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# dino_finetuned_giant_10_layers_thawed

This model is a fine-tuned version of [facebook/dinov2-giant](https://huggingface.co/facebook/dinov2-giant) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0387
- Accuracy: 0.7361

## 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: 54
- eval_batch_size: 54
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 216
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 3.3778        | 0.3145 | 25   | 2.5161          | 0.3373   |
| 2.0106        | 0.6289 | 50   | 1.8874          | 0.4838   |
| 1.9           | 0.9434 | 75   | 1.6407          | 0.5441   |
| 1.2966        | 1.2579 | 100  | 1.4907          | 0.5930   |
| 1.3413        | 1.5723 | 125  | 1.3532          | 0.6358   |
| 1.2871        | 1.8868 | 150  | 1.2731          | 0.6547   |
| 0.7792        | 2.2013 | 175  | 1.1967          | 0.6875   |
| 0.7153        | 2.5157 | 200  | 1.1761          | 0.6966   |
| 0.7544        | 2.8302 | 225  | 1.1136          | 0.7096   |
| 0.465         | 3.1447 | 250  | 1.0962          | 0.7187   |
| 0.414         | 3.4591 | 275  | 1.0997          | 0.7274   |
| 0.4749        | 3.7736 | 300  | 1.0717          | 0.7291   |
| 0.4742        | 4.0881 | 325  | 1.0425          | 0.7323   |
| 0.3448        | 4.4025 | 350  | 1.0402          | 0.7392   |
| 0.3341        | 4.7170 | 375  | 1.0387          | 0.7361   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1

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