train-distillation.py [55:73]:
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    parser.add_argument("--train_path", type=str, default="vanilla_train")
    parser.add_argument("--num_classes", type=int, default=-1,
                        help="Number of subclasses to use")

    # training parameters
    parser.add_argument("--optimizer", type=str, default="sgd,lr=0.1-0.01-0.001,momentum=0.9,weight_decay=0.0001",
                        help="Optimizer (SGD / RMSprop / Adam, etc.)")
    parser.add_argument("--batch_size", type=int, default=256,
                        help="Number of sentences per batch")
    parser.add_argument("--epochs", type=int, default=90,
                        help="Number of epochs")
    parser.add_argument("--stopping_criterion", type=str, default="",
                        help="Stopping criterion, and number of non-increase before stopping the experiment")
    parser.add_argument("--validation_metrics", type=str, default="",
                        help="Validation metrics")
    parser.add_argument("--train_transform", choices=["random", "flip", "center"], default="random",
                        help="Transformation applied to training images")
    parser.add_argument("--seed", type=int, default=0,
                        help="Random seed")
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train-logistic.py [56:74]:
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    parser.add_argument("--train_path", type=str, default="vanilla_train")
    parser.add_argument("--num_classes", type=int, default=-1,
                        help="Number of subclasses to use")

    # training parameters
    parser.add_argument("--optimizer", type=str, default="sgd,lr=0.1-0.01-0.001,momentum=0.9,weight_decay=0.0001",
                        help="Optimizer (SGD / RMSprop / Adam, etc.)")
    parser.add_argument("--batch_size", type=int, default=256,
                        help="Number of sentences per batch")
    parser.add_argument("--epochs", type=int, default=90,
                        help="Number of epochs")
    parser.add_argument("--stopping_criterion", type=str, default="",
                        help="Stopping criterion, and number of non-increase before stopping the experiment")
    parser.add_argument("--validation_metrics", type=str, default="",
                        help="Validation metrics")
    parser.add_argument("--train_transform", choices=["random", "flip", "center"], default="random",
                        help="Transformation applied to training images")
    parser.add_argument("--seed", type=int, default=0,
                        help="Random seed")
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