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: 0.2481
• Accuracy: 0.9279

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: 168
• eval_batch_size: 168
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 672
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8568	0.9933	74	0.3500	0.8978
0.7674	2.0	149	0.3065	0.9089
0.724	2.9933	223	0.2805	0.9164
0.6316	4.0	298	0.2725	0.9197
0.6462	4.9933	372	0.2659	0.9195
0.5809	6.0	447	0.2623	0.9223
0.5212	6.9933	521	0.2624	0.9217
0.5561	8.0	596	0.2523	0.9259
0.5061	8.9933	670	0.2502	0.9268
0.4955	9.9329	740	0.2481	0.9279

Framework versions

• PEFT 0.13.0
• Transformers 4.45.1
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.20.0