hushem_1x_deit_tiny_sgd_0001_fold5

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: 1.5523
• Accuracy: 0.2439

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	1.7547	0.2439
1.7078	2.0	12	1.7422	0.2439
1.7078	3.0	18	1.7303	0.2439
1.6827	4.0	24	1.7187	0.2439
1.6676	5.0	30	1.7076	0.2439
1.6676	6.0	36	1.6970	0.2439
1.6669	7.0	42	1.6882	0.2439
1.6669	8.0	48	1.6793	0.2439
1.5935	9.0	54	1.6701	0.2439
1.6316	10.0	60	1.6617	0.2439
1.6316	11.0	66	1.6538	0.2439
1.6324	12.0	72	1.6460	0.2439
1.6324	13.0	78	1.6387	0.2439
1.5842	14.0	84	1.6318	0.2439
1.5897	15.0	90	1.6256	0.2439
1.5897	16.0	96	1.6199	0.2439
1.5943	17.0	102	1.6144	0.2439
1.5943	18.0	108	1.6092	0.2195
1.5586	19.0	114	1.6040	0.2195
1.5924	20.0	120	1.5990	0.2195
1.5924	21.0	126	1.5945	0.2195
1.5676	22.0	132	1.5902	0.2195
1.5676	23.0	138	1.5862	0.2195
1.5352	24.0	144	1.5823	0.2195
1.5842	25.0	150	1.5786	0.2195
1.5842	26.0	156	1.5752	0.2195
1.5461	27.0	162	1.5723	0.2195
1.5461	28.0	168	1.5695	0.2195
1.551	29.0	174	1.5671	0.2439
1.5549	30.0	180	1.5649	0.2439
1.5549	31.0	186	1.5628	0.2439
1.5532	32.0	192	1.5610	0.2439
1.5532	33.0	198	1.5594	0.2439
1.5006	34.0	204	1.5578	0.2439
1.5134	35.0	210	1.5565	0.2439
1.5134	36.0	216	1.5553	0.2439
1.5386	37.0	222	1.5543	0.2439
1.5386	38.0	228	1.5536	0.2439
1.5372	39.0	234	1.5530	0.2439
1.528	40.0	240	1.5526	0.2439
1.528	41.0	246	1.5524	0.2439
1.5555	42.0	252	1.5523	0.2439
1.5555	43.0	258	1.5523	0.2439
1.509	44.0	264	1.5523	0.2439
1.5379	45.0	270	1.5523	0.2439
1.5379	46.0	276	1.5523	0.2439
1.5588	47.0	282	1.5523	0.2439
1.5588	48.0	288	1.5523	0.2439
1.509	49.0	294	1.5523	0.2439
1.5414	50.0	300	1.5523	0.2439

Framework versions

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