---
license: mit
base_model: neuralmind/bert-large-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-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0987
- Accuracy: 0.3229

## 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: 5e-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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8592        | 1.0   | 1200  | 0.8029          | 0.6279   |
| 0.9076        | 2.0   | 2400  | 1.1314          | 0.3229   |
| 1.1221        | 3.0   | 3600  | 1.1170          | 0.3229   |
| 1.1211        | 4.0   | 4800  | 1.1020          | 0.3362   |
| 1.115         | 5.0   | 6000  | 1.1015          | 0.3408   |
| 1.12          | 6.0   | 7200  | 1.0989          | 0.3408   |
| 1.1153        | 7.0   | 8400  | 1.0989          | 0.3408   |
| 1.1123        | 8.0   | 9600  | 1.0993          | 0.3408   |
| 1.1125        | 9.0   | 10800 | 1.0987          | 0.3408   |
| 1.1109        | 10.0  | 12000 | 1.0987          | 0.3229   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1