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# vit-base-patch16-224-in21k-finetuned-SMD-shuffled-transformed

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0602
- 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.524         | 1.0   | 40   | 1.5157          | 0.5915   |
| 0.8485        | 2.0   | 80   | 0.7746          | 0.8592   |
| 0.3255        | 3.0   | 120  | 0.3268          | 0.9577   |
| 0.1379        | 4.0   | 160  | 0.1649          | 0.9859   |
| 0.0948        | 5.0   | 200  | 0.1110          | 1.0      |
| 0.0749        | 6.0   | 240  | 0.0897          | 1.0      |
| 0.0654        | 7.0   | 280  | 0.0761          | 1.0      |
| 0.0536        | 8.0   | 320  | 0.0602          | 1.0      |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0

划伤 印字偏移 污染 污染手绘 磨光 非反光大污染