uisikdag/vit-base-patch16-224-in21k-fog-or-smog-classification

fogsmog_hfclass

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.3700
• Accuracy: 0.91

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: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6766	1.0	25	0.6299	0.795
0.3444	2.0	50	0.3701	0.8625
0.2456	3.0	75	0.2988	0.885
0.1402	4.0	100	0.3076	0.905
0.1275	5.0	125	0.4505	0.8525
0.0909	6.0	150	0.3739	0.8825
0.0792	7.0	175	0.3642	0.885
0.0482	8.0	200	0.3812	0.885
0.0451	9.0	225	0.3290	0.9
0.0526	10.0	250	0.4004	0.8825
0.0575	11.0	275	0.2842	0.925
0.0457	12.0	300	0.3952	0.895
0.0505	13.0	325	0.4411	0.885
0.0324	14.0	350	0.4185	0.8925
0.0354	15.0	375	0.3347	0.9025
0.0443	16.0	400	0.2949	0.915
0.0305	17.0	425	0.3603	0.905
0.0234	18.0	450	0.3858	0.8875
0.0219	19.0	475	0.3541	0.91
0.0284	20.0	500	0.3700	0.91

Framework versions

• Transformers 4.26.0
• Pytorch 1.13.1+cu117
• Datasets 2.9.0
• Tokenizers 0.13.2