vit-base-patch16-224-MSC-dmae

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

• Loss: 0.6300
• Accuracy: 0.95

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: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.67	1	1.2258	0.5
No log	2.0	3	1.0536	0.7
No log	2.67	4	0.9143	0.75
No log	4.0	6	0.6899	0.9
No log	4.67	7	0.6300	0.95
No log	6.0	9	0.5069	0.9
0.8554	6.67	10	0.4671	0.9
0.8554	8.0	12	0.4312	0.9

Framework versions

• Transformers 4.33.2
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3