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ultralytics 8.0.184 https://yolovision.ultralytics.com #YV23 (#5004)

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Glenn Jocher 2023-09-20 23:05:49 +02:00 • committed by GitHub
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4
docs/modes/train.md
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@ -189,7 +189,7 @@ Training settings for YOLO models refer to the various hyperparameters and confi
| `project` | `None` | project name |
| `name` | `None` | experiment name |
| `exist_ok` | `False` | whether to overwrite existing experiment |
| `pretrained` | `True` | (bool \| str) whether to use a pretrained model (bool) or a model to load weights from (str) |
| `pretrained` | `True` | (bool or str) whether to use a pretrained model (bool) or a model to load weights from (str) |
| `optimizer` | `'auto'` | optimizer to use, choices=[SGD, Adam, Adamax, AdamW, NAdam, RAdam, RMSProp, auto] |
| `verbose` | `False` | whether to print verbose output |
| `seed` | `0` | random seed for reproducibility |
@ -202,7 +202,7 @@ Training settings for YOLO models refer to the various hyperparameters and confi
| `amp` | `True` | Automatic Mixed Precision (AMP) training, choices=[True, False] |
| `fraction` | `1.0` | dataset fraction to train on (default is 1.0, all images in train set) |
| `profile` | `False` | profile ONNX and TensorRT speeds during training for loggers |
| `freeze` | `None` | (int \| list, optional) freeze first n layers, or freeze list of layer indices during training |
| `freeze` | `None` | (int or list, optional) freeze first n layers, or freeze list of layer indices during training |
| `lr0` | `0.01` | initial learning rate (i.e. SGD=1E-2, Adam=1E-3) |
| `lrf` | `0.01` | final learning rate (lr0 * lrf) |
| `momentum` | `0.937` | SGD momentum/Adam beta1 |

4
docs/usage/cfg.md
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@ -88,7 +88,7 @@ The training settings for YOLO models encompass various hyperparameters and conf
| `project` | `None` | project name |
| `name` | `None` | experiment name |
| `exist_ok` | `False` | whether to overwrite existing experiment |
| `pretrained` | `True` | (bool \| str) whether to use a pretrained model (bool) or a model to load weights from (str) |
| `pretrained` | `True` | (bool or str) whether to use a pretrained model (bool) or a model to load weights from (str) |
| `optimizer` | `'auto'` | optimizer to use, choices=[SGD, Adam, Adamax, AdamW, NAdam, RAdam, RMSProp, auto] |
| `verbose` | `False` | whether to print verbose output |
| `seed` | `0` | random seed for reproducibility |
@ -101,7 +101,7 @@ The training settings for YOLO models encompass various hyperparameters and conf
| `amp` | `True` | Automatic Mixed Precision (AMP) training, choices=[True, False] |
| `fraction` | `1.0` | dataset fraction to train on (default is 1.0, all images in train set) |
| `profile` | `False` | profile ONNX and TensorRT speeds during training for loggers |
| `freeze` | `None` | (int \| list, optional) freeze first n layers, or freeze list of layer indices during training |
| `freeze` | `None` | (int or list, optional) freeze first n layers, or freeze list of layer indices during training |
| `lr0` | `0.01` | initial learning rate (i.e. SGD=1E-2, Adam=1E-3) |
| `lrf` | `0.01` | final learning rate (lr0 * lrf) |
| `momentum` | `0.937` | SGD momentum/Adam beta1 |