swin-tiny-patch4-window7-224-dmae-va-U

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

• Loss: 0.0900
• Accuracy: 0.9725

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: 40

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.9	7	1.4643	0.2110
1.4218	1.94	15	1.4070	0.3303
1.3226	2.97	23	1.3454	0.3486
1.1908	4.0	31	1.1438	0.4220
1.1908	4.9	38	0.8730	0.5780
0.9441	5.94	46	0.8100	0.6422
0.7185	6.97	54	0.6099	0.7339
0.6526	8.0	62	0.5096	0.7890
0.6526	8.9	69	0.4925	0.8165
0.5185	9.94	77	0.3989	0.8349
0.4946	10.97	85	0.3276	0.8807
0.4469	12.0	93	0.3023	0.8899
0.376	12.9	100	0.3112	0.8991
0.376	13.94	108	0.2117	0.9266
0.3156	14.97	116	0.2024	0.9174
0.366	16.0	124	0.2065	0.9450
0.2806	16.9	131	0.1942	0.9174
0.2806	17.94	139	0.2393	0.9174
0.2695	18.97	147	0.1498	0.9541
0.2357	20.0	155	0.1465	0.9358
0.2345	20.9	162	0.1522	0.9633
0.2157	21.94	170	0.1403	0.9450
0.2157	22.97	178	0.0999	0.9541
0.1894	24.0	186	0.1427	0.9633
0.2195	24.9	193	0.0949	0.9633
0.1874	25.94	201	0.1152	0.9633
0.1874	26.97	209	0.1226	0.9541
0.1815	28.0	217	0.0964	0.9633
0.1619	28.9	224	0.0912	0.9633
0.201	29.94	232	0.0903	0.9633
0.1659	30.97	240	0.0745	0.9633
0.1659	32.0	248	0.0781	0.9633
0.1459	32.9	255	0.0930	0.9633
0.1459	33.94	263	0.0900	0.9725
0.1487	34.97	271	0.0796	0.9725
0.1487	36.0	279	0.0784	0.9725
0.1504	36.13	280	0.0784	0.9725

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0