hushem_1x_deit_tiny_sgd_lr0001_fold2

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: 1.5853
• 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: 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	1.6380	0.1333
1.612	2.0	12	1.6350	0.1333
1.612	3.0	18	1.6320	0.1333
1.5793	4.0	24	1.6293	0.1333
1.6085	5.0	30	1.6268	0.1333
1.6085	6.0	36	1.6242	0.1333
1.5833	7.0	42	1.6217	0.1333
1.5833	8.0	48	1.6197	0.1333
1.5532	9.0	54	1.6175	0.1333
1.5785	10.0	60	1.6153	0.1333
1.5785	11.0	66	1.6132	0.1333
1.5506	12.0	72	1.6113	0.1333
1.5506	13.0	78	1.6095	0.1333
1.5868	14.0	84	1.6078	0.1333
1.532	15.0	90	1.6062	0.1333
1.532	16.0	96	1.6045	0.1333
1.5321	17.0	102	1.6029	0.1333
1.5321	18.0	108	1.6015	0.1333
1.5965	19.0	114	1.6001	0.1333
1.5428	20.0	120	1.5987	0.1333
1.5428	21.0	126	1.5975	0.1333
1.5622	22.0	132	1.5964	0.1333
1.5622	23.0	138	1.5951	0.1333
1.5259	24.0	144	1.5941	0.1333
1.5339	25.0	150	1.5932	0.1333
1.5339	26.0	156	1.5923	0.1333
1.5237	27.0	162	1.5914	0.1333
1.5237	28.0	168	1.5907	0.1333
1.5539	29.0	174	1.5899	0.1333
1.5487	30.0	180	1.5891	0.1333
1.5487	31.0	186	1.5885	0.1333
1.5317	32.0	192	1.5879	0.1333
1.5317	33.0	198	1.5874	0.1333
1.4989	34.0	204	1.5869	0.1333
1.5301	35.0	210	1.5865	0.1333
1.5301	36.0	216	1.5862	0.1333
1.5061	37.0	222	1.5859	0.1333
1.5061	38.0	228	1.5857	0.1333
1.5205	39.0	234	1.5855	0.1333
1.5267	40.0	240	1.5854	0.1333
1.5267	41.0	246	1.5854	0.1333
1.5211	42.0	252	1.5853	0.1333
1.5211	43.0	258	1.5853	0.1333
1.524	44.0	264	1.5853	0.1333
1.5163	45.0	270	1.5853	0.1333
1.5163	46.0	276	1.5853	0.1333
1.5253	47.0	282	1.5853	0.1333
1.5253	48.0	288	1.5853	0.1333
1.5384	49.0	294	1.5853	0.1333
1.5175	50.0	300	1.5853	0.1333

Framework versions

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