Instructions to use RushnaFathima/dinov2-base-rawdata-finetuned-SkinDisease with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RushnaFathima/dinov2-base-rawdata-finetuned-SkinDisease with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="RushnaFathima/dinov2-base-rawdata-finetuned-SkinDisease") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("RushnaFathima/dinov2-base-rawdata-finetuned-SkinDisease") model = AutoModelForImageClassification.from_pretrained("RushnaFathima/dinov2-base-rawdata-finetuned-SkinDisease", device_map="auto") - Notebooks
- Google Colab
- Kaggle
dinov2-base-rawdata-finetuned-SkinDisease
This model is a fine-tuned version of facebook/dinov2-base on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4141
- Accuracy: 0.8724
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 3.1724 | 1.0 | 14 | 1.9875 | 0.3776 |
| 1.9233 | 2.0 | 28 | 1.2796 | 0.5995 |
| 0.9913 | 3.0 | 42 | 0.8862 | 0.7168 |
| 0.7552 | 4.0 | 56 | 0.7308 | 0.7577 |
| 0.5114 | 5.0 | 70 | 0.5880 | 0.8163 |
| 0.4078 | 6.0 | 84 | 0.6009 | 0.8265 |
| 0.3522 | 7.0 | 98 | 0.5508 | 0.8393 |
| 0.3091 | 8.0 | 112 | 0.4744 | 0.8520 |
| 0.2232 | 9.0 | 126 | 0.4141 | 0.8724 |
| 0.1817 | 10.0 | 140 | 0.4219 | 0.8699 |
Framework versions
- Transformers 5.10.2
- Pytorch 2.10.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2
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Model tree for RushnaFathima/dinov2-base-rawdata-finetuned-SkinDisease
Base model
facebook/dinov2-baseEvaluation results
- Accuracy on imagefolderself-reported0.872