UL_interior_classification

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

• Loss: 1.2517
• Accuracy: 0.5876

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: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.7547	0.9811	13	2.3422	0.3285
1.7119	1.9623	26	1.8850	0.4964
1.249	2.9434	39	1.5653	0.5292
0.8838	4.0	53	1.3675	0.5693
0.8896	4.9811	66	1.2907	0.5803
0.7262	5.9623	79	1.2625	0.5803
0.6817	6.8679	91	1.2517	0.5876

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1