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

Loss: 0.5242
Accuracy: 0.9091

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	1	0.6762	0.6364
No log	2.0	2	0.6309	0.7273
No log	3.0	3	0.6095	0.6364
No log	4.0	4	0.5775	0.6364
No log	5.0	5	0.5443	0.8182
No log	6.0	6	0.5242	0.9091
No log	7.0	7	0.5149	0.8182
No log	8.0	8	0.5094	0.8182
No log	9.0	9	0.5038	0.8182
0.4095	10.0	10	0.4992	0.8182

Framework versions

Transformers 4.19.4
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1

shivarama23/swin-tiny-patch4-window7-224-finetuned-image_quality

swin-tiny-patch4-window7-224-finetuned-image_quality

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

shivarama23/
swin-tiny-patch4-window7-224-finetuned-image_quality