hushem_40x_deit_base_sgd_0001_fold2

hkivancoral/hushem_40x_deit_base_sgd_0001_fold2

hushem_40x_deit_base_sgd_0001_fold2 is a image classification model from hkivancoral. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Image Classification
Library: transformers
License: apache-2.0
Model type: vit
Access: Public
Created: Dec 24, 2023
Updated: Dec 24, 2023
SHA: d4d54dc8

Base models

facebook/deit-base-patch16-224

Datasets

imagefolder

Model card

From the Hugging Face model README

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

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Dec 24, 2023
Updated: Dec 24, 2023