hushem_1x_deit_base_adamax_001_fold1

hkivancoral/hushem_1x_deit_base_adamax_001_fold1

hushem_1x_deit_base_adamax_001_fold1 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: Nov 15, 2023
Updated: Nov 15, 2023
SHA: 9c8d18ff

Base models

facebook/deit-base-patch16-224

Datasets

imagefolder

Model card

From the Hugging Face model README

hushem_1x_deit_base_adamax_001_fold1

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: 4.0186
Accuracy: 0.5333

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	1.5701	0.2444
1.7784	2.0	12	1.4475	0.2444
1.7784	3.0	18	1.5245	0.2444
1.3959	4.0	24	1.4708	0.4222
1.2593	5.0	30	1.4970	0.2889
1.2593	6.0	36	2.3855	0.2444
1.1884	7.0	42	1.0899	0.5333
1.1884	8.0	48	1.5303	0.3778
1.0528	9.0	54	1.8879	0.2667
0.9521	10.0	60	1.5051	0.3556
0.9521	11.0	66	1.7383	0.4222
0.832	12.0	72	1.4982	0.4667
0.832	13.0	78	2.2428	0.4222
0.6131	14.0	84	2.0924	0.4667
0.7375	15.0	90	1.9680	0.3778
0.7375	16.0	96	2.1272	0.4
0.3749	17.0	102	2.6064	0.4222
0.3749	18.0	108	3.2946	0.4
0.1952	19.0	114	3.4322	0.4
0.1436	20.0	120	3.6588	0.4222
0.1436	21.0	126	2.5255	0.4889
0.198	22.0	132	4.0901	0.3778
0.198	23.0	138	3.7265	0.4444
0.1826	24.0	144	2.5207	0.5333
0.0757	25.0	150	3.1947	0.4667
0.0757	26.0	156	2.8055	0.5333
0.0579	27.0	162	2.7690	0.5333
0.0579	28.0	168	3.0584	0.5333
0.0219	29.0	174	2.7699	0.6
0.0037	30.0	180	3.6076	0.5556
0.0037	31.0	186	4.1981	0.4667
0.0005	32.0	192	4.2123	0.5111
0.0005	33.0	198	4.1138	0.4889
0.0004	34.0	204	4.0577	0.5333
0.0002	35.0	210	4.0352	0.5333
0.0002	36.0	216	4.0255	0.5333
0.0002	37.0	222	4.0206	0.5333
0.0002	38.0	228	4.0191	0.5333
0.0001	39.0	234	4.0188	0.5333
0.0001	40.0	240	4.0186	0.5333
0.0001	41.0	246	4.0185	0.5333
0.0001	42.0	252	4.0186	0.5333
0.0001	43.0	258	4.0186	0.5333
0.0001	44.0	264	4.0186	0.5333
0.0001	45.0	270	4.0186	0.5333
0.0001	46.0	276	4.0186	0.5333
0.0001	47.0	282	4.0186	0.5333
0.0001	48.0	288	4.0186	0.5333
0.0001	49.0	294	4.0186	0.5333
0.0001	50.0	300	4.0186	0.5333

Framework versions

Transformers 4.35.1
Pytorch 2.1.0+cu118
Datasets 2.14.7
Tokenizers 0.14.1

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Nov 15, 2023
Updated: Nov 15, 2023