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# swaddling-classifier

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the ahaque/swaddling_classifier dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4074
- Accuracy: 1.0

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 1    | 0.5106          | 0.6667   |
| No log        | 2.0   | 2    | 0.4672          | 0.6667   |
| No log        | 3.0   | 3    | 0.4365          | 1.0      |
| No log        | 4.0   | 4    | 0.4169          | 1.0      |
| No log        | 5.0   | 5    | 0.4074          | 1.0      |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1

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