vit-base-patch16-224-Trial007-YEL_STEM2

sbaner24/vit-base-patch16-224-Trial007-YEL_STEM2

vit-base-patch16-224-Trial007-YEL_STEM2 is a image classification model from sbaner24. 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: Jun 20, 2023
Updated: Mar 5, 2024
SHA: 56d8f617

Datasets

imagefolder

Model card

From the Hugging Face model README

vit-base-patch16-224-Trial007-YEL_STEM2

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

Loss: 0.1172
Accuracy: 0.9815

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: 5e-05
train_batch_size: 60
eval_batch_size: 60
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 240
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
0.6676	0.89	2	0.6180	0.7222
0.5805	1.78	4	0.5004	0.7593
0.5012	2.67	6	0.3783	0.9630
0.2794	4.0	9	0.2285	0.9630
0.2695	4.89	11	0.2551	0.8889
0.2782	5.78	13	0.1079	0.9630
0.2131	6.67	15	0.1205	0.9630
0.1537	8.0	18	0.1861	0.9630
0.1739	8.89	20	0.1172	0.9815
0.1059	9.78	22	0.1092	0.9815
0.146	10.67	24	0.1072	0.9815
0.088	12.0	27	0.1015	0.9815
0.1304	12.89	29	0.1151	0.9815
0.0924	13.78	31	0.1313	0.9815
0.091	14.67	33	0.1178	0.9815
0.0508	16.0	36	0.0971	0.9815
0.1004	16.89	38	0.1175	0.9815
0.1097	17.78	40	0.1423	0.9630
0.0758	18.67	42	0.1597	0.9630
0.0687	20.0	45	0.1205	0.9815
0.0513	20.89	47	0.1107	0.9815
0.0755	21.78	49	0.1150	0.9815
0.0897	22.67	51	0.1332	0.9630
0.0439	24.0	54	0.1263	0.9815
0.0607	24.89	56	0.1111	0.9815
0.0719	25.78	58	0.1004	0.9815
0.0599	26.67	60	0.1064	0.9815
0.0613	28.0	63	0.1355	0.9815
0.0689	28.89	65	0.1444	0.9815
0.0754	29.78	67	0.1398	0.9815
0.0835	30.67	69	0.1345	0.9815
0.0801	32.0	72	0.1348	0.9815
0.0701	32.89	74	0.1365	0.9815
0.0647	33.78	76	0.1348	0.9815
0.0982	34.67	78	0.1346	0.9815
0.0671	36.0	81	0.1378	0.9815
0.054	36.89	83	0.1371	0.9815
0.0735	37.78	85	0.1355	0.9815
0.0736	38.67	87	0.1349	0.9815
0.0287	40.0	90	0.1329	0.9815
0.0539	40.89	92	0.1322	0.9815
0.0483	41.78	94	0.1324	0.9815
0.083	42.67	96	0.1319	0.9815
0.0558	44.0	99	0.1319	0.9815
0.0752	44.44	100	0.1319	0.9815

Framework versions

Transformers 4.30.0.dev0
Pytorch 1.12.1
Datasets 2.12.0
Tokenizers 0.13.1

Task: Image Classification
Library: transformers
Type: vit
License: apache-2.0
Created: Jun 20, 2023
Updated: Mar 5, 2024