hushem_1x_deit_small_adamax_00001_fold2

This model is a fine-tuned version of facebook/deit-small-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 1.3101
• Accuracy: 0.6222

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	1.3638	0.3556
1.331	2.0	12	1.3133	0.4222
1.331	3.0	18	1.2851	0.4222
1.0997	4.0	24	1.2715	0.4
0.9418	5.0	30	1.2498	0.4444
0.9418	6.0	36	1.2371	0.5111
0.7701	7.0	42	1.2279	0.5111
0.7701	8.0	48	1.2223	0.5556
0.6624	9.0	54	1.2136	0.5333
0.5468	10.0	60	1.2047	0.5111
0.5468	11.0	66	1.2129	0.5333
0.4638	12.0	72	1.2131	0.5556
0.4638	13.0	78	1.2055	0.5778
0.375	14.0	84	1.2059	0.5778
0.3096	15.0	90	1.2025	0.5778
0.3096	16.0	96	1.2062	0.5778
0.2535	17.0	102	1.2103	0.6
0.2535	18.0	108	1.2313	0.5778
0.2168	19.0	114	1.2293	0.5778
0.1735	20.0	120	1.2169	0.6222
0.1735	21.0	126	1.2306	0.6222
0.1492	22.0	132	1.2370	0.6222
0.1492	23.0	138	1.2467	0.6222
0.1264	24.0	144	1.2411	0.6222
0.1012	25.0	150	1.2438	0.6222
0.1012	26.0	156	1.2523	0.6222
0.0887	27.0	162	1.2537	0.6
0.0887	28.0	168	1.2661	0.6222
0.0734	29.0	174	1.2715	0.6222
0.0647	30.0	180	1.2745	0.6
0.0647	31.0	186	1.2817	0.6222
0.0577	32.0	192	1.2861	0.6222
0.0577	33.0	198	1.2908	0.6222
0.0525	34.0	204	1.2935	0.6222
0.048	35.0	210	1.2969	0.6222
0.048	36.0	216	1.2990	0.6
0.0443	37.0	222	1.3015	0.6
0.0443	38.0	228	1.3052	0.6222
0.0404	39.0	234	1.3082	0.6222
0.0394	40.0	240	1.3089	0.6222
0.0394	41.0	246	1.3101	0.6222
0.0387	42.0	252	1.3101	0.6222
0.0387	43.0	258	1.3101	0.6222
0.0369	44.0	264	1.3101	0.6222
0.0381	45.0	270	1.3101	0.6222
0.0381	46.0	276	1.3101	0.6222
0.0382	47.0	282	1.3101	0.6222
0.0382	48.0	288	1.3101	0.6222
0.037	49.0	294	1.3101	0.6222
0.0386	50.0	300	1.3101	0.6222

Framework versions

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