beit-base-patch16-224-pt22k-ft22k-finetuned-mnist

This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the mnist 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: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• 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
0.3376	1.0	937	0.0446	0.9855
0.318	2.0	1874	0.0262	0.9916
0.2374	3.0	2811	0.0202	0.9935

Framework versions

• Transformers 4.23.1
• Pytorch 1.12.1+cu113
• Datasets 2.6.1
• Tokenizers 0.13.1