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

Loss: 0.0360
Accuracy: 0.9922

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2199	1.0	81	0.0596	0.9852
0.1283	2.0	162	0.0360	0.9922
0.1013	3.0	243	0.0305	0.9922

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cpu
Datasets 2.14.6
Tokenizers 0.14.1

zbbg1111/swin-tiny-patch4-window7-224-finetuned-geo-industrials1

swin-tiny-patch4-window7-224-finetuned-geo-industrials1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

zbbg1111/
swin-tiny-patch4-window7-224-finetuned-geo-industrials1