swin-base-finetuned-snacks

This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the snacks dataset. It achieves the following results on the evaluation set:

• Loss: 0.2404
• Accuracy: 0.9455

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
0.0044	1.0	38	0.2981	0.9309
0.0023	2.0	76	0.2287	0.9445
0.0012	3.0	114	0.2404	0.9455

Framework versions

• Transformers 4.19.2
• Pytorch 1.11.0+cu113
• Datasets 2.2.2
• Tokenizers 0.12.1