This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the cifar100 dataset. It achieves the following results on the evaluation set:

Loss: 0.4223
Accuracy: 0.8735

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: 4e-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: 20 (with early stopping)

Training results

Training Loss	Epoch	Step	Accuracy	Validation Loss
0.6439	1.0	781	0.8138	0.6126
0.6222	2.0	1562	0.8393	0.5094
0.2912	3.0	2343	0.861	0.4452
0.2234	4.0	3124	0.8679	0.4330
0.121	5.0	3905	0.8735	0.4223
0.2589	6.0	4686	0.8622	0.4775
0.1419	7.0	5467	0.8642	0.4900
0.1513	8.0	6248	0.8667	0.4956

Framework versions

Transformers 4.20.1
Pytorch 1.11.0
Datasets 2.1.0
Tokenizers 0.12.1

MazenAmria/swin-tiny-finetuned-cifar100

swin-tiny-finetuned-cifar100

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

MazenAmria/
swin-tiny-finetuned-cifar100