teacher-status-van-tiny-256-2

This model is a fine-tuned version of Visual-Attention-Network/van-tiny on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.0916
• Accuracy: 0.9759
• F1 Score: 0.9842
• Recall: 0.9757
• Precision: 0.9929

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	F1 Score	Recall	Precision
0.6896	0.99	26	0.6707	0.7701	0.8701	1.0	0.7701
0.5438	1.98	52	0.4302	0.7701	0.8701	1.0	0.7701
0.3756	2.97	78	0.2762	0.8850	0.9285	0.9688	0.8914
0.3017	4.0	105	0.2002	0.9225	0.9503	0.9618	0.9390
0.257	4.99	131	0.1794	0.9385	0.9605	0.9722	0.9492
0.2345	5.98	157	0.1485	0.9358	0.9582	0.9549	0.9615
0.2318	6.97	183	0.1302	0.9439	0.9631	0.9514	0.9751
0.2173	8.0	210	0.1277	0.9519	0.9689	0.9722	0.9655
0.2058	8.99	236	0.1269	0.9572	0.9722	0.9722	0.9722
0.1955	9.98	262	0.1146	0.9572	0.9724	0.9792	0.9658
0.2083	10.97	288	0.1083	0.9652	0.9772	0.9688	0.9859
0.1886	12.0	315	0.1048	0.9599	0.9741	0.9792	0.9691
0.1618	12.99	341	0.1033	0.9626	0.9757	0.9757	0.9757
0.1908	13.98	367	0.1044	0.9599	0.9739	0.9722	0.9756
0.1594	14.97	393	0.0915	0.9626	0.9758	0.9792	0.9724
0.1474	16.0	420	0.0916	0.9759	0.9842	0.9757	0.9929
0.1734	16.99	446	0.0951	0.9652	0.9773	0.9722	0.9825
0.1484	17.98	472	0.1049	0.9706	0.9809	0.9792	0.9826
0.1495	18.97	498	0.0930	0.9679	0.9791	0.9757	0.9825
0.1385	20.0	525	0.0955	0.9626	0.9759	0.9826	0.9692
0.1492	20.99	551	0.0911	0.9599	0.9741	0.9792	0.9691
0.1401	21.98	577	0.0927	0.9706	0.9809	0.9792	0.9826
0.1288	22.97	603	0.0940	0.9706	0.9809	0.9792	0.9826
0.1304	24.0	630	0.0913	0.9652	0.9775	0.9826	0.9725
0.14	24.99	656	0.0979	0.9652	0.9776	0.9861	0.9693
0.1461	25.98	682	0.0874	0.9706	0.9810	0.9861	0.9759
0.1429	26.97	708	0.0837	0.9706	0.9808	0.9757	0.9860
0.1444	28.0	735	0.0876	0.9679	0.9792	0.9792	0.9792
0.145	28.99	761	0.0903	0.9706	0.9809	0.9792	0.9826
0.1445	29.71	780	0.0882	0.9679	0.9791	0.9757	0.9825

Framework versions

• Transformers 4.36.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.0
• Tokenizers 0.15.0