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: 1.0498
Accuracy: 0.5008

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: 1e-05
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
1.1042	1.0	376	1.0929	0.3856
1.1057	2.0	752	1.0909	0.3923
1.1149	3.0	1128	1.0890	0.3940
1.1189	4.0	1504	1.0872	0.3907
1.1034	5.0	1880	1.0854	0.3973
1.0984	6.0	2256	1.0837	0.4023
1.1017	7.0	2632	1.0821	0.4073
1.0896	8.0	3008	1.0805	0.4157
1.0923	9.0	3384	1.0789	0.4240
1.0904	10.0	3760	1.0774	0.4257
1.0756	11.0	4136	1.0759	0.4324
1.0821	12.0	4512	1.0745	0.4357
1.0908	13.0	4888	1.0731	0.4424
1.0966	14.0	5264	1.0718	0.4441
1.0817	15.0	5640	1.0706	0.4441
1.0679	16.0	6016	1.0693	0.4457
1.0876	17.0	6392	1.0681	0.4457
1.064	18.0	6768	1.0670	0.4474
1.072	19.0	7144	1.0658	0.4474
1.09	20.0	7520	1.0648	0.4474
1.081	21.0	7896	1.0637	0.4508
1.0655	22.0	8272	1.0627	0.4558
1.0774	23.0	8648	1.0618	0.4574
1.0736	24.0	9024	1.0609	0.4608
1.0774	25.0	9400	1.0600	0.4691
1.055	26.0	9776	1.0591	0.4691
1.0689	27.0	10152	1.0583	0.4674
1.0612	28.0	10528	1.0576	0.4691
1.0701	29.0	10904	1.0568	0.4691
1.0631	30.0	11280	1.0561	0.4741
1.0623	31.0	11656	1.0555	0.4758
1.0571	32.0	12032	1.0549	0.4791
1.0769	33.0	12408	1.0543	0.4841
1.0511	34.0	12784	1.0537	0.4891
1.0652	35.0	13160	1.0532	0.4891
1.0631	36.0	13536	1.0527	0.4908
1.0446	37.0	13912	1.0523	0.4908
1.0591	38.0	14288	1.0519	0.4925
1.0589	39.0	14664	1.0516	0.4925
1.0552	40.0	15040	1.0512	0.4942
1.0353	41.0	15416	1.0509	0.4925
1.0348	42.0	15792	1.0507	0.4958
1.0561	43.0	16168	1.0505	0.4992
1.0679	44.0	16544	1.0503	0.4992
1.0611	45.0	16920	1.0501	0.5008
1.0413	46.0	17296	1.0500	0.5008
1.0517	47.0	17672	1.0499	0.5008
1.0644	48.0	18048	1.0499	0.5008
1.052	49.0	18424	1.0498	0.5008
1.0428	50.0	18800	1.0498	0.5008

Framework versions

Transformers 4.32.1
Pytorch 2.1.0+cu121
Datasets 2.12.0
Tokenizers 0.13.2

hkivancoral/smids_5x_deit_base_sgd_00001_fold1

smids_5x_deit_base_sgd_00001_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
smids_5x_deit_base_sgd_00001_fold1