b07611031/leafback-swin-tiny-patch4-window7-224-finetuned

swin-tiny-patch4-window7-224-finetuned-eurosat

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: 0.1073
• Accuracy: 0.9675

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: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	5	0.6616	0.6299
0.6583	2.0	10	0.5232	0.7597
0.6583	3.0	15	0.5043	0.7857
0.3346	4.0	20	0.2879	0.8766
0.3346	5.0	25	0.2424	0.9091
0.1544	6.0	30	0.2217	0.8896
0.1544	7.0	35	0.1466	0.9221
0.088	8.0	40	0.1261	0.9481
0.088	9.0	45	0.1680	0.9221
0.0977	10.0	50	0.1446	0.9351
0.0977	11.0	55	0.1812	0.9221
0.0719	12.0	60	0.1798	0.9286
0.0719	13.0	65	0.1056	0.9610
0.0629	14.0	70	0.1073	0.9675
0.0629	15.0	75	0.1106	0.9545
0.0414	16.0	80	0.1286	0.9416
0.0414	17.0	85	0.0761	0.9610
0.0397	18.0	90	0.0785	0.9675
0.0397	19.0	95	0.0746	0.9675
0.0487	20.0	100	0.0684	0.9675
0.0487	21.0	105	0.0602	0.9610
0.0244	22.0	110	0.0551	0.9675
0.0244	23.0	115	0.0639	0.9675
0.0214	24.0	120	0.0583	0.9675
0.0214	25.0	125	0.0663	0.9675
0.0261	26.0	130	0.1006	0.9610
0.0261	27.0	135	0.0711	0.9675
0.019	28.0	140	0.0629	0.9675
0.019	29.0	145	0.0728	0.9610
0.0237	30.0	150	0.0747	0.9610

Framework versions

• Transformers 4.38.1
• Pytorch 1.10.0+cu111
• Datasets 2.17.1
• Tokenizers 0.15.2