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: 2.5728
Accuracy: 0.5116

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	1.5927	0.2558
1.8022	2.0	12	1.4288	0.2558
1.8022	3.0	18	1.5308	0.2558
1.5239	4.0	24	1.4740	0.2558
1.4801	5.0	30	2.2308	0.2558
1.4801	6.0	36	1.4153	0.2558
1.5953	7.0	42	1.4884	0.2326
1.5953	8.0	48	1.5775	0.2558
1.4262	9.0	54	1.4549	0.2558
1.4607	10.0	60	1.4401	0.2558
1.4607	11.0	66	1.3707	0.3256
1.3771	12.0	72	1.3285	0.3721
1.3771	13.0	78	1.2980	0.3721
1.2887	14.0	84	1.6464	0.2558
1.194	15.0	90	1.4572	0.2791
1.194	16.0	96	1.5171	0.3256
1.2311	17.0	102	1.4178	0.4186
1.2311	18.0	108	1.3427	0.3256
1.2234	19.0	114	1.3369	0.3721
1.1384	20.0	120	1.4187	0.3721
1.1384	21.0	126	1.5195	0.2558
1.0551	22.0	132	1.5010	0.3488
1.0551	23.0	138	1.4046	0.3721
0.958	24.0	144	1.2991	0.3721
0.9405	25.0	150	1.3687	0.4651
0.9405	26.0	156	1.8052	0.3256
0.7255	27.0	162	1.6391	0.4419
0.7255	28.0	168	1.3419	0.5116
0.6435	29.0	174	1.7678	0.4419
0.4939	30.0	180	2.2022	0.3256
0.4939	31.0	186	1.6603	0.5116
0.4434	32.0	192	1.5952	0.4884
0.4434	33.0	198	1.7642	0.5116
0.2864	34.0	204	2.0069	0.4651
0.1858	35.0	210	2.5370	0.4884
0.1858	36.0	216	2.2076	0.4651
0.1248	37.0	222	2.7233	0.5581
0.1248	38.0	228	2.6548	0.5349
0.0495	39.0	234	2.4864	0.5116
0.0526	40.0	240	2.5601	0.5116
0.0526	41.0	246	2.5731	0.5116
0.0219	42.0	252	2.5728	0.5116
0.0219	43.0	258	2.5728	0.5116
0.0327	44.0	264	2.5728	0.5116
0.0324	45.0	270	2.5728	0.5116
0.0324	46.0	276	2.5728	0.5116
0.0326	47.0	282	2.5728	0.5116
0.0326	48.0	288	2.5728	0.5116
0.0208	49.0	294	2.5728	0.5116
0.0503	50.0	300	2.5728	0.5116

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

hkivancoral/hushem_1x_deit_base_rms_0001_fold3

hushem_1x_deit_base_rms_0001_fold3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hkivancoral/
hushem_1x_deit_base_rms_0001_fold3