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# dino-vits16-finetuned-BUI

This model is a fine-tuned version of [facebook/dino-vits16](https://huggingface.co/facebook/dino-vits16) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2273
- Accuracy: 0.6667

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.8   | 2    | 0.7731          | 0.6032   |
| 0.496         | 2.0   | 5    | 0.8259          | 0.6190   |
| 0.496         | 2.8   | 7    | 0.8272          | 0.4286   |
| 0.5238        | 4.0   | 10   | 1.3584          | 0.3810   |
| 0.5238        | 4.8   | 12   | 1.3436          | 0.6508   |
| 0.7243        | 6.0   | 15   | 1.3677          | 0.3492   |
| 0.7243        | 6.8   | 17   | 0.9869          | 0.3651   |
| 0.986         | 8.0   | 20   | 0.6984          | 0.6190   |
| 0.986         | 8.8   | 22   | 0.9421          | 0.3968   |
| 0.6498        | 10.0  | 25   | 1.0109          | 0.6508   |
| 0.6498        | 10.8  | 27   | 0.7512          | 0.5238   |
| 0.5898        | 12.0  | 30   | 0.7748          | 0.6508   |
| 0.5898        | 12.8  | 32   | 0.7725          | 0.6190   |
| 0.5113        | 14.0  | 35   | 0.8037          | 0.5873   |
| 0.5113        | 14.8  | 37   | 0.8376          | 0.6190   |
| 0.4379        | 16.0  | 40   | 1.1071          | 0.6508   |
| 0.4379        | 16.8  | 42   | 1.0065          | 0.5397   |
| 0.4803        | 18.0  | 45   | 1.3034          | 0.6667   |
| 0.4803        | 18.8  | 47   | 1.0748          | 0.6349   |
| 0.6217        | 20.0  | 50   | 1.0113          | 0.4603   |
| 0.6217        | 20.8  | 52   | 1.2488          | 0.6508   |
| 0.3975        | 22.0  | 55   | 1.0682          | 0.5556   |
| 0.3975        | 22.8  | 57   | 1.5174          | 0.6349   |
| 0.3629        | 24.0  | 60   | 1.0892          | 0.4921   |
| 0.3629        | 24.8  | 62   | 1.0608          | 0.5556   |
| 0.3678        | 26.0  | 65   | 1.4989          | 0.6508   |
| 0.3678        | 26.8  | 67   | 1.0048          | 0.5714   |
| 0.362         | 28.0  | 70   | 0.9922          | 0.6032   |
| 0.362         | 28.8  | 72   | 1.0652          | 0.6190   |
| 0.2969        | 30.0  | 75   | 1.0573          | 0.5397   |
| 0.2969        | 30.8  | 77   | 1.1591          | 0.6190   |
| 0.288         | 32.0  | 80   | 1.1467          | 0.6349   |
| 0.288         | 32.8  | 82   | 1.1856          | 0.5556   |
| 0.2285        | 34.0  | 85   | 1.1599          | 0.6190   |
| 0.2285        | 34.8  | 87   | 1.2128          | 0.6190   |
| 0.239         | 36.0  | 90   | 1.1406          | 0.6032   |
| 0.239         | 36.8  | 92   | 1.1442          | 0.6349   |
| 0.2024        | 38.0  | 95   | 1.1724          | 0.6508   |
| 0.2024        | 38.8  | 97   | 1.2025          | 0.6667   |
| 0.1864        | 40.0  | 100  | 1.2273          | 0.6667   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.6.0+cu124
- Datasets 3.3.1
- Tokenizers 0.19.1

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