---
library_name: transformers
license: cc-by-4.0
base_model: dccuchile/tulio-chilean-spanish-bert
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Gestionabilidad-v3_batch32
  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. -->

# Gestionabilidad-v3_batch32

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: 0.1858
- Accuracy: 0.9298
- Precision: 0.9300
- Recall: 0.9298
- F1: 0.9296

## 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: 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: 5

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.283         | 0.2289 | 500   | 0.2429          | 0.9044   | 0.9072    | 0.9044 | 0.9048 |
| 0.2275        | 0.4579 | 1000  | 0.2073          | 0.9185   | 0.9185    | 0.9185 | 0.9183 |
| 0.2066        | 0.6868 | 1500  | 0.1900          | 0.9187   | 0.9202    | 0.9187 | 0.9181 |
| 0.1949        | 0.9158 | 2000  | 0.2105          | 0.9194   | 0.9213    | 0.9194 | 0.9187 |
| 0.1657        | 1.1447 | 2500  | 0.1920          | 0.9263   | 0.9270    | 0.9263 | 0.9259 |
| 0.1502        | 1.3736 | 3000  | 0.2021          | 0.9280   | 0.9279    | 0.9280 | 0.9279 |
| 0.1412        | 1.6026 | 3500  | 0.1858          | 0.9298   | 0.9300    | 0.9298 | 0.9296 |
| 0.1477        | 1.8315 | 4000  | 0.1950          | 0.9300   | 0.9304    | 0.9300 | 0.9301 |
| 0.1296        | 2.0604 | 4500  | 0.2188          | 0.9303   | 0.9304    | 0.9303 | 0.9304 |
| 0.1004        | 2.2894 | 5000  | 0.2367          | 0.9304   | 0.9305    | 0.9304 | 0.9305 |
| 0.0958        | 2.5183 | 5500  | 0.2294          | 0.9305   | 0.9305    | 0.9305 | 0.9303 |
| 0.1003        | 2.7473 | 6000  | 0.2394          | 0.9293   | 0.9299    | 0.9293 | 0.9290 |
| 0.1029        | 2.9762 | 6500  | 0.2294          | 0.9321   | 0.9320    | 0.9321 | 0.9320 |
| 0.0696        | 3.2051 | 7000  | 0.2727          | 0.9324   | 0.9324    | 0.9324 | 0.9322 |
| 0.0619        | 3.4341 | 7500  | 0.2672          | 0.9287   | 0.9301    | 0.9287 | 0.9289 |
| 0.0627        | 3.6630 | 8000  | 0.2897          | 0.9326   | 0.9329    | 0.9326 | 0.9327 |
| 0.0639        | 3.8919 | 8500  | 0.2970          | 0.9322   | 0.9322    | 0.9322 | 0.9322 |
| 0.0549        | 4.1209 | 9000  | 0.3230          | 0.9321   | 0.9322    | 0.9321 | 0.9321 |
| 0.0409        | 4.3498 | 9500  | 0.3722          | 0.9313   | 0.9317    | 0.9313 | 0.9314 |
| 0.0388        | 4.5788 | 10000 | 0.3326          | 0.9333   | 0.9335    | 0.9333 | 0.9333 |
| 0.0373        | 4.8077 | 10500 | 0.3565          | 0.9332   | 0.9335    | 0.9332 | 0.9333 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0