---
base_model: pysentimiento/robertuito-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
model-index:
- name: robertuito-finetuned-class
  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. -->

# robertuito-finetuned-class

This model is a fine-tuned version of [pysentimiento/robertuito-base-uncased](https://huggingface.co/pysentimiento/robertuito-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6600
- F1: 0.7394
- Recall: 0.7425
- Accuracy: 0.7564

## 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: 2.989919952299843e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 15
- distributed_type: multi-GPU
- 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 | F1     | Recall | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|
| No log        | 1.0   | 87   | 0.7059          | 0.6831 | 0.6717 | 0.7315   |
| No log        | 2.0   | 174  | 0.6123          | 0.7420 | 0.7442 | 0.7629   |
| No log        | 3.0   | 261  | 0.6600          | 0.7394 | 0.7425 | 0.7564   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0