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

Loss: 1.0440
Accuracy: 0.6889

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
1.0975	1.0	215	1.3370	0.3778
0.8761	2.0	430	1.2895	0.4444
0.7359	3.0	645	1.2565	0.4889
0.6277	4.0	860	1.2398	0.5556
0.5094	5.0	1075	1.2052	0.5556
0.4187	6.0	1290	1.1950	0.5778
0.3909	7.0	1505	1.1310	0.6
0.3137	8.0	1720	1.1412	0.5556
0.2817	9.0	1935	1.0706	0.5778
0.2108	10.0	2150	1.0537	0.6
0.1785	11.0	2365	1.0606	0.5778
0.1677	12.0	2580	1.0202	0.5778
0.1602	13.0	2795	1.0251	0.5778
0.1355	14.0	3010	1.0164	0.6
0.1234	15.0	3225	1.0019	0.5778
0.0937	16.0	3440	0.9960	0.6
0.0963	17.0	3655	0.9708	0.5778
0.0998	18.0	3870	0.9907	0.5778
0.0604	19.0	4085	0.9932	0.6
0.0724	20.0	4300	0.9792	0.5556
0.0616	21.0	4515	0.9528	0.5556
0.0591	22.0	4730	0.9741	0.5556
0.0433	23.0	4945	0.9824	0.5556
0.0476	24.0	5160	0.9907	0.5556
0.0326	25.0	5375	0.9714	0.5778
0.0325	26.0	5590	0.9834	0.6
0.0352	27.0	5805	0.9903	0.5778
0.0319	28.0	6020	0.9831	0.5778
0.0242	29.0	6235	0.9872	0.6
0.0238	30.0	6450	1.0027	0.6222
0.0166	31.0	6665	0.9985	0.5778
0.0151	32.0	6880	1.0088	0.6
0.0176	33.0	7095	1.0180	0.6
0.0221	34.0	7310	1.0038	0.6444
0.0159	35.0	7525	0.9868	0.6667
0.0115	36.0	7740	1.0104	0.6444
0.017	37.0	7955	1.0128	0.6889
0.0105	38.0	8170	1.0250	0.6444
0.0144	39.0	8385	1.0115	0.6889
0.0092	40.0	8600	1.0202	0.6667
0.0131	41.0	8815	1.0296	0.6444
0.0108	42.0	9030	1.0274	0.6889
0.0089	43.0	9245	1.0423	0.6889
0.0153	44.0	9460	1.0420	0.6889
0.0077	45.0	9675	1.0387	0.6667
0.0096	46.0	9890	1.0413	0.6889
0.0073	47.0	10105	1.0431	0.6889
0.0112	48.0	10320	1.0453	0.6889
0.0085	49.0	10535	1.0438	0.6889
0.01	50.0	10750	1.0440	0.6889

Framework versions

Transformers 4.32.1
Pytorch 2.1.1+cu121
Datasets 2.12.0
Tokenizers 0.13.2

hkivancoral/hushem_40x_deit_tiny_sgd_001_fold2

hushem_40x_deit_tiny_sgd_001_fold2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
hushem_40x_deit_tiny_sgd_001_fold2