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

Loss: 0.3956
Accuracy: 0.8598

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: 8
eval_batch_size: 8
seed: 1337
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
0.448	1.0	82	0.7304	0.5725
0.5097	2.0	164	0.7652	0.4946
0.452	3.0	246	0.7565	0.4841
0.3885	4.0	328	0.7565	0.4812
0.4743	5.0	410	0.7739	0.4626
0.4749	4.0	464	0.4572	0.7988
0.4319	5.0	580	0.3956	0.8598

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cpu
Datasets 3.0.0
Tokenizers 0.19.1

hangpatrick92/TransparentBagClassifier

TransparentBagClassifier

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hangpatrick92/
TransparentBagClassifier