---
tags:
- generated_from_trainer
base_model: dccuchile/distilbert-base-spanish-uncased
metrics:
- accuracy
model-index:
- name: Prototipo_3_EMI
  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. -->

# Prototipo_3_EMI

This model is a fine-tuned version of [dccuchile/distilbert-base-spanish-uncased](https://huggingface.co./dccuchile/distilbert-base-spanish-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2540
- Accuracy: 0.5423

## 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: 3e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.2186        | 0.1778 | 200  | 1.1556          | 0.4803   |
| 1.1345        | 0.3556 | 400  | 1.0663          | 0.525    |
| 1.102         | 0.5333 | 600  | 1.0479          | 0.5293   |
| 1.1325        | 0.7111 | 800  | 1.0483          | 0.5353   |
| 1.1211        | 0.8889 | 1000 | 1.0337          | 0.521    |
| 0.9736        | 1.0667 | 1200 | 1.0006          | 0.5503   |
| 0.9428        | 1.2444 | 1400 | 1.0214          | 0.5523   |
| 0.9095        | 1.4222 | 1600 | 1.0174          | 0.555    |
| 0.9806        | 1.6    | 1800 | 1.0155          | 0.5527   |
| 0.969         | 1.7778 | 2000 | 1.0043          | 0.5547   |
| 0.9112        | 1.9556 | 2200 | 1.0050          | 0.5537   |
| 0.7557        | 2.1333 | 2400 | 1.0496          | 0.5607   |
| 0.8212        | 2.3111 | 2600 | 1.0494          | 0.5597   |
| 0.7695        | 2.4889 | 2800 | 1.0510          | 0.5687   |
| 0.7648        | 2.6667 | 3000 | 1.0513          | 0.5603   |
| 0.8232        | 2.8444 | 3200 | 1.0316          | 0.563    |
| 0.6288        | 3.0222 | 3400 | 1.0883          | 0.5503   |
| 0.6736        | 3.2    | 3600 | 1.1232          | 0.548    |
| 0.682         | 3.3778 | 3800 | 1.1695          | 0.543    |
| 0.6682        | 3.5556 | 4000 | 1.1608          | 0.5427   |
| 0.6516        | 3.7333 | 4200 | 1.1636          | 0.545    |
| 0.6731        | 3.9111 | 4400 | 1.1694          | 0.5403   |
| 0.5388        | 4.0889 | 4600 | 1.2120          | 0.544    |
| 0.5663        | 4.2667 | 4800 | 1.2278          | 0.544    |
| 0.5579        | 4.4444 | 5000 | 1.2439          | 0.538    |
| 0.5216        | 4.6222 | 5200 | 1.2507          | 0.5427   |
| 0.4634        | 4.8    | 5400 | 1.2531          | 0.5393   |
| 0.5359        | 4.9778 | 5600 | 1.2540          | 0.5423   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1