vit-base-patch16-224-in21k-laneclassifierasphaltconcrete-detectorVITmain50epochs

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

• Loss: 0.0004
• Accuracy: {'accuracy': 1.0}
• F1: {'f1': 1.0}
• Precision: {'precision': 1.0}
• Recall: {'recall': 1.0}

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: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.0576	0.9933	111	0.0139	{'accuracy': 0.9977628635346756}	{'f1': 0.9966709613995368}	{'precision': 0.9985795454545454}	{'recall': 0.9947916666666667}
0.0365	1.9955	223	0.0012	{'accuracy': 1.0}	{'f1': 1.0}	{'precision': 1.0}	{'recall': 1.0}
0.0009	2.9978	335	0.0008	{'accuracy': 1.0}	{'f1': 1.0}	{'precision': 1.0}	{'recall': 1.0}
0.0007	4.0	447	0.0007	{'accuracy': 1.0}	{'f1': 1.0}	{'precision': 1.0}	{'recall': 1.0}
0.0006	4.9933	558	0.0005	{'accuracy': 1.0}	{'f1': 1.0}	{'precision': 1.0}	{'recall': 1.0}
0.0005	5.9955	670	0.0005	{'accuracy': 1.0}	{'f1': 1.0}	{'precision': 1.0}	{'recall': 1.0}
0.0005	6.9978	782	0.0004	{'accuracy': 1.0}	{'f1': 1.0}	{'precision': 1.0}	{'recall': 1.0}
0.0005	7.9463	888	0.0004	{'accuracy': 1.0}	{'f1': 1.0}	{'precision': 1.0}	{'recall': 1.0}

Framework versions

• Transformers 4.43.3
• Pytorch 2.3.1
• Datasets 2.20.0
• Tokenizers 0.19.1