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# app_prova_1

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: 0.1379
- Accuracy: 0.9267

## 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: 3e-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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3233        | 0.8   | 300  | 1.2570          | 0.46     |
| 1.3345        | 1.6   | 600  | 1.1174          | 0.5083   |
| 0.8058        | 2.4   | 900  | 0.8762          | 0.635    |
| 0.7172        | 3.2   | 1200 | 0.6472          | 0.7617   |
| 0.7787        | 4.0   | 1500 | 0.4798          | 0.8267   |
| 0.4868        | 4.8   | 1800 | 0.3784          | 0.8483   |
| 0.188         | 5.6   | 2100 | 0.2755          | 0.8967   |
| 0.3602        | 6.4   | 2400 | 0.2220          | 0.91     |
| 0.1426        | 7.2   | 2700 | 0.2077          | 0.9117   |
| 0.2024        | 8.0   | 3000 | 0.1465          | 0.935    |
| 0.1914        | 8.8   | 3300 | 0.1438          | 0.93     |
| 0.0593        | 9.6   | 3600 | 0.1379          | 0.9267   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "app_prova_1", "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