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# vit-base-v1-eval-epoch-maxgrad-decay-cosine

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2420
- Accuracy: 0.7032

## Model description

Detects the 14 highest mountains in the world

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.0001        | 0.9903  | 51   | 1.0182          | 0.7898   |
| 0.0027        | 2.0     | 103  | 1.4837          | 0.6688   |
| 0.0076        | 2.9903  | 154  | 1.2528          | 0.7420   |
| 0.0001        | 4.0     | 206  | 1.2986          | 0.7325   |
| 0.0007        | 4.9903  | 257  | 1.2049          | 0.7261   |
| 0.0001        | 6.0     | 309  | 1.1404          | 0.7707   |
| 0.0           | 6.9903  | 360  | 1.1531          | 0.7675   |
| 0.0           | 8.0     | 412  | 1.1605          | 0.7643   |
| 0.0           | 8.9903  | 463  | 1.1647          | 0.7643   |
| 0.0           | 10.0    | 515  | 1.1668          | 0.7675   |
| 0.0           | 10.9903 | 566  | 1.1690          | 0.7707   |
| 0.0           | 12.0    | 618  | 1.1702          | 0.7739   |
| 0.0           | 12.9903 | 669  | 1.1707          | 0.7739   |
| 0.0           | 14.0    | 721  | 1.1711          | 0.7739   |
| 0.0           | 14.8544 | 765  | 1.1710          | 0.7739   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3

annapurna broad peak manaslu mount everest nanga parbat shishapangma cho oyu dhaulagiri gasherbrum i gasherbrum ii k2 kangchenjunga lhotse makalu