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| # | |
| # number of samples in each train loop. -1 for all, otherwise a number like 50, 100, 300 | |
| n_stocks = 50 | |
| # model training epochs on the current stock sample in a training loop | |
| n_epochs = 20 | |
| # number of epochs patience without validation loss progress | |
| n_epochs_patience=3 | |
| # the earliest date to gather stock market data | |
| train_date_start='1991-01-01' | |
| # number of outer training loops for train task | |
| n_outer_train_loop=1000 | |
| # file name with stock tickers to work with in data/data-3rd-party dir | |
| stocks_train_list= "IBD50.csv" | |
| # "all_stocks.csv" | |
| # "IBD250.csv" | |
| # "IBD50.csv" | |
| logging_dir="tmp" | |
| # Number of trials to run hyperparam search with Optuna | |
| n_optuna_trials=50 | |
| # Hugging Face repo id prefix to upload/download model and data to/from | |
| repo_id = "ivelin/canswim" | |
| # main dir for data storage | |
| data_dir="data" | |
| # subdir for 3rd party data storage | |
| data_3rd_party="data-3rd-party" | |