swin-tiny-patch4-window7-224-med-device-classification

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.2927
• Accuracy: 0.75

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	1	1.6093	0.5
No log	2.0	2	1.6063	0.5
No log	3.0	3	1.6063	0.5
No log	4.0	4	1.6100	0.25
No log	5.0	5	1.6100	0.25
No log	6.0	6	1.6170	0.25
No log	7.0	7	1.6170	0.25
No log	8.0	8	1.5910	0.25
No log	9.0	9	1.5910	0.25
0.7949	10.0	10	1.5705	0.25
0.7949	11.0	11	1.5705	0.25
0.7949	12.0	12	1.5368	0.25
0.7949	13.0	13	1.5368	0.25
0.7949	14.0	14	1.4843	0.25
0.7949	15.0	15	1.4843	0.25
0.7949	16.0	16	1.4413	0.25
0.7949	17.0	17	1.4413	0.25
0.7949	18.0	18	1.4050	0.5
0.7949	19.0	19	1.4050	0.5
0.6509	20.0	20	1.3670	0.5
0.6509	21.0	21	1.3670	0.5
0.6509	22.0	22	1.3404	0.5
0.6509	23.0	23	1.3404	0.5
0.6509	24.0	24	1.3212	0.5
0.6509	25.0	25	1.3212	0.5
0.6509	26.0	26	1.3087	0.5
0.6509	27.0	27	1.3087	0.5
0.6509	28.0	28	1.2969	0.75
0.6509	29.0	29	1.2969	0.75
0.5774	30.0	30	1.2927	0.75

Framework versions

• Transformers 4.30.0
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.13.3