Train-Augmentation-V2-swinv2-base – AI Model by ahmedesmail16 | AlphaNeural AI

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Train-Augmentation-V2-swinv2-base

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image-classification

generated_from_trainer

microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft

autotrain_compatible

endpoints_compatible

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Train-Augmentation-V2-swinv2-base

This model is a fine-tuned version of microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.9822
Accuracy: 0.8459

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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5894	0.99	109	0.7123	0.7481
0.2772	2.0	219	0.6394	0.7970
0.1863	3.0	329	0.7819	0.7669
0.0925	4.0	439	0.7062	0.8083
0.0461	4.99	548	0.8637	0.8120
0.0427	6.0	658	0.9080	0.7970
0.043	7.0	768	1.0747	0.8045
0.0074	8.0	878	0.9019	0.8421
0.0169	8.99	987	0.9099	0.8459
0.015	10.0	1097	0.9512	0.8647
0.0022	11.0	1207	1.0051	0.8609
0.0081	12.0	1317	1.0061	0.8308
0.0013	12.99	1426	0.9844	0.8534
0.0037	14.0	1536	0.9864	0.8459
0.0002	14.9	1635	0.9822	0.8459

Framework versions

Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.19.1
Tokenizers 0.15.2