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: 1.1092
Accuracy: 0.4634

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
1.7467	1.0	220	1.6098	0.2683
1.5306	2.0	440	1.5314	0.2683
1.3989	3.0	660	1.5004	0.2439
1.3588	4.0	880	1.4811	0.2195
1.3953	5.0	1100	1.4639	0.2683
1.3096	6.0	1320	1.4476	0.2439
1.2743	7.0	1540	1.4329	0.2683
1.2405	8.0	1760	1.4190	0.2927
1.253	9.0	1980	1.4052	0.3171
1.2253	10.0	2200	1.3912	0.3171
1.1663	11.0	2420	1.3767	0.3659
1.1699	12.0	2640	1.3616	0.3659
1.1615	13.0	2860	1.3463	0.3659
1.0999	14.0	3080	1.3303	0.3902
1.1286	15.0	3300	1.3148	0.3659
1.1333	16.0	3520	1.2990	0.3659
1.075	17.0	3740	1.2842	0.3659
1.0779	18.0	3960	1.2709	0.3659
1.0652	19.0	4180	1.2579	0.3659
1.0475	20.0	4400	1.2462	0.3659
1.0095	21.0	4620	1.2350	0.3902
1.0607	22.0	4840	1.2247	0.3902
1.0243	23.0	5060	1.2151	0.4146
1.0174	24.0	5280	1.2064	0.4146
0.9654	25.0	5500	1.1977	0.3902
1.017	26.0	5720	1.1899	0.4146
1.0002	27.0	5940	1.1820	0.3902
1.0191	28.0	6160	1.1750	0.3902
0.9876	29.0	6380	1.1683	0.3902
0.9526	30.0	6600	1.1623	0.4146
0.9957	31.0	6820	1.1566	0.4390
0.9778	32.0	7040	1.1513	0.4390
0.9223	33.0	7260	1.1464	0.4634
0.9281	34.0	7480	1.1418	0.4634
0.9107	35.0	7700	1.1376	0.4634
0.9485	36.0	7920	1.1336	0.4634
0.9035	37.0	8140	1.1298	0.4634
0.9223	38.0	8360	1.1266	0.4634
0.9312	39.0	8580	1.1235	0.4634
0.8782	40.0	8800	1.1209	0.4634
0.9252	41.0	9020	1.1184	0.4634
0.8989	42.0	9240	1.1164	0.4634
0.8959	43.0	9460	1.1145	0.4634
0.8589	44.0	9680	1.1130	0.4634
0.8899	45.0	9900	1.1117	0.4634
0.8915	46.0	10120	1.1107	0.4634
0.9043	47.0	10340	1.1100	0.4634
0.8309	48.0	10560	1.1095	0.4634
0.8724	49.0	10780	1.1093	0.4634
0.9011	50.0	11000	1.1092	0.4634

Framework versions

Transformers 4.32.1
Pytorch 2.1.0+cu121
Datasets 2.12.0
Tokenizers 0.13.2

hkivancoral/hushem_40x_deit_small_sgd_0001_fold5

hushem_40x_deit_small_sgd_0001_fold5

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
hushem_40x_deit_small_sgd_0001_fold5