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vogue-fashion-collection-15

Model description

This model classifies an image into a fashion collection. It is trained on the tonyassi/vogue-runway-top15-512px dataset and fine-tuned version of google/vit-base-patch16-224-in21k.

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Dataset description

tonyassi/vogue-runway-top15-512px

  • 15 fashion houses
  • 1679 collections
  • 87,547 images

How to use

from transformers import pipeline

# Initialize image classification pipeline
pipe = pipeline("image-classification", model="tonyassi/vogue-fashion-collection-15")

# Perform classification
result = pipe('image.png')

# Print results
print(result)

Examples

image/jpeg fendi,spring 2023 couture

image/jpeg gucci,spring 2017 ready to wear

image/jpeg prada,fall 2018 ready to wear

Training and evaluation data

It achieves the following results on the evaluation set:

  • Loss: 0.1795
  • Accuracy: 0.9454

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.0
  • Tokenizers 0.15.0
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Safetensors
Model size
87.1M params
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