---
library_name: transformers
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mi-super-modelo
  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. -->

# mi-super-modelo

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3218
- Accuracy: 0.87

## 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: 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7166        | 0.04  | 5    | 0.6899          | 0.5      |
| 0.6804        | 0.08  | 10   | 0.6806          | 0.505    |
| 0.6756        | 0.12  | 15   | 0.6625          | 0.565    |
| 0.6527        | 0.16  | 20   | 0.6229          | 0.67     |
| 0.6245        | 0.2   | 25   | 0.6537          | 0.585    |
| 0.6079        | 0.24  | 30   | 0.5368          | 0.76     |
| 0.5977        | 0.28  | 35   | 0.4603          | 0.83     |
| 0.3683        | 0.32  | 40   | 0.5971          | 0.71     |
| 0.3948        | 0.36  | 45   | 0.4346          | 0.815    |
| 0.4459        | 0.4   | 50   | 0.4177          | 0.81     |
| 0.5583        | 0.44  | 55   | 0.3364          | 0.855    |
| 0.5495        | 0.48  | 60   | 0.3367          | 0.865    |
| 0.1608        | 0.52  | 65   | 0.3992          | 0.825    |
| 0.4232        | 0.56  | 70   | 0.3484          | 0.835    |
| 0.6385        | 0.6   | 75   | 0.3930          | 0.86     |
| 0.2918        | 0.64  | 80   | 0.3389          | 0.86     |
| 0.2137        | 0.68  | 85   | 0.3272          | 0.865    |
| 0.419         | 0.72  | 90   | 0.3188          | 0.885    |
| 0.2032        | 0.76  | 95   | 0.3158          | 0.87     |
| 0.226         | 0.8   | 100  | 0.3204          | 0.87     |
| 0.2525        | 0.84  | 105  | 0.3398          | 0.83     |
| 0.2573        | 0.88  | 110  | 0.3494          | 0.85     |
| 0.3895        | 0.92  | 115  | 0.3368          | 0.835    |
| 0.2776        | 0.96  | 120  | 0.3241          | 0.87     |
| 0.2487        | 1.0   | 125  | 0.3218          | 0.87     |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cpu
- Datasets 2.21.0
- Tokenizers 0.19.1