swinv2-tiny-patch4-window8-256-finetuned_swinv2tiny-autotags-256

This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.1115
• Accuracy: 0.9655

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: 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: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.6169	0.99	61	1.1018	0.6701
0.7747	1.99	122	0.4571	0.8670
0.6088	2.99	183	0.3002	0.9198
0.3908	3.99	244	0.2334	0.9299
0.399	4.99	305	0.2138	0.9320
0.2969	5.99	366	0.1650	0.9492
0.2743	6.99	427	0.1514	0.9533
0.2947	7.99	488	0.1428	0.9513
0.2304	8.99	549	0.1541	0.9523
0.1957	9.99	610	0.1256	0.9604
0.1645	10.99	671	0.1138	0.9645
0.2317	11.99	732	0.1140	0.9655
0.1001	12.99	793	0.1068	0.9706
0.1564	13.99	854	0.1119	0.9675
0.1386	14.99	915	0.1115	0.9655

Framework versions

• Transformers 4.25.1
• Pytorch 1.10.2+cu113
• Datasets 2.10.1
• Tokenizers 0.13.2