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

Loss: 0.6993
Accuracy: 0.8333

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: 2e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.799	0.8333	10	1.9456	0.1667
1.2417	1.6667	20	1.7680	0.3333
1.1543	2.5	30	1.5470	0.5
0.8829	3.3333	40	1.4117	0.5
0.8725	4.1667	50	1.2967	0.5
0.5514	5.0	60	1.1901	0.5
0.4565	5.8333	70	1.1867	0.5
0.3663	6.6667	80	1.0417	0.5
0.3448	7.5	90	0.8938	0.6667
0.2525	8.3333	100	0.8804	0.75
0.1729	9.1667	110	0.9067	0.6667
0.1848	10.0	120	0.8441	0.6667
0.1847	10.8333	130	0.7352	0.8333
0.0916	11.6667	140	0.7336	0.8333
0.1771	12.5	150	0.7012	0.8333
0.105	13.3333	160	0.7030	0.8333
0.1008	14.1667	170	0.7004	0.8333
0.1127	15.0	180	0.6993	0.8333

Framework versions

Transformers 4.44.2
Pytorch 2.5.0+cu121
Datasets 3.1.0
Tokenizers 0.19.1

griffio/vit-base-patch16-224-rotated-dungeons-v101

vit-base-patch16-224-rotated-dungeons-v101

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

griffio/
vit-base-patch16-224-rotated-dungeons-v101