compoundleaf-swin-tiny-patch4-window7-224-finetuned

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: 0.0204
• Accuracy: 0.9955

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	7	0.9808	0.5446
1.1008	2.0	14	0.6537	0.8438
0.6618	3.0	21	0.2581	0.9464
0.6618	4.0	28	0.0740	0.9866
0.1685	5.0	35	0.0405	0.9911
0.0552	6.0	42	0.0824	0.9866
0.0552	7.0	49	0.0753	0.9777
0.0422	8.0	56	0.0204	0.9955
0.0212	9.0	63	0.0646	0.9821
0.02	10.0	70	0.0172	0.9955
0.02	11.0	77	0.0279	0.9955
0.0159	12.0	84	0.0221	0.9955
0.0053	13.0	91	0.0415	0.9866
0.0053	14.0	98	0.0222	0.9955
0.0075	15.0	105	0.0408	0.9955
0.003	16.0	112	0.0187	0.9955
0.003	17.0	119	0.0307	0.9911
0.0073	18.0	126	0.0327	0.9955
0.0079	19.0	133	0.0203	0.9955
0.0066	20.0	140	0.0319	0.9955
0.0066	21.0	147	0.0451	0.9866
0.0038	22.0	154	0.0264	0.9955
0.0122	23.0	161	0.0968	0.9821
0.0122	24.0	168	0.0547	0.9911
0.0096	25.0	175	0.0260	0.9955
0.0034	26.0	182	0.0432	0.9911
0.0034	27.0	189	0.0587	0.9911
0.009	28.0	196	0.0478	0.9911
0.004	29.0	203	0.0323	0.9955
0.0081	30.0	210	0.0302	0.9955

Framework versions

• Transformers 4.38.1
• Pytorch 1.10.0+cu111
• Datasets 2.17.1
• Tokenizers 0.15.2