        | 2.8717 | 4500 | 0.1191          | 0.9732   | 0.9727    | 0.9732 | 0.9729 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1