---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: google-play-sentiment-analysis
  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. -->

# google-play-sentiment-analysis

This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3877
- Accuracy: 0.5328

## 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: 3e-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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.2365        | 1.0   | 1275  | 1.1915          | 0.5056   |
| 1.0717        | 2.0   | 2550  | 1.2020          | 0.5133   |
| 0.8201        | 3.0   | 3825  | 1.3425          | 0.5017   |
| 0.5824        | 4.0   | 5100  | 1.5890          | 0.5294   |
| 0.4379        | 5.0   | 6375  | 1.9669          | 0.5128   |
| 0.3143        | 6.0   | 7650  | 2.4700          | 0.5361   |
| 0.2556        | 7.0   | 8925  | 2.9751          | 0.5211   |
| 0.1924        | 8.0   | 10200 | 3.2435          | 0.5211   |
| 0.1494        | 9.0   | 11475 | 3.3190          | 0.5278   |
| 0.1293        | 10.0  | 12750 | 3.3877          | 0.5328   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0