hushem_1x_deit_tiny_sgd_lr00001_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: 1.6574
• Accuracy: 0.2667

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	1.6633	0.2667
1.6088	2.0	12	1.6630	0.2667
1.6088	3.0	18	1.6627	0.2667
1.5763	4.0	24	1.6624	0.2667
1.6076	5.0	30	1.6621	0.2667
1.6076	6.0	36	1.6618	0.2667
1.5951	7.0	42	1.6616	0.2667
1.5951	8.0	48	1.6613	0.2667
1.5898	9.0	54	1.6611	0.2667
1.5905	10.0	60	1.6609	0.2667
1.5905	11.0	66	1.6606	0.2667
1.5785	12.0	72	1.6604	0.2667
1.5785	13.0	78	1.6602	0.2667
1.623	14.0	84	1.6600	0.2667
1.5698	15.0	90	1.6598	0.2667
1.5698	16.0	96	1.6596	0.2667
1.5831	17.0	102	1.6594	0.2667
1.5831	18.0	108	1.6593	0.2667
1.6234	19.0	114	1.6591	0.2667
1.605	20.0	120	1.6589	0.2667
1.605	21.0	126	1.6588	0.2667
1.6023	22.0	132	1.6586	0.2667
1.6023	23.0	138	1.6585	0.2667
1.5903	24.0	144	1.6584	0.2667
1.5877	25.0	150	1.6583	0.2667
1.5877	26.0	156	1.6582	0.2667
1.5697	27.0	162	1.6581	0.2667
1.5697	28.0	168	1.6580	0.2667
1.6252	29.0	174	1.6579	0.2667
1.6032	30.0	180	1.6578	0.2667
1.6032	31.0	186	1.6577	0.2667
1.6035	32.0	192	1.6577	0.2667
1.6035	33.0	198	1.6576	0.2667
1.5747	34.0	204	1.6575	0.2667
1.5966	35.0	210	1.6575	0.2667
1.5966	36.0	216	1.6575	0.2667
1.5685	37.0	222	1.6574	0.2667
1.5685	38.0	228	1.6574	0.2667
1.5973	39.0	234	1.6574	0.2667
1.5951	40.0	240	1.6574	0.2667
1.5951	41.0	246	1.6574	0.2667
1.5959	42.0	252	1.6574	0.2667
1.5959	43.0	258	1.6574	0.2667
1.6121	44.0	264	1.6574	0.2667
1.5823	45.0	270	1.6574	0.2667
1.5823	46.0	276	1.6574	0.2667
1.5911	47.0	282	1.6574	0.2667
1.5911	48.0	288	1.6574	0.2667
1.6171	49.0	294	1.6574	0.2667
1.5945	50.0	300	1.6574	0.2667

Framework versions

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