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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: 1.1957
- Accuracy: 0.495

## 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-06
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4561        | 1.0   | 513  | 1.2817          | 0.4547   |
| 1.2173        | 2.0   | 1026 | 1.2062          | 0.4907   |
| 1.1137        | 3.0   | 1539 | 1.1957          | 0.495    |
| 1.028         | 4.0   | 2052 | 1.2423          | 0.4903   |
| 0.9541        | 5.0   | 2565 | 1.2519          | 0.483    |
| 0.8827        | 6.0   | 3078 | 1.2847          | 0.485    |
| 0.8353        | 7.0   | 3591 | 1.3275          | 0.4793   |
| 0.7752        | 8.0   | 4104 | 1.3532          | 0.4893   |
| 0.7351        | 9.0   | 4617 | 1.3674          | 0.483    |
| 0.7373        | 10.0  | 5130 | 1.3706          | 0.486    |


### 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": ["accuracy"], "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