swin-tiny-patch4-window7-224-finetuned-fluro_cls

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0000
• Accuracy: 1.0

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	0.67	1	0.7112	0.5238
No log	1.67	2	0.5591	0.8571
0.811	2.67	3	0.3781	0.9524
0.811	3.67	4	0.1995	1.0
0.811	4.67	5	0.1215	1.0
0.3531	5.67	6	0.0578	1.0
0.3531	6.67	7	0.0195	1.0
0.3531	7.67	8	0.0072	1.0
0.0618	8.67	9	0.0030	1.0
0.0618	9.67	10	0.0012	1.0
0.0618	10.67	11	0.0005	1.0
0.0079	11.67	12	0.0003	1.0
0.0079	12.67	13	0.0001	1.0
0.0079	13.67	14	0.0001	1.0
0.0051	14.67	15	0.0001	1.0
0.0051	15.67	16	0.0000	1.0
0.0051	16.67	17	0.0000	1.0
0.0017	17.67	18	0.0000	1.0
0.0017	18.67	19	0.0000	1.0
0.0017	19.67	20	0.0000	1.0
0.0004	20.67	21	0.0000	1.0
0.0004	21.67	22	0.0000	1.0
0.0004	22.67	23	0.0000	1.0
0.0022	23.67	24	0.0000	1.0
0.0022	24.67	25	0.0000	1.0
0.0022	25.67	26	0.0000	1.0
0.001	26.67	27	0.0000	1.0
0.001	27.67	28	0.0000	1.0
0.001	28.67	29	0.0000	1.0
0.0013	29.67	30	0.0000	1.0

Framework versions

• Transformers 4.25.1
• Pytorch 1.10.2+cu113
• Datasets 2.7.1
• Tokenizers 0.13.2