vit-base-patch16-224-cifar100 – AI Model by MatanBT | AlphaNeural AI

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MatanBT/
vit-base-patch16-224-cifar100

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image-classification

generated_from_trainer

google/vit-base-patch16-224

endpoints_compatible

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vit-base-patch16-224-cifar100

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

Loss: 0.3001
Accuracy: 0.9267

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: 128
eval_batch_size: 64
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3521	1.2788	500	0.3978	0.8883
0.1523	2.5575	1000	0.3153	0.9119
0.0798	3.8363	1500	0.3076	0.9165
0.0340	5.1151	2000	0.3171	0.9185
0.0096	6.3939	2500	0.3021	0.926
0.0085	7.6726	3000	0.3022	0.9251
0.0045	8.9514	3500	0.3001	0.9267

Framework versions

Transformers 5.3.0
Pytorch 2.6.0+cu124
Datasets 4.8.3
Tokenizers 0.22.2