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: 1.5789
Accuracy: 0.1463

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
No log	1.0	6	1.6455	0.1220
1.6035	2.0	12	1.6420	0.1220
1.6035	3.0	18	1.6386	0.1463
1.6142	4.0	24	1.6353	0.1463
1.5857	5.0	30	1.6321	0.1463
1.5857	6.0	36	1.6289	0.1463
1.5718	7.0	42	1.6259	0.1463
1.5718	8.0	48	1.6232	0.1463
1.5833	9.0	54	1.6206	0.1463
1.5737	10.0	60	1.6178	0.1463
1.5737	11.0	66	1.6153	0.1463
1.5614	12.0	72	1.6128	0.1220
1.5614	13.0	78	1.6104	0.1220
1.5648	14.0	84	1.6081	0.1220
1.5575	15.0	90	1.6060	0.1220
1.5575	16.0	96	1.6040	0.1220
1.5452	17.0	102	1.6020	0.1220
1.5452	18.0	108	1.6002	0.1220
1.5768	19.0	114	1.5984	0.1220
1.5464	20.0	120	1.5966	0.1220
1.5464	21.0	126	1.5950	0.1220
1.5149	22.0	132	1.5934	0.1220
1.5149	23.0	138	1.5920	0.1220
1.6056	24.0	144	1.5905	0.1220
1.5161	25.0	150	1.5892	0.1220
1.5161	26.0	156	1.5879	0.1220
1.519	27.0	162	1.5868	0.1220
1.519	28.0	168	1.5857	0.1220
1.5531	29.0	174	1.5848	0.1220
1.5347	30.0	180	1.5839	0.1220
1.5347	31.0	186	1.5831	0.1220
1.5238	32.0	192	1.5824	0.1220
1.5238	33.0	198	1.5817	0.1463
1.5463	34.0	204	1.5811	0.1463
1.5219	35.0	210	1.5805	0.1463
1.5219	36.0	216	1.5800	0.1463
1.5056	37.0	222	1.5797	0.1463
1.5056	38.0	228	1.5794	0.1463
1.5505	39.0	234	1.5791	0.1463
1.5261	40.0	240	1.5790	0.1463
1.5261	41.0	246	1.5789	0.1463
1.5175	42.0	252	1.5789	0.1463
1.5175	43.0	258	1.5789	0.1463
1.5317	44.0	264	1.5789	0.1463
1.5241	45.0	270	1.5789	0.1463
1.5241	46.0	276	1.5789	0.1463
1.5533	47.0	282	1.5789	0.1463
1.5533	48.0	288	1.5789	0.1463
1.4945	49.0	294	1.5789	0.1463
1.5379	50.0	300	1.5789	0.1463

Framework versions

Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1

hkivancoral/hushem_1x_deit_tiny_sgd_lr0001_fold5

hushem_1x_deit_tiny_sgd_lr0001_fold5

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
hushem_1x_deit_tiny_sgd_lr0001_fold5