hushem_1x_deit_tiny_sgd_001_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: 1.2764
• Accuracy: 0.3659

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: 0.001
• 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	1.6481	0.2439
1.6453	2.0	12	1.5595	0.2439
1.6453	3.0	18	1.4979	0.2683
1.5144	4.0	24	1.4546	0.2683
1.4538	5.0	30	1.4262	0.2927
1.4538	6.0	36	1.4074	0.2683
1.3994	7.0	42	1.3954	0.2683
1.3994	8.0	48	1.3847	0.2683
1.3731	9.0	54	1.3749	0.2683
1.3564	10.0	60	1.3671	0.2927
1.3564	11.0	66	1.3612	0.3415
1.3402	12.0	72	1.3541	0.3659
1.3402	13.0	78	1.3472	0.3171
1.2912	14.0	84	1.3416	0.3171
1.304	15.0	90	1.3360	0.2927
1.304	16.0	96	1.3318	0.3171
1.267	17.0	102	1.3278	0.3171
1.267	18.0	108	1.3225	0.3171
1.2687	19.0	114	1.3187	0.3415
1.2447	20.0	120	1.3147	0.3415
1.2447	21.0	126	1.3131	0.3171
1.2262	22.0	132	1.3086	0.3171
1.2262	23.0	138	1.3054	0.3171
1.2132	24.0	144	1.3031	0.3171
1.2231	25.0	150	1.3007	0.3171
1.2231	26.0	156	1.2974	0.3171
1.1895	27.0	162	1.2937	0.3171
1.1895	28.0	168	1.2903	0.3415
1.2062	29.0	174	1.2886	0.3415
1.1907	30.0	180	1.2864	0.3415
1.1907	31.0	186	1.2852	0.3415
1.1836	32.0	192	1.2832	0.3415
1.1836	33.0	198	1.2819	0.3415
1.1632	34.0	204	1.2802	0.3415
1.1553	35.0	210	1.2792	0.3659
1.1553	36.0	216	1.2784	0.3659
1.1703	37.0	222	1.2777	0.3659
1.1703	38.0	228	1.2771	0.3659
1.1625	39.0	234	1.2768	0.3659
1.1523	40.0	240	1.2765	0.3659
1.1523	41.0	246	1.2764	0.3659
1.1617	42.0	252	1.2764	0.3659
1.1617	43.0	258	1.2764	0.3659
1.1427	44.0	264	1.2764	0.3659
1.1631	45.0	270	1.2764	0.3659
1.1631	46.0	276	1.2764	0.3659
1.162	47.0	282	1.2764	0.3659
1.162	48.0	288	1.2764	0.3659
1.1542	49.0	294	1.2764	0.3659
1.1633	50.0	300	1.2764	0.3659

Framework versions

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