Train-Test-Augmentation-V3D-swinv2-base – AI Model by ahmedesmail16 | AlphaNeural AI

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Train-Test-Augmentation-V3D-swinv2-base

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image-classification

generated_from_trainer

microsoft/swinv2-base-patch4-window12-192-22k

autotrain_compatible

endpoints_compatible

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Train-Test-Augmentation-V3D-swinv2-base

This model is a fine-tuned version of microsoft/swinv2-base-patch4-window12-192-22k on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.7725
Accuracy: 0.8142

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.8252	0.9825	28	0.9390	0.7273
0.5282	2.0	57	0.6414	0.7804
0.2556	2.9825	85	0.6210	0.7815
0.1633	4.0	114	0.7030	0.8142
0.0869	4.9825	142	0.7398	0.7877
0.0524	6.0	171	0.8167	0.7962
0.0277	6.9825	199	0.6993	0.8176
0.0245	8.0	228	0.7444	0.8210
0.0232	8.9825	256	0.8129	0.8142
0.017	9.8246	280	0.7725	0.8142

Framework versions

Transformers 4.41.1
Pytorch 2.1.2
Datasets 2.19.1
Tokenizers 0.19.1