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Deci-AI
/
super-gradients
connected to https://github.com/Deci-AI/super-gradients.git

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imagenet_efficientnet_train_params.yaml 826 B
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  1. defaults:
    2. 

  2.   - default_train_params
    3. 

  3. 

  4. max_epochs: 550
    5. 

  5. lr_updates:
    6. 

  6.   _target_: numpy.arange
    7. 

  7.   start: 0
    8. 

  8.   stop: 500
    9. 

  9.   step: 3
    10. 

  10. 

  11. lr_mode: step
    12. 

  12. lr_decay_factor: 0.963
    13. 

  13. initial_lr: 0.032
    14. 

  14. optimizer: RMSpropTF
    15. 

  15. 

  16. optimizer_params:
    17. 

  17.   eps: 0.001
    18. 

  18.   weight_decay: 1e-5
    19. 

  19. 

  20. lr_warmup_epochs: 5
    21. 

  21. loss: cross_entropy
    22. 

  22. zero_weight_decay_on_bias_and_bn: True
    23. 

  23. ema: True
    24. 

  24. 

  25. loss_logging_items_names: [Loss]
    26. 

  26. metric_to_watch: Accuracy
    27. 

  27. greater_metric_to_watch_is_better: True
    28. 

  28. 

  29. train_metrics_list:                               # metrics for evaluation
    30. 

  30.   - _target_: super_gradients.training.metrics.Accuracy
    31. 

  31.   - _target_: super_gradients.training.metrics.Top5
    32. 

  32. 

  33. valid_metrics_list:                               # metrics for evaluation
    34. 

  34.   - _target_: super_gradients.training.metrics.Accuracy
    35. 

  35.   - _target_: super_gradients.training.metrics.Top5
    36. 

  36. 

  37. _convert_: all
    38.
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