Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use halimalm/vogue with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use halimalm/vogue with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="halimalm/vogue") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("halimalm/vogue") model = AutoModelForImageClassification.from_pretrained("halimalm/vogue") - Notebooks
- Google Colab
- Kaggle
vogue
This model is a fine-tuned version of google/vit-base-patch16-224 on the vogue-designer-looks dataset. It achieves the following results on the evaluation set:
- Loss: 0.7083
- Accuracy: 0.8655
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 86 | 1.2303 | 0.6 |
| 1.491 | 2.0 | 172 | 0.9322 | 0.7706 |
| 0.9886 | 3.0 | 258 | 0.7960 | 0.8235 |
| 0.7985 | 4.0 | 344 | 0.7546 | 0.8471 |
| 0.6993 | 5.0 | 430 | 0.7032 | 0.8765 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0
- Datasets 3.4.1
- Tokenizers 0.21.1
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Model tree for halimalm/vogue
Base model
google/vit-base-patch16-224Space using halimalm/vogue 1
Evaluation results
- Accuracy on vogue-designer-looksself-reported0.865