beit-base

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the cats_vs_dogs dataset. It achieves the following results on the evaluation set:

• Loss: 0.0116
• Accuracy: 0.9977

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• 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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0303	1.0	585	0.0186	0.9942
0.0374	2.0	1170	0.0150	0.9955
0.0559	3.0	1755	0.0116	0.9977

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.10.1
• Tokenizers 0.13.2