---
base_model: finiteautomata/beto-sentiment-analysis
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: beto-sentiment-analysis-finetuned-detests24
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# beto-sentiment-analysis-finetuned-detests24

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: 1.0647
- Accuracy: 0.8609
- F1-score: 0.7906
- Precision: 0.8107
- Recall: 0.7755
- Auc: 0.7755

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:|
| 0.4035        | 1.0   | 153  | 0.3459          | 0.8527   | 0.7540   | 0.8257    | 0.7219 | 0.7219 |
| 0.2217        | 2.0   | 306  | 0.4773          | 0.8183   | 0.7700   | 0.7519    | 0.8088 | 0.8088 |
| 0.0787        | 3.0   | 459  | 0.6757          | 0.8576   | 0.7959   | 0.7982    | 0.7936 | 0.7936 |
| 0.016         | 4.0   | 612  | 0.7801          | 0.8478   | 0.7851   | 0.7830    | 0.7873 | 0.7873 |
| 0.0251        | 5.0   | 765  | 0.9783          | 0.8511   | 0.7994   | 0.7862    | 0.8173 | 0.8173 |
| 0.0159        | 6.0   | 918  | 0.9841          | 0.8576   | 0.7926   | 0.8001    | 0.7860 | 0.7860 |
| 0.0002        | 7.0   | 1071 | 0.9943          | 0.8609   | 0.7906   | 0.8107    | 0.7755 | 0.7755 |
| 0.0001        | 8.0   | 1224 | 1.0252          | 0.8625   | 0.7925   | 0.8139    | 0.7765 | 0.7765 |
| 0.0013        | 9.0   | 1377 | 1.0663          | 0.8511   | 0.7808   | 0.7916    | 0.7716 | 0.7716 |
| 0.0001        | 10.0  | 1530 | 1.0647          | 0.8609   | 0.7906   | 0.8107    | 0.7755 | 0.7755 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1