swin-tiny-patch4-window7-224-finetuned-woody

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: 0.4349
• Accuracy: 0.7927

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
0.632	1.0	58	0.5883	0.6836
0.6067	2.0	116	0.6017	0.6848
0.5865	3.0	174	0.5695	0.7042
0.553	4.0	232	0.5185	0.7515
0.5468	5.0	290	0.5108	0.7430
0.5473	6.0	348	0.4882	0.7648
0.5381	7.0	406	0.4800	0.7588
0.5468	8.0	464	0.5056	0.7358
0.5191	9.0	522	0.4784	0.7673
0.5318	10.0	580	0.4762	0.7636
0.5079	11.0	638	0.4859	0.7673
0.5216	12.0	696	0.4691	0.7697
0.515	13.0	754	0.4857	0.7624
0.5186	14.0	812	0.4685	0.7733
0.4748	15.0	870	0.4536	0.7818
0.4853	16.0	928	0.4617	0.7770
0.4868	17.0	986	0.4622	0.7782
0.4572	18.0	1044	0.4583	0.7770
0.4679	19.0	1102	0.4590	0.7733
0.4508	20.0	1160	0.4576	0.7903
0.4663	21.0	1218	0.4542	0.7891
0.4533	22.0	1276	0.4428	0.7903
0.4892	23.0	1334	0.4372	0.7867
0.4704	24.0	1392	0.4414	0.7903
0.4304	25.0	1450	0.4430	0.7988
0.4411	26.0	1508	0.4348	0.7818
0.4604	27.0	1566	0.4387	0.7927
0.441	28.0	1624	0.4378	0.7964
0.442	29.0	1682	0.4351	0.7915
0.4585	30.0	1740	0.4349	0.7927

Framework versions

• Transformers 4.23.1
• Pytorch 1.12.1+cu113
• Datasets 2.6.0
• Tokenizers 0.13.1