hushem_5x_deit_small_rms_0001_fold1

hkivancoral/hushem_5x_deit_small_rms_0001_fold1

hushem_5x_deit_small_rms_0001_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 19, 2023
Updated: Nov 20, 2023
SHA: fa382ae4

Base models

facebook/deit-small-patch16-224

Datasets

imagefolder

Model card

From the Hugging Face model README

hushem_5x_deit_small_rms_0001_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: 1.0120
Accuracy: 0.8444

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: 1e-05
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
0.7286	1.0	27	0.7253	0.7333
0.1535	2.0	54	0.7112	0.7333
0.0294	3.0	81	0.7268	0.7333
0.0088	4.0	108	0.6613	0.7778
0.002	5.0	135	0.6035	0.8
0.0011	6.0	162	0.5742	0.8444
0.0009	7.0	189	0.5650	0.8222
0.0006	8.0	216	0.5900	0.8444
0.0005	9.0	243	0.6288	0.8444
0.0004	10.0	270	0.6359	0.8444
0.0003	11.0	297	0.6555	0.8444
0.0003	12.0	324	0.6530	0.8444
0.0002	13.0	351	0.6624	0.8444
0.0002	14.0	378	0.6755	0.8444
0.0002	15.0	405	0.7042	0.8444
0.0002	16.0	432	0.7026	0.8444
0.0001	17.0	459	0.7218	0.8444
0.0001	18.0	486	0.7361	0.8444
0.0001	19.0	513	0.7477	0.8444
0.0001	20.0	540	0.7601	0.8444
0.0001	21.0	567	0.7574	0.8444
0.0001	22.0	594	0.7945	0.8444
0.0001	23.0	621	0.8035	0.8444
0.0001	24.0	648	0.8071	0.8444
0.0001	25.0	675	0.8201	0.8444
0.0	26.0	702	0.8263	0.8444
0.0	27.0	729	0.8414	0.8444
0.0	28.0	756	0.8501	0.8444
0.0	29.0	783	0.8628	0.8444
0.0	30.0	810	0.8618	0.8444
0.0	31.0	837	0.8808	0.8444
0.0	32.0	864	0.8998	0.8444
0.0	33.0	891	0.9078	0.8444
0.0	34.0	918	0.9219	0.8444
0.0	35.0	945	0.9258	0.8444
0.0	36.0	972	0.9286	0.8444
0.0	37.0	999	0.9396	0.8444
0.0	38.0	1026	0.9562	0.8444
0.0	39.0	1053	0.9622	0.8444
0.0	40.0	1080	0.9723	0.8444
0.0	41.0	1107	0.9820	0.8444
0.0	42.0	1134	0.9901	0.8444
0.0	43.0	1161	0.9932	0.8444
0.0	44.0	1188	0.9995	0.8444
0.0	45.0	1215	1.0030	0.8444
0.0	46.0	1242	1.0074	0.8444
0.0	47.0	1269	1.0103	0.8444
0.0	48.0	1296	1.0119	0.8444
0.0	49.0	1323	1.0120	0.8444
0.0	50.0	1350	1.0120	0.8444

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Nov 19, 2023
Updated: Nov 20, 2023