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# my_classification

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3033
- Accuracy: 0.7277

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 5.7973        | 1.0   | 175  | 4.2373          | 0.1537   |
| 3.3114        | 2.0   | 350  | 2.8087          | 0.4224   |
| 1.68          | 3.0   | 525  | 1.9823          | 0.5983   |
| 0.7776        | 4.0   | 700  | 1.6113          | 0.6648   |
| 0.3974        | 5.0   | 875  | 1.4166          | 0.6962   |
| 0.1666        | 6.0   | 1050 | 1.3312          | 0.7119   |
| 0.0657        | 7.0   | 1225 | 1.3033          | 0.7277   |
| 0.0315        | 8.0   | 1400 | 1.3021          | 0.7191   |
| 0.0187        | 9.0   | 1575 | 1.2946          | 0.7198   |
| 0.0146        | 10.0  | 1750 | 1.3018          | 0.7191   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224", "model-index": [{"name": "my_classification", "results": []}]}
transformers pytorch vit image-classification generated_from_trainer base_model:google/vit-base-patch16-224 license:apache-2.0 autotrain_compatible endpoints_compatible region:us