Edit model card

vit-base-cats-vs-dogs

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the cats_vs_dogs dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0202
  • Accuracy: 0.9935

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 1337
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.064 1.0 311 0.0483 0.9849
0.0622 2.0 622 0.0275 0.9903
0.0366 3.0 933 0.0262 0.9917
0.0294 4.0 1244 0.0219 0.9932
0.0161 5.0 1555 0.0202 0.9935

Framework versions

  • Transformers 4.8.1
  • Pytorch 1.9.0+cu102
  • Datasets 1.11.1.dev0
  • Tokenizers 0.10.3
Downloads last month
8
Hosted inference API
Drag image file here or click to browse from your device
This model can be loaded on the Inference API on-demand.

Dataset used to train nateraw/vit-base-cats-vs-dogs

Evaluation results