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

Loss: 1.0084
Accuracy: 0.8571

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: 1e-05
train_batch_size: 4
eval_batch_size: 8
seed: 1024
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 12
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	12	1.1281	0.8571
No log	2.0	24	1.1248	0.8571
No log	3.0	36	1.0930	0.8571
No log	4.0	48	1.1040	0.8214
No log	5.0	60	1.0646	0.8214
No log	6.0	72	1.0540	0.8214
No log	7.0	84	1.0309	0.8571
No log	8.0	96	1.0274	0.8571
No log	9.0	108	1.0155	0.8571
No log	10.0	120	1.0079	0.8571
No log	11.0	132	1.0175	0.8571
No log	12.0	144	1.0029	0.8571

Framework versions

Transformers 4.44.2
Pytorch 2.5.0+cu121
Datasets 3.1.0
Tokenizers 0.19.1

griffio/vit-base-patch16-224-in21k-rotated-dungeons-v002

vit-base-patch16-224-in21k-rotated-dungeons-v002

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

griffio/
vit-base-patch16-224-in21k-rotated-dungeons-v002