---
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: 3.5035
- Accuracy: 0.5107

## 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.18          | 1.0   | 1125  | 1.2287          | 0.4957   |
| 0.9342        | 2.0   | 2250  | 1.3080          | 0.5223   |
| 0.6743        | 3.0   | 3375  | 1.4724          | 0.5147   |
| 0.493         | 4.0   | 4500  | 1.8871          | 0.5113   |
| 0.3701        | 5.0   | 5625  | 2.4745          | 0.5183   |
| 0.275         | 6.0   | 6750  | 2.7261          | 0.5183   |
| 0.2115        | 7.0   | 7875  | 3.1310          | 0.5183   |
| 0.1521        | 8.0   | 9000  | 3.3735          | 0.5077   |
| 0.1442        | 9.0   | 10125 | 3.4553          | 0.5137   |
| 0.1189        | 10.0  | 11250 | 3.5035          | 0.5107   |


### Framework versions

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