hushem_1x_deit_tiny_sgd_00001_fold3

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: 1.6900
• Accuracy: 0.2791

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	1.7081	0.2791
1.7325	2.0	12	1.7072	0.2791
1.7325	3.0	18	1.7063	0.2791
1.7152	4.0	24	1.7055	0.2791
1.6813	5.0	30	1.7046	0.2791
1.6813	6.0	36	1.7038	0.2791
1.6984	7.0	42	1.7030	0.2791
1.6984	8.0	48	1.7022	0.2791
1.7131	9.0	54	1.7014	0.2791
1.7337	10.0	60	1.7007	0.2791
1.7337	11.0	66	1.7000	0.2791
1.7143	12.0	72	1.6993	0.2791
1.7143	13.0	78	1.6987	0.2791
1.6884	14.0	84	1.6981	0.2791
1.7252	15.0	90	1.6975	0.2791
1.7252	16.0	96	1.6969	0.2791
1.7269	17.0	102	1.6963	0.2791
1.7269	18.0	108	1.6958	0.2791
1.6858	19.0	114	1.6953	0.2791
1.7013	20.0	120	1.6948	0.2791
1.7013	21.0	126	1.6943	0.2791
1.7051	22.0	132	1.6939	0.2791
1.7051	23.0	138	1.6935	0.2791
1.6834	24.0	144	1.6931	0.2791
1.6977	25.0	150	1.6927	0.2791
1.6977	26.0	156	1.6924	0.2791
1.7016	27.0	162	1.6920	0.2791
1.7016	28.0	168	1.6917	0.2791
1.7242	29.0	174	1.6915	0.2791
1.6808	30.0	180	1.6912	0.2791
1.6808	31.0	186	1.6910	0.2791
1.7032	32.0	192	1.6908	0.2791
1.7032	33.0	198	1.6906	0.2791
1.6261	34.0	204	1.6905	0.2791
1.7412	35.0	210	1.6903	0.2791
1.7412	36.0	216	1.6902	0.2791
1.6899	37.0	222	1.6901	0.2791
1.6899	38.0	228	1.6901	0.2791
1.6944	39.0	234	1.6900	0.2791
1.6965	40.0	240	1.6900	0.2791
1.6965	41.0	246	1.6900	0.2791
1.6787	42.0	252	1.6900	0.2791
1.6787	43.0	258	1.6900	0.2791
1.6617	44.0	264	1.6900	0.2791
1.7215	45.0	270	1.6900	0.2791
1.7215	46.0	276	1.6900	0.2791
1.6881	47.0	282	1.6900	0.2791
1.6881	48.0	288	1.6900	0.2791
1.6823	49.0	294	1.6900	0.2791
1.7275	50.0	300	1.6900	0.2791

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0