cat_vs_dog_classification

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:

• eval_loss: 0.0226
• eval_accuracy: 0.9944
• eval_runtime: 38.0768
• eval_samples_per_second: 61.481
• eval_steps_per_second: 1.943
• epoch: 1.2
• step: 705

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: 3e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3

Framework versions

• Transformers 4.37.2
• Pytorch 2.1.0+cu121
• Datasets 2.17.1
• Tokenizers 0.15.2