---
base_model: dccuchile/distilbert-base-spanish-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: distilbert-base-spanish-uncased-finetuned-text-intelligence
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilbert-base-spanish-uncased-finetuned-text-intelligence

This model is a fine-tuned version of [dccuchile/distilbert-base-spanish-uncased](https://huggingface.co/dccuchile/distilbert-base-spanish-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6945
- Accuracy: 0.8834
- F1: 0.8827

## 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: 1e-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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 1.0148        | 1.0   | 235  | 0.7880          | 0.7138   | 0.6551 |
| 0.6349        | 2.0   | 470  | 0.5415          | 0.8516   | 0.8500 |
| 0.4709        | 3.0   | 705  | 0.4505          | 0.8587   | 0.8613 |
| 0.3727        | 4.0   | 940  | 0.4156          | 0.8905   | 0.8900 |
| 0.3163        | 5.0   | 1175 | 0.4262          | 0.8905   | 0.8910 |
| 0.2695        | 6.0   | 1410 | 0.5090          | 0.8869   | 0.8874 |
| 0.2332        | 7.0   | 1645 | 0.5014          | 0.8869   | 0.8865 |
| 0.1811        | 8.0   | 1880 | 0.5735          | 0.8834   | 0.8827 |
| 0.1542        | 9.0   | 2115 | 0.5626          | 0.8940   | 0.8932 |
| 0.1192        | 10.0  | 2350 | 0.5680          | 0.8905   | 0.8900 |
| 0.124         | 11.0  | 2585 | 0.6291          | 0.8869   | 0.8857 |
| 0.0988        | 12.0  | 2820 | 0.6424          | 0.8834   | 0.8835 |
| 0.0933        | 13.0  | 3055 | 0.7085          | 0.8693   | 0.8668 |
| 0.0813        | 14.0  | 3290 | 0.6560          | 0.8905   | 0.8893 |
| 0.0599        | 15.0  | 3525 | 0.7175          | 0.8799   | 0.8793 |
| 0.0632        | 16.0  | 3760 | 0.6862          | 0.8799   | 0.8786 |
| 0.0489        | 17.0  | 3995 | 0.7064          | 0.8869   | 0.8858 |
| 0.0449        | 18.0  | 4230 | 0.7046          | 0.8834   | 0.8830 |
| 0.039         | 19.0  | 4465 | 0.6997          | 0.8799   | 0.8790 |
| 0.0388        | 20.0  | 4700 | 0.6945          | 0.8834   | 0.8827 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.1.0
- Datasets 2.19.0
- Tokenizers 0.19.1