hushem_1x_deit_small_sgd_00001_fold2

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: 1.5076
• Accuracy: 0.1778

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	1.5128	0.1778
1.5351	2.0	12	1.5126	0.1778
1.5351	3.0	18	1.5123	0.1778
1.521	4.0	24	1.5120	0.1778
1.5462	5.0	30	1.5118	0.1778
1.5462	6.0	36	1.5116	0.1778
1.5099	7.0	42	1.5113	0.1778
1.5099	8.0	48	1.5111	0.1778
1.5333	9.0	54	1.5109	0.1778
1.5206	10.0	60	1.5106	0.1778
1.5206	11.0	66	1.5105	0.1778
1.5227	12.0	72	1.5103	0.1778
1.5227	13.0	78	1.5101	0.1778
1.5256	14.0	84	1.5099	0.1778
1.5395	15.0	90	1.5097	0.1778
1.5395	16.0	96	1.5095	0.1778
1.5169	17.0	102	1.5094	0.1778
1.5169	18.0	108	1.5092	0.1778
1.5502	19.0	114	1.5091	0.1778
1.4882	20.0	120	1.5090	0.1778
1.4882	21.0	126	1.5088	0.1778
1.5202	22.0	132	1.5087	0.1778
1.5202	23.0	138	1.5086	0.1778
1.5139	24.0	144	1.5085	0.1778
1.4995	25.0	150	1.5084	0.1778
1.4995	26.0	156	1.5083	0.1778
1.5175	27.0	162	1.5082	0.1778
1.5175	28.0	168	1.5081	0.1778
1.5365	29.0	174	1.5081	0.1778
1.5232	30.0	180	1.5080	0.1778
1.5232	31.0	186	1.5079	0.1778
1.5236	32.0	192	1.5079	0.1778
1.5236	33.0	198	1.5078	0.1778
1.5292	34.0	204	1.5078	0.1778
1.544	35.0	210	1.5077	0.1778
1.544	36.0	216	1.5077	0.1778
1.4971	37.0	222	1.5077	0.1778
1.4971	38.0	228	1.5077	0.1778
1.4951	39.0	234	1.5076	0.1778
1.5452	40.0	240	1.5076	0.1778
1.5452	41.0	246	1.5076	0.1778
1.5473	42.0	252	1.5076	0.1778
1.5473	43.0	258	1.5076	0.1778
1.5095	44.0	264	1.5076	0.1778
1.495	45.0	270	1.5076	0.1778
1.495	46.0	276	1.5076	0.1778
1.5118	47.0	282	1.5076	0.1778
1.5118	48.0	288	1.5076	0.1778
1.493	49.0	294	1.5076	0.1778
1.528	50.0	300	1.5076	0.1778

Framework versions

• Transformers 4.35.0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1