---
base_model:
- openai/clip-vit-large-patch14
datasets:
- tanganke/resisc45
metrics:
- accuracy
---

# Model Card

## Model Details

- Architecture: ViT-Large with patch size 14
- Training Data: RESISC45 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: 0.7100892066955566
- fine-tuned: 0.9738245606422424