hushem_40x_deit_base_sgd_0001_fold1

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

• Loss: 1.2920
• Accuracy: 0.3778

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: 0.0001
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.3635	1.0	215	1.4586	0.2889
1.3564	2.0	430	1.4485	0.2889
1.3735	3.0	645	1.4395	0.2889
1.3415	4.0	860	1.4312	0.2889
1.3033	5.0	1075	1.4236	0.2889
1.3111	6.0	1290	1.4165	0.2667
1.2796	7.0	1505	1.4098	0.2667
1.265	8.0	1720	1.4035	0.2667
1.2454	9.0	1935	1.3975	0.2667
1.2437	10.0	2150	1.3919	0.2667
1.2689	11.0	2365	1.3867	0.2667
1.212	12.0	2580	1.3818	0.2667
1.2193	13.0	2795	1.3771	0.2667
1.2167	14.0	3010	1.3726	0.2667
1.205	15.0	3225	1.3683	0.2667
1.2084	16.0	3440	1.3641	0.2889
1.1861	17.0	3655	1.3601	0.3333
1.1898	18.0	3870	1.3563	0.3556
1.1745	19.0	4085	1.3526	0.3556
1.1602	20.0	4300	1.3489	0.3556
1.1523	21.0	4515	1.3454	0.3556
1.1329	22.0	4730	1.3420	0.3556
1.1475	23.0	4945	1.3387	0.3556
1.1333	24.0	5160	1.3354	0.3556
1.1285	25.0	5375	1.3322	0.3333
1.0938	26.0	5590	1.3292	0.3333
1.0832	27.0	5805	1.3262	0.3333
1.0889	28.0	6020	1.3234	0.3333
1.0886	29.0	6235	1.3206	0.3333
1.0684	30.0	6450	1.3180	0.3333
1.0707	31.0	6665	1.3154	0.3333
1.068	32.0	6880	1.3130	0.3333
1.0647	33.0	7095	1.3107	0.3556
1.0516	34.0	7310	1.3085	0.3556
1.0515	35.0	7525	1.3064	0.3556
1.0477	36.0	7740	1.3045	0.3556
1.0685	37.0	7955	1.3027	0.3556
1.0459	38.0	8170	1.3010	0.3556
1.0276	39.0	8385	1.2995	0.3556
1.016	40.0	8600	1.2981	0.3556
1.044	41.0	8815	1.2969	0.3556
1.0849	42.0	9030	1.2957	0.3556
1.0504	43.0	9245	1.2948	0.3778
1.0115	44.0	9460	1.2940	0.3778
1.0336	45.0	9675	1.2933	0.3778
1.0415	46.0	9890	1.2928	0.3778
1.013	47.0	10105	1.2924	0.3778
1.0207	48.0	10320	1.2921	0.3778
1.054	49.0	10535	1.2920	0.3778
1.0317	50.0	10750	1.2920	0.3778

Framework versions

• Transformers 4.32.1
• Pytorch 2.1.0+cu121
• Datasets 2.12.0
• Tokenizers 0.13.2