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ViT-B-32-Cars – AI Model by dobrien | AlphaNeural AI
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ViT-B-32-Cars
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Dataset: Cars
Dataset Location: tanganke/stanford_cars
Test-Set Accuracy: 0.7970153093338013
Test-Set Loss: 0.7825230360031128
Training Hyperparameters:
Seed: 599121577
Device: cuda
Machine: L40S
Number of Devices: 1
Precision: Float32
Gradient Norm Clip Value: 10.0
Accumulate Gradient Batches: 1
Batch Size: 32
Loss: Cross Entropy
Epochs: 35
Optimizer: AdamW
Learning Rate: 1e-5
Weight Decay: 0.1
Scheduler: CosineAnnealingLR
Train Split Percent: 90%
Validation Split Percent: 10%
Test Split Percent: 100%
