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

Loss: 0.0614
Accuracy: 0.5

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: 256
eval_batch_size: 256
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5616	1.0	1	0.5417	0.5
0.5578	2.0	2	0.3600	0.5
0.3708	3.0	3	0.2513	0.5
0.2601	4.0	4	0.1906	0.5
0.1806	5.0	5	0.1600	0.5
0.1246	6.0	6	0.1007	0.5
0.1019	7.0	7	0.0846	0.5
0.0729	8.0	8	0.0743	0.5
0.0597	9.0	9	0.0547	0.5
0.0453	10.0	10	0.0614	0.5

Framework versions

Transformers 4.52.3
Pytorch 2.7.0+cu126
Datasets 3.6.0
Tokenizers 0.21.1

Jedrzej-Smok/2025-07-13_16-11-21

2025-07-13_16-11-21

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Jedrzej-Smok/
2025-07-13_16-11-21