---
datasets:
- yelp_review_full
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: mi-super-modelo
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: yelp_review_full
      type: yelp_review_full
      config: yelp_review_full
      split: test
      args: yelp_review_full
    metrics:
    - type: accuracy
      value: 0.225
      name: Accuracy
---

<!-- 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 [bert-base-cased](https://huggingface.co/bert-base-cased) on the yelp_review_full dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6404
- Accuracy: 0.225

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7058        | 0.5   | 5    | 1.7046          | 0.225    |
| 1.6208        | 1.0   | 10   | 1.6404          | 0.225    |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3