---
base_model: finiteautomata/beto-sentiment-analysis
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: beto-sentiment-analysis-finetuned-detests
  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. -->

# beto-sentiment-analysis-finetuned-detests

This model is a fine-tuned version of [finiteautomata/beto-sentiment-analysis](https://huggingface.co/finiteautomata/beto-sentiment-analysis) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2413
- Accuracy: 0.8396
- F1-score: 0.7695
- Precision: 0.7724
- Recall: 0.7668
- Auc: 0.7668

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall | Auc    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:|
| 0.3772        | 1.0   | 174  | 0.4358          | 0.8298   | 0.6814   | 0.8246    | 0.6513 | 0.6513 |
| 0.1092        | 2.0   | 348  | 0.4312          | 0.8625   | 0.7925   | 0.8139    | 0.7765 | 0.7765 |
| 0.0955        | 3.0   | 522  | 0.7126          | 0.8412   | 0.7724   | 0.7746    | 0.7704 | 0.7704 |
| 0.0625        | 4.0   | 696  | 0.9681          | 0.8412   | 0.7688   | 0.7757    | 0.7627 | 0.7627 |
| 0.0056        | 5.0   | 870  | 1.1017          | 0.8347   | 0.7567   | 0.7666    | 0.7484 | 0.7484 |
| 0.0018        | 6.0   | 1044 | 1.2244          | 0.8347   | 0.7630   | 0.7651    | 0.7610 | 0.7610 |
| 0.0001        | 7.0   | 1218 | 1.2190          | 0.8412   | 0.7637   | 0.7778    | 0.7526 | 0.7526 |
| 0.0001        | 8.0   | 1392 | 1.2356          | 0.8396   | 0.7645   | 0.7739    | 0.7566 | 0.7566 |
| 0.0001        | 9.0   | 1566 | 1.2332          | 0.8380   | 0.7547   | 0.7746    | 0.7403 | 0.7403 |
| 0.0001        | 10.0  | 1740 | 1.2413          | 0.8396   | 0.7695   | 0.7724    | 0.7668 | 0.7668 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3