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: 1.5214
Accuracy: 0.1333

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
No log	1.0	6	1.5231	0.1333
1.415	2.0	12	1.5230	0.1333
1.415	3.0	18	1.5229	0.1333
1.4163	4.0	24	1.5228	0.1333
1.412	5.0	30	1.5228	0.1333
1.412	6.0	36	1.5227	0.1333
1.4139	7.0	42	1.5226	0.1333
1.4139	8.0	48	1.5225	0.1333
1.425	9.0	54	1.5225	0.1333
1.4037	10.0	60	1.5224	0.1333
1.4037	11.0	66	1.5223	0.1333
1.4157	12.0	72	1.5223	0.1333
1.4157	13.0	78	1.5222	0.1333
1.4043	14.0	84	1.5221	0.1333
1.4083	15.0	90	1.5221	0.1333
1.4083	16.0	96	1.5220	0.1333
1.4137	17.0	102	1.5220	0.1333
1.4137	18.0	108	1.5219	0.1333
1.4171	19.0	114	1.5219	0.1333
1.4171	20.0	120	1.5218	0.1333
1.4171	21.0	126	1.5218	0.1333
1.415	22.0	132	1.5218	0.1333
1.415	23.0	138	1.5217	0.1333
1.4319	24.0	144	1.5217	0.1333
1.416	25.0	150	1.5217	0.1333
1.416	26.0	156	1.5216	0.1333
1.4082	27.0	162	1.5216	0.1333
1.4082	28.0	168	1.5216	0.1333
1.413	29.0	174	1.5216	0.1333
1.4097	30.0	180	1.5215	0.1333
1.4097	31.0	186	1.5215	0.1333
1.4098	32.0	192	1.5215	0.1333
1.4098	33.0	198	1.5215	0.1333
1.4176	34.0	204	1.5215	0.1333
1.4032	35.0	210	1.5214	0.1333
1.4032	36.0	216	1.5214	0.1333
1.4087	37.0	222	1.5214	0.1333
1.4087	38.0	228	1.5214	0.1333
1.4343	39.0	234	1.5214	0.1333
1.4129	40.0	240	1.5214	0.1333
1.4129	41.0	246	1.5214	0.1333
1.4161	42.0	252	1.5214	0.1333
1.4161	43.0	258	1.5214	0.1333
1.3976	44.0	264	1.5214	0.1333
1.4177	45.0	270	1.5214	0.1333
1.4177	46.0	276	1.5214	0.1333
1.4164	47.0	282	1.5214	0.1333
1.4164	48.0	288	1.5214	0.1333
1.4144	49.0	294	1.5214	0.1333
1.4018	50.0	300	1.5214	0.1333

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.14.7
Tokenizers 0.15.0

hkivancoral/hushem_1x_deit_base_sgd_0001_fold1

hushem_1x_deit_base_sgd_0001_fold1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
hushem_1x_deit_base_sgd_0001_fold1