resnet-50-bottomCleanedData

This model is a fine-tuned version of microsoft/resnet-50 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.0822
• Accuracy: 0.9762

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 7
• total_train_batch_size: 56
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.01
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.3323	1.0	141	1.3319	0.5187
1.1302	2.0	283	1.1059	0.5335
0.8793	2.99	424	0.7848	0.7094
0.7652	4.0	566	0.7255	0.7219
0.7708	4.99	707	0.5280	0.8173
0.6153	6.0	849	0.4221	0.8490
0.5895	7.0	991	0.4015	0.8570
0.5617	8.0	1132	0.2998	0.9001
0.517	9.0	1274	0.2737	0.9160
0.5366	9.99	1415	0.2229	0.9240
0.4645	11.0	1557	0.2038	0.9330
0.4114	11.99	1698	0.1851	0.9376
0.4528	13.0	1840	0.1796	0.9432
0.4182	14.0	1982	0.1578	0.9523
0.432	15.0	2123	0.1660	0.9421
0.4442	16.0	2265	0.1401	0.9557
0.4059	16.99	2406	0.1332	0.9591
0.3498	18.0	2548	0.1431	0.9535
0.3869	18.99	2689	0.1237	0.9512
0.3639	20.0	2831	0.1193	0.9603
0.3819	21.0	2973	0.1234	0.9557
0.3491	22.0	3114	0.1207	0.9569
0.3259	23.0	3256	0.1234	0.9591
0.3199	23.99	3397	0.1028	0.9659
0.3398	25.0	3539	0.1010	0.9603
0.3108	25.99	3680	0.1015	0.9671
0.3417	27.0	3822	0.1080	0.9614
0.3835	28.0	3964	0.1056	0.9591
0.3336	29.0	4105	0.1011	0.9637
0.3035	30.0	4247	0.0972	0.9614
0.2559	30.99	4388	0.0941	0.9659
0.378	32.0	4530	0.0963	0.9603
0.2932	32.99	4671	0.0916	0.9716
0.3072	34.0	4813	0.0917	0.9671
0.3081	35.0	4955	0.1025	0.9625
0.2724	36.0	5096	0.0874	0.9671
0.2621	37.0	5238	0.0847	0.9705
0.3521	37.99	5379	0.0829	0.9728
0.2883	39.0	5521	0.0860	0.9728
0.2617	39.99	5662	0.0898	0.9682
0.2893	41.0	5804	0.0877	0.9671
0.2994	42.0	5946	0.0822	0.9762
0.2483	43.0	6087	0.0834	0.9705
0.301	44.0	6229	0.0883	0.9694
0.2648	44.99	6370	0.0834	0.9705
0.2902	46.0	6512	0.0879	0.9648
0.299	46.99	6653	0.0843	0.9694
0.2726	48.0	6795	0.0920	0.9659
0.3252	49.0	6937	0.0857	0.9716
0.274	49.8	7050	0.0813	0.9762

Framework versions

• Transformers 4.28.1
• Pytorch 2.0.0+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3