run_supervised.sh

#parser.add_argument("dataset", choices=["SEED", "UCIHAR", "SEEDUC", "Cho2017", "DREAMER"],help="which dataset to use")
#parser.add_argument("embedding_dim", type=int, help="mumber of features in the latent representation")
#parser.add_argument("n_head_token_enc", type=int, help="number of heads of the token encoder")
#parser.add_argument("n_head_context_enc", type=int, help="number of heads of the context encoder")
#parser.add_argument("depth_context_enc", type=int, help="depth of the context encoder")
#
#parser.add_argument("lr", type=float, help="used learning rate for optimization")
#parser.add_argument("finetune_epochs", type=int, help="number of epochs for supervised fine-tuning")
#parser.add_argument("es_after_epochs", type=int, help="Number of Epochs without improvement in validation loss to stop the training after")

#parser.add_argument("train_val_split",  choices=["random", "subject"], help="whether to split the validation-set randomly or to perform leave one subject out validation")
#parser.add_argument("preprocessing",  choices=["None", "standardize", "normalize"], help="what preprocessing to apply to the inputs, e.g. normalization or standardization")


python main_supervised_cli.py "DREAMER" 14 7 7 4 1e-4 100 20 "random" "None" #DREAMER supervised v0
python main_supervised_cli.py "UCIHAR" 9 3 3 4 1e-4 100 20 "random" "None" #UCIHAR supervised v0
python main_supervised_cli.py "SEED" 62 31 31 4 1e-4 100 20 "random" "None" #SEED supervised v0