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# S2_M1_R3_ViT_42618549

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0001
- 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0171        | 1.0   | 307  | 0.0156          | 0.9952   |
| 0.0097        | 2.0   | 614  | 0.0005          | 1.0      |
| 0.0045        | 3.0   | 921  | 0.0021          | 0.9990   |
| 0.0           | 4.0   | 1229 | 0.0001          | 1.0      |
| 0.0001        | 5.0   | 1535 | 0.0001          | 1.0      |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "google/vit-base-patch16-224", "model-index": [{"name": "S2_M1_R3_ViT_42618549", "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