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: 0.2123
Accuracy: 0.9455

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: 16
eval_batch_size: 16
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
num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.6072	1.0	28	1.3183	0.6
0.9996	2.0	56	0.7635	0.8909
0.5012	3.0	84	0.4795	0.9273
0.2416	4.0	112	0.3269	0.9455
0.1426	5.0	140	0.2570	0.9818
0.1051	6.0	168	0.2330	0.9818
0.0862	7.0	196	0.2197	0.9636
0.0738	8.0	224	0.2123	0.9455

Framework versions

Transformers 4.57.1
Pytorch 2.8.0
Datasets 4.4.1
Tokenizers 0.22.1

singlaashish/vit-finetuned-chessman2

vit-finetuned-chessman2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

singlaashish/
vit-finetuned-chessman2