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

Accuracy: {'accuracy': 0.8966666666666666}
Loss: 0.8484
Overall Accuracy: 0.8967
Human Accuracy: 0.72
Ld Accuracy: 0.99
Sd Accuracy: 0.98

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
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss	Overall Accuracy	Human Accuracy	Ld Accuracy	Sd Accuracy
1.0272	0.96	18	{'accuracy': 0.9033333333333333}	0.8552	0.9033	0.7835	0.9640	0.9565

Framework versions

Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

sj21867/ai_art_exp2_vit_realism

ai_art_exp2_vit_realism

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sj21867/
ai_art_exp2_vit_realism