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Model Details

  • Architecture: ViT-Large with patch size 14
  • Training Data: stanford cars dataset

Training Details

Adam Optimizer with a constant learning rate 1e-5 for 4000 steps training (batch_size=32). Only the vision encoder is fine-tuned.

Evaluation Results

  • pre-trained: 0.7770098447799683
  • fine-tuned: 0.92734694480896
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