hushem_40x_deit_base_sgd_0001_fold2

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

• Loss: 1.2543
• Accuracy: 0.3333

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
1.3992	1.0	215	1.3998	0.2667
1.3515	2.0	430	1.3921	0.3111
1.3529	3.0	645	1.3851	0.3111
1.3241	4.0	860	1.3787	0.3111
1.3174	5.0	1075	1.3730	0.3333
1.331	6.0	1290	1.3675	0.3333
1.3242	7.0	1505	1.3623	0.3333
1.2565	8.0	1720	1.3574	0.3111
1.2719	9.0	1935	1.3525	0.3333
1.2647	10.0	2150	1.3477	0.3333
1.2293	11.0	2365	1.3430	0.3556
1.1981	12.0	2580	1.3386	0.3556
1.2258	13.0	2795	1.3342	0.3556
1.1901	14.0	3010	1.3299	0.3111
1.1988	15.0	3225	1.3257	0.3333
1.2048	16.0	3440	1.3214	0.3333
1.1848	17.0	3655	1.3173	0.3333
1.1799	18.0	3870	1.3134	0.3333
1.1629	19.0	4085	1.3095	0.3333
1.1482	20.0	4300	1.3058	0.3333
1.1478	21.0	4515	1.3022	0.3333
1.1472	22.0	4730	1.2988	0.3333
1.1143	23.0	4945	1.2955	0.3333
1.1122	24.0	5160	1.2923	0.3333
1.1	25.0	5375	1.2893	0.3111
1.1089	26.0	5590	1.2864	0.3111
1.1001	27.0	5805	1.2836	0.3333
1.0858	28.0	6020	1.2810	0.3333
1.093	29.0	6235	1.2786	0.3333
1.081	30.0	6450	1.2761	0.3333
1.0426	31.0	6665	1.2739	0.3333
1.0757	32.0	6880	1.2718	0.3333
1.0524	33.0	7095	1.2698	0.3333
1.0725	34.0	7310	1.2680	0.3333
1.055	35.0	7525	1.2662	0.3333
1.0308	36.0	7740	1.2646	0.3333
1.0978	37.0	7955	1.2631	0.3333
1.0264	38.0	8170	1.2617	0.3333
1.0508	39.0	8385	1.2604	0.3333
1.0208	40.0	8600	1.2593	0.3333
1.0505	41.0	8815	1.2583	0.3333
1.0147	42.0	9030	1.2574	0.3333
1.0355	43.0	9245	1.2566	0.3333
1.0064	44.0	9460	1.2559	0.3333
1.019	45.0	9675	1.2554	0.3333
1.0292	46.0	9890	1.2549	0.3333
1.0584	47.0	10105	1.2546	0.3333
1.0425	48.0	10320	1.2544	0.3333
1.0211	49.0	10535	1.2543	0.3333
1.0221	50.0	10750	1.2543	0.3333

Framework versions

• Transformers 4.32.1
• Pytorch 2.1.0+cu121
• Datasets 2.12.0
• Tokenizers 0.13.2