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

Loss: 0.3767
Accuracy: 0.8614

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: 0.001
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
0.9992	1.0	76	0.9734	0.5159
0.868	2.0	152	0.8565	0.6578
0.7395	3.0	228	0.7685	0.7112
0.6957	4.0	304	0.6964	0.7329
0.6074	5.0	380	0.6430	0.7546
0.5254	6.0	456	0.6017	0.7763
0.5109	7.0	532	0.5681	0.7930
0.4805	8.0	608	0.5426	0.7963
0.5102	9.0	684	0.5230	0.7980
0.3976	10.0	760	0.5054	0.8047
0.4427	11.0	836	0.4905	0.8130
0.4239	12.0	912	0.4775	0.8230
0.3866	13.0	988	0.4665	0.8247
0.3955	14.0	1064	0.4585	0.8264
0.3407	15.0	1140	0.4495	0.8314
0.3573	16.0	1216	0.4427	0.8347
0.3641	17.0	1292	0.4365	0.8364
0.3346	18.0	1368	0.4307	0.8397
0.3763	19.0	1444	0.4260	0.8414
0.3869	20.0	1520	0.4209	0.8481
0.3653	21.0	1596	0.4169	0.8497
0.3686	22.0	1672	0.4141	0.8548
0.3341	23.0	1748	0.4097	0.8531
0.3374	24.0	1824	0.4075	0.8564
0.2762	25.0	1900	0.4048	0.8548
0.3405	26.0	1976	0.4003	0.8548
0.2508	27.0	2052	0.3979	0.8581
0.3194	28.0	2128	0.3965	0.8531
0.2863	29.0	2204	0.3942	0.8598
0.2965	30.0	2280	0.3922	0.8614
0.3328	31.0	2356	0.3904	0.8614
0.2682	32.0	2432	0.3879	0.8614
0.27	33.0	2508	0.3869	0.8631
0.3255	34.0	2584	0.3856	0.8598
0.5893	35.0	2660	0.3845	0.8614
0.2978	36.0	2736	0.3831	0.8614
0.3197	37.0	2812	0.3822	0.8631
0.2821	38.0	2888	0.3814	0.8631
0.2797	39.0	2964	0.3806	0.8631
0.3067	40.0	3040	0.3796	0.8631
0.2337	41.0	3116	0.3790	0.8648
0.2989	42.0	3192	0.3784	0.8631
0.2792	43.0	3268	0.3779	0.8631
0.2985	44.0	3344	0.3775	0.8631
0.2895	45.0	3420	0.3772	0.8614
0.2249	46.0	3496	0.3770	0.8614
0.2475	47.0	3572	0.3768	0.8631
0.2872	48.0	3648	0.3767	0.8631
0.2536	49.0	3724	0.3767	0.8614
0.3607	50.0	3800	0.3767	0.8614

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

hkivancoral/smids_1x_deit_small_sgd_001_fold1

smids_1x_deit_small_sgd_001_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
smids_1x_deit_small_sgd_001_fold1