cards_bottom_right_swin-tiny-patch4-window7-224-finetuned-v2

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: 0.9317
• Accuracy: 0.6079

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
1.4965	1.0	1338	1.3516	0.4156
1.4486	2.0	2677	1.1784	0.4938
1.4384	3.0	4015	1.1050	0.5223
1.4538	4.0	5354	1.0751	0.5433
1.3928	5.0	6692	1.0604	0.5440
1.4148	6.0	8031	1.0459	0.5523
1.3921	7.0	9369	1.0464	0.5501
1.3812	8.0	10708	1.0461	0.5491
1.3494	9.0	12046	1.0445	0.5486
1.3555	10.0	13385	0.9973	0.5693
1.3303	11.0	14723	0.9952	0.5719
1.3575	12.0	16062	1.0317	0.5574
1.3129	13.0	17400	0.9851	0.5813
1.3439	14.0	18739	1.0510	0.5523
1.3371	15.0	20077	0.9820	0.5795
1.2835	16.0	21416	0.9886	0.5738
1.3002	17.0	22754	0.9685	0.5869
1.289	18.0	24093	0.9519	0.5941
1.3007	19.0	25431	0.9855	0.5800
1.2927	20.0	26770	0.9499	0.5925
1.2985	21.0	28108	0.9669	0.5854
1.2957	22.0	29447	0.9551	0.5903
1.2579	23.0	30785	0.9300	0.6053
1.2475	24.0	32124	0.9296	0.6049
1.2227	25.0	33462	0.9317	0.6079
1.2069	26.0	34801	0.9609	0.5887
1.2156	27.0	36139	0.9297	0.6052
1.25	28.0	37478	0.9300	0.6062
1.2394	29.0	38816	0.9238	0.6071
1.209	29.99	40140	0.9284	0.6064

Framework versions

• Transformers 4.37.2
• Pytorch 2.0.1+cu117
• Datasets 2.17.0
• Tokenizers 0.15.2