hushem_1x_deit_tiny_sgd_0001_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: 1.5555
• 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: 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	1.6995	0.2791
1.7242	2.0	12	1.6902	0.2791
1.7242	3.0	18	1.6819	0.2791
1.6909	4.0	24	1.6741	0.2791
1.6461	5.0	30	1.6664	0.2791
1.6461	6.0	36	1.6587	0.2791
1.6466	7.0	42	1.6518	0.2791
1.6466	8.0	48	1.6448	0.2791
1.6495	9.0	54	1.6384	0.2791
1.6495	10.0	60	1.6323	0.2791
1.6495	11.0	66	1.6267	0.2791
1.6244	12.0	72	1.6213	0.2791
1.6244	13.0	78	1.6166	0.2791
1.593	14.0	84	1.6117	0.2791
1.6183	15.0	90	1.6071	0.2791
1.6183	16.0	96	1.6026	0.2791
1.6105	17.0	102	1.5985	0.2558
1.6105	18.0	108	1.5946	0.2558
1.5599	19.0	114	1.5912	0.2558
1.5756	20.0	120	1.5878	0.2558
1.5756	21.0	126	1.5845	0.2558
1.5692	22.0	132	1.5817	0.2558
1.5692	23.0	138	1.5789	0.2558
1.544	24.0	144	1.5763	0.2558
1.548	25.0	150	1.5738	0.2558
1.548	26.0	156	1.5716	0.2791
1.549	27.0	162	1.5695	0.2791
1.549	28.0	168	1.5675	0.2791
1.5593	29.0	174	1.5658	0.2791
1.528	30.0	180	1.5641	0.2791
1.528	31.0	186	1.5627	0.2791
1.5394	32.0	192	1.5615	0.2791
1.5394	33.0	198	1.5603	0.2791
1.4822	34.0	204	1.5592	0.2791
1.5618	35.0	210	1.5583	0.2791
1.5618	36.0	216	1.5575	0.2791
1.5279	37.0	222	1.5568	0.2791
1.5279	38.0	228	1.5563	0.2791
1.5233	39.0	234	1.5559	0.2791
1.5255	40.0	240	1.5556	0.2791
1.5255	41.0	246	1.5555	0.2791
1.5147	42.0	252	1.5555	0.2791
1.5147	43.0	258	1.5555	0.2791
1.5048	44.0	264	1.5555	0.2791
1.5464	45.0	270	1.5555	0.2791
1.5464	46.0	276	1.5555	0.2791
1.5243	47.0	282	1.5555	0.2791
1.5243	48.0	288	1.5555	0.2791
1.5049	49.0	294	1.5555	0.2791
1.5545	50.0	300	1.5555	0.2791

Framework versions

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