---
base_model: mrm8488/electricidad-base-discriminator
tags:
- classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: clasificador-muchocine
  results: []
---

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# clasificador-muchocine

This model is a fine-tuned version of [mrm8488/electricidad-base-discriminator](https://huggingface.co/mrm8488/electricidad-base-discriminator) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3974
- Accuracy: 0.4310

## Model description

This model enables the classification of user movie reviews written in Spanish into 5 categories corresponding to the number of stars provided in the review (label_0 corresponds to 1 star and label_4 to 5 stars)

## Intended uses & limitations

Please, note that this model has been trained with a Spanish dataset and may therefore not be suitable for classifying texts written in other languages. Also, note that the achieved accuracy in the evaluation tests is around 43%.

## Training and evaluation data

The dataset employed was randomly divided for the following purposes: 80% training data - 20% test data.

## Training procedure

The model has been trained following a 3-epoch cycle.

### 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: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 388  | 1.3304          | 0.3948   |
| 1.4184        | 2.0   | 776  | 1.3010          | 0.4297   |
| 0.9847        | 3.0   | 1164 | 1.3974          | 0.4310   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1