NVIDIA Deep Learning Examples
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Model
NVIDIA Deep Learning Examples
GPUNet-P1 pretrained weights (PyTorch, AMP, ImageNet)GPUNet-P1 ImageNet pretrained weights
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1 Version
21.12.0_ampSelected05/10/2022 8:04 PM UTC152.84 MBAccuracy: 0450 EpochsBatch Size: 256GPU: V100Copied!
21.12.0_ampSelected
05/10/2022 8:04 PM UTC152.84 MBAccuracy: 0450 EpochsBatch Size: 256GPU: V100
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architecture
| Key | Value |
|---|---|
| type | prunet_1 |
performance
| Key | Value |
|---|---|
| val_top1 | 81.29 |
| val_top5 | 95.554 |
training
| Key | Value |
|---|---|
| aa | rand-m9-mstd0.5 |
| batch_size | 256 |
| amp | True |
| decay_epochs | 2.4 |
| lr | 0.08 |
| crop_pct | 0.875 |
| model | prunet_1 |
| img_size | 224 |
| epochs | 450 |
| decay_rate | 0.97 |
| model_ema | True |
| model_ema_decay | 0.9999 |