Instructions to use touchtech/fashion-images-perspectives with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use touchtech/fashion-images-perspectives with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="touchtech/fashion-images-perspectives") 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("touchtech/fashion-images-perspectives") model = AutoModelForImageClassification.from_pretrained("touchtech/fashion-images-perspectives", device_map="auto") - Notebooks
- Google Colab
- Kaggle
fashion-images-perspectives
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the touchtech/fashion-images-perspectives dataset. It achieves the following results on the evaluation set:
- Loss: 0.2280
- Accuracy: 0.9269
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5677 | 1.0 | 3042 | 0.3996 | 0.8838 |
| 0.4259 | 2.0 | 6084 | 0.3984 | 0.8747 |
| 0.3448 | 3.0 | 9126 | 0.2591 | 0.9190 |
| 0.3094 | 4.0 | 12168 | 0.2280 | 0.9269 |
| 0.2449 | 5.0 | 15210 | 0.2583 | 0.9229 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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Model tree for touchtech/fashion-images-perspectives
Base model
google/vit-base-patch16-224-in21kEvaluation results
- Accuracy on touchtech/fashion-images-perspectivesself-reported0.927