food101-vit-dinov3

This model is a fine-tuned version of timm/vit_base_patch16_dinov3.lvd1689m on the ethz/food101 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0491
• Accuracy: 0.9865

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
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 0.1
• num_epochs: 10.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.7454	1.0	237	0.2419	0.9493
0.3067	2.0	474	0.1198	0.9671
0.2526	3.0	711	0.0859	0.9747
0.1810	4.0	948	0.0706	0.9802
0.1365	5.0	1185	0.0621	0.9802
0.1284	6.0	1422	0.0648	0.9814
0.1034	7.0	1659	0.0523	0.9830
0.0815	8.0	1896	0.0566	0.9834
0.0810	9.0	2133	0.0503	0.9861
0.0597	10.0	2370	0.0491	0.9865

Framework versions

• Transformers 5.3.0.dev0
• Pytorch 2.10.0+cu128
• Datasets 4.6.1
• Tokenizers 0.22.2