Edit model card

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
Downloads last month
13
Safetensors
Model size
303M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for tanganke/clip-vit-large-patch14_svhn

Finetuned
(29)
this model

Dataset used to train tanganke/clip-vit-large-patch14_svhn

Collection including tanganke/clip-vit-large-patch14_svhn