hushem_1x_deit_small_sgd_001_fold1

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: 1.2536
• Accuracy: 0.4667

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	1.3733	0.3778
1.5546	2.0	12	1.3601	0.4
1.5546	3.0	18	1.3490	0.4222
1.5316	4.0	24	1.3414	0.4222
1.4864	5.0	30	1.3332	0.4222
1.4864	6.0	36	1.3258	0.4222
1.4723	7.0	42	1.3198	0.4222
1.4723	8.0	48	1.3148	0.4
1.4485	9.0	54	1.3096	0.4
1.4339	10.0	60	1.3042	0.4
1.4339	11.0	66	1.3005	0.4222
1.4182	12.0	72	1.2965	0.4222
1.4182	13.0	78	1.2931	0.4
1.3944	14.0	84	1.2902	0.4222
1.3955	15.0	90	1.2868	0.4444
1.3955	16.0	96	1.2841	0.4444
1.3685	17.0	102	1.2813	0.4444
1.3685	18.0	108	1.2791	0.4444
1.351	19.0	114	1.2769	0.4444
1.3583	20.0	120	1.2750	0.4667
1.3583	21.0	126	1.2734	0.4444
1.3432	22.0	132	1.2719	0.4444
1.3432	23.0	138	1.2696	0.4444
1.3309	24.0	144	1.2677	0.4444
1.3166	25.0	150	1.2667	0.4444
1.3166	26.0	156	1.2651	0.4667
1.3168	27.0	162	1.2639	0.4667
1.3168	28.0	168	1.2624	0.4667
1.3102	29.0	174	1.2615	0.4667
1.3034	30.0	180	1.2602	0.4667
1.3034	31.0	186	1.2590	0.4667
1.3106	32.0	192	1.2580	0.4667
1.3106	33.0	198	1.2570	0.4667
1.2903	34.0	204	1.2562	0.4667
1.2915	35.0	210	1.2554	0.4667
1.2915	36.0	216	1.2549	0.4667
1.2913	37.0	222	1.2546	0.4667
1.2913	38.0	228	1.2542	0.4667
1.2715	39.0	234	1.2539	0.4667
1.2929	40.0	240	1.2538	0.4667
1.2929	41.0	246	1.2537	0.4667
1.2815	42.0	252	1.2536	0.4667
1.2815	43.0	258	1.2536	0.4667
1.2834	44.0	264	1.2536	0.4667
1.2687	45.0	270	1.2536	0.4667
1.2687	46.0	276	1.2536	0.4667
1.2845	47.0	282	1.2536	0.4667
1.2845	48.0	288	1.2536	0.4667
1.2639	49.0	294	1.2536	0.4667
1.2911	50.0	300	1.2536	0.4667

Framework versions

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