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# 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: 3.6324
- F1: 0.5277

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.7056        | 1.0   | 1125  | 1.5127          | 0.4766 |
| 0.7472        | 2.0   | 2250  | 1.4296          | 0.5148 |
| 0.5266        | 3.0   | 3375  | 1.6938          | 0.5262 |
| 0.3887        | 4.0   | 4500  | 2.1185          | 0.5176 |
| 0.3078        | 5.0   | 5625  | 2.5383          | 0.5229 |
| 0.2286        | 6.0   | 6750  | 3.0566          | 0.5107 |
| 0.1718        | 7.0   | 7875  | 3.3369          | 0.5248 |
| 0.1324        | 8.0   | 9000  | 3.4615          | 0.5255 |
| 0.1372        | 9.0   | 10125 | 3.5526          | 0.5221 |
| 0.1095        | 10.0  | 11250 | 3.6324          | 0.5277 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "neuralmind/bert-base-portuguese-cased", "model-index": [{"name": "google-play-sentiment-analysis", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:neuralmind/bert-base-portuguese-cased license:mit autotrain_compatible endpoints_compatible region:us