vit-base-patch16-224-in21k-finetuned-lora-food101

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.2034
• Accuracy: 0.94

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: 0.005
• train_batch_size: 128
• eval_batch_size: 128
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 512
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	9	0.5701	0.866
2.1862	2.0	18	0.2383	0.936
0.3244	3.0	27	0.2034	0.94
0.1904	4.0	36	0.2018	0.932
0.1786	5.0	45	0.1818	0.94

Framework versions

• PEFT 0.10.0
• Transformers 4.39.0
• Pytorch 2.2.1
• Datasets 2.18.0
• Tokenizers 0.15.2