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# dinov2-base-finetuned-HAM10000

This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the image_folder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1610
- Accuracy: 0.9391

## 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: 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7187        | 0.99  | 70   | 0.5756          | 0.8014   |
| 0.5567        | 2.0   | 141  | 0.5557          | 0.8074   |
| 0.4815        | 2.99  | 211  | 0.3852          | 0.8483   |
| 0.3919        | 4.0   | 282  | 0.3132          | 0.8842   |
| 0.3898        | 4.99  | 352  | 0.2606          | 0.9042   |
| 0.2679        | 6.0   | 423  | 0.2422          | 0.9142   |
| 0.248         | 6.99  | 493  | 0.2498          | 0.9152   |
| 0.1556        | 8.0   | 564  | 0.1844          | 0.9271   |
| 0.1314        | 8.99  | 634  | 0.1610          | 0.9391   |
| 0.0877        | 9.93  | 700  | 0.1704          | 0.9391   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["image_folder"], "metrics": ["accuracy"], "base_model": "facebook/dinov2-base", "model-index": [{"name": "dinov2-base-finetuned-HAM10000", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "image_folder", "type": "image_folder", "config": "default", "split": "train", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9391217564870259, "name": "Accuracy"}]}]}]}
transformers pytorch dinov2 image-classification generated_from_trainer dataset:image_folder base_model:facebook/dinov2-base license:apache-2.0 model-index autotrain_compatible endpoints_compatible has_space region:us