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 | |