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# app_prova

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1297
- Accuracy: 0.69

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1788        | 0.4   | 50   | 1.0801          | 0.635    |
| 0.9743        | 0.8   | 100  | 1.1113          | 0.686    |
| 0.8909        | 1.2   | 150  | 1.0996          | 0.698    |
| 0.7816        | 1.6   | 200  | 1.0869          | 0.695    |
| 0.6782        | 2.0   | 250  | 1.0705          | 0.685    |
| 0.693         | 2.4   | 300  | 1.1389          | 0.678    |
| 0.4672        | 2.8   | 350  | 1.1297          | 0.69     |


### Framework versions

- Transformers 4.36.1
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "app_prova", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us