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: 0.3985
Accuracy: 1.0

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
0.7264	1.0	1	0.7131	0.5
0.7239	2.0	2	0.6431	0.5
0.6495	3.0	3	0.5960	0.5833
0.5979	4.0	4	0.5529	0.8333
0.5506	5.0	5	0.5156	1.0
0.5064	6.0	6	0.4762	1.0
0.4715	7.0	7	0.4439	1.0
0.4309	8.0	8	0.4305	1.0
0.4172	9.0	9	0.4192	1.0
0.3853	10.0	10	0.3985	1.0

Framework versions

Transformers 4.52.3
Pytorch 2.7.0+cu126
Datasets 3.6.0
Tokenizers 0.21.1

Jedrzej-Smok/2025-05-30_11-48-34

2025-05-30_11-48-34

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Jedrzej-Smok/
2025-05-30_11-48-34