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---
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
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