msi-vit-small-pretrain

This model is a fine-tuned version of WinKawaks/vit-small-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 2.4835
• Accuracy: 0.6394

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0897	1.0	781	1.7652	0.6574
0.0539	2.0	1562	2.5512	0.6017
0.0127	3.0	2343	2.4835	0.6394

Framework versions

• Transformers 4.36.0
• Pytorch 2.0.1+cu117
• Datasets 2.15.0
• Tokenizers 0.15.0