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---
base_model:
- openai/clip-vit-large-patch14
datasets:
- svhn
metrics:
- accuracy
---
# Model Card
## Model Details
- Architecture: ViT-Large with patch size 14
- Training Data: SVHN 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: 0.5881173014640808
- fine-tuned: 0.9790836572647095
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