hushem_1x_deit_tiny_sgd_lr0001_fold1

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: 1.5010
• Accuracy: 0.2444

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	1.5317	0.2667
1.5768	2.0	12	1.5295	0.2444
1.5768	3.0	18	1.5277	0.2444
1.5217	4.0	24	1.5259	0.2444
1.5806	5.0	30	1.5243	0.2444
1.5806	6.0	36	1.5226	0.2444
1.5608	7.0	42	1.5211	0.2444
1.5608	8.0	48	1.5198	0.2444
1.5538	9.0	54	1.5184	0.2444
1.5354	10.0	60	1.5172	0.2444
1.5354	11.0	66	1.5159	0.2444
1.5529	12.0	72	1.5148	0.2444
1.5529	13.0	78	1.5137	0.2444
1.5094	14.0	84	1.5127	0.2444
1.5228	15.0	90	1.5118	0.2444
1.5228	16.0	96	1.5108	0.2444
1.5295	17.0	102	1.5100	0.2444
1.5295	18.0	108	1.5092	0.2444
1.5298	19.0	114	1.5084	0.2444
1.5372	20.0	120	1.5077	0.2444
1.5372	21.0	126	1.5071	0.2444
1.5336	22.0	132	1.5065	0.2444
1.5336	23.0	138	1.5059	0.2444
1.5077	24.0	144	1.5053	0.2444
1.5022	25.0	150	1.5049	0.2444
1.5022	26.0	156	1.5044	0.2444
1.5158	27.0	162	1.5040	0.2444
1.5158	28.0	168	1.5036	0.2444
1.4961	29.0	174	1.5032	0.2444
1.5155	30.0	180	1.5029	0.2444
1.5155	31.0	186	1.5025	0.2444
1.5093	32.0	192	1.5022	0.2444
1.5093	33.0	198	1.5020	0.2444
1.4596	34.0	204	1.5017	0.2444
1.4894	35.0	210	1.5015	0.2444
1.4894	36.0	216	1.5014	0.2444
1.5058	37.0	222	1.5012	0.2444
1.5058	38.0	228	1.5011	0.2444
1.4675	39.0	234	1.5010	0.2444
1.4822	40.0	240	1.5010	0.2444
1.4822	41.0	246	1.5010	0.2444
1.5008	42.0	252	1.5010	0.2444
1.5008	43.0	258	1.5010	0.2444
1.5075	44.0	264	1.5010	0.2444
1.5338	45.0	270	1.5010	0.2444
1.5338	46.0	276	1.5010	0.2444
1.5016	47.0	282	1.5010	0.2444
1.5016	48.0	288	1.5010	0.2444
1.4777	49.0	294	1.5010	0.2444
1.4813	50.0	300	1.5010	0.2444

Framework versions

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