---
tags:
- generated_from_trainer
base_model: dccuchile/distilbert-base-spanish-uncased
metrics:
- accuracy
model-index:
- name: Prototipo_4_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_4_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: 1.0406
- Accuracy: 0.5567

## 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: 2e-05
- train_batch_size: 50
- eval_batch_size: 50
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.3118        | 0.3704 | 200  | 1.2660          | 0.4457   |
| 1.0828        | 0.7407 | 400  | 1.0757          | 0.5203   |
| 1.0145        | 1.1111 | 600  | 1.0380          | 0.534    |
| 0.9955        | 1.4815 | 800  | 1.0184          | 0.5377   |
| 0.9449        | 1.8519 | 1000 | 0.9944          | 0.5507   |
| 0.9143        | 2.2222 | 1200 | 1.0077          | 0.5533   |
| 0.8609        | 2.5926 | 1400 | 1.0104          | 0.5473   |
| 0.882         | 2.9630 | 1600 | 1.0037          | 0.5507   |
| 0.8049        | 3.3333 | 1800 | 1.0202          | 0.5593   |
| 0.8045        | 3.7037 | 2000 | 1.0234          | 0.5503   |
| 0.78          | 4.0741 | 2200 | 1.0280          | 0.5593   |
| 0.7651        | 4.4444 | 2400 | 1.0411          | 0.5583   |
| 0.7301        | 4.8148 | 2600 | 1.0406          | 0.5567   |


### Framework versions

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