diff options
-rw-r--r-- | openbb_terminal/forecast/brnn_view.py | 2 | ||||
-rw-r--r-- | openbb_terminal/forecast/forecast_controller.py | 6 | ||||
-rw-r--r-- | openbb_terminal/forecast/nhits_model.py | 2 | ||||
-rw-r--r-- | openbb_terminal/forecast/nhits_view.py | 2 | ||||
-rw-r--r-- | openbb_terminal/forecast/tcn_model.py | 7 | ||||
-rw-r--r-- | openbb_terminal/forecast/tcn_view.py | 6 | ||||
-rw-r--r-- | openbb_terminal/forecast/trans_model.py | 3 | ||||
-rw-r--r-- | openbb_terminal/forecast/trans_view.py | 6 | ||||
-rw-r--r-- | website/content/terminal/reference/forecast/nhits.md | 6 |
9 files changed, 19 insertions, 21 deletions
diff --git a/openbb_terminal/forecast/brnn_view.py b/openbb_terminal/forecast/brnn_view.py index 21daa9a80ae..cff4d7fd05a 100644 --- a/openbb_terminal/forecast/brnn_view.py +++ b/openbb_terminal/forecast/brnn_view.py @@ -33,7 +33,7 @@ def display_brnn_forecast( batch_size: int = 32, n_epochs: int = 100, learning_rate: float = 1e-3, - model_save_name: str = "rnn_model", + model_save_name: str = "brnn_model", force_reset: bool = True, save_checkpoints: bool = True, export: str = "", diff --git a/openbb_terminal/forecast/forecast_controller.py b/openbb_terminal/forecast/forecast_controller.py index 448ebec0f06..cf183430c60 100644 --- a/openbb_terminal/forecast/forecast_controller.py +++ b/openbb_terminal/forecast/forecast_controller.py @@ -3032,7 +3032,7 @@ class ForecastController(BaseController): "--layer_widths", dest="layer_widths", type=check_positive, - default=3, + default=512, help="The number of neurons in each layer", ) parser.add_argument( @@ -3056,7 +3056,7 @@ class ForecastController(BaseController): "--max_pool_1d", action="store_true", dest="maxpool1d", - default=False, + default=True, help="Whether to use max_pool_1d or AvgPool1d", ) if other_args and "-" not in other_args[0][0]: @@ -3068,7 +3068,7 @@ class ForecastController(BaseController): target_dataset=True, n_days=True, force_reset=True, - model_save_name="tft_model", + model_save_name="nhits_model", train_split=True, dropout=0.1, input_chunk_length=True, diff --git a/openbb_terminal/forecast/nhits_model.py b/openbb_terminal/forecast/nhits_model.py index 84786465c55..8b3fa948832 100644 --- a/openbb_terminal/forecast/nhits_model.py +++ b/openbb_terminal/forecast/nhits_model.py @@ -40,7 +40,7 @@ def get_nhits_data( batch_size: int = 32, n_epochs: int = 100, learning_rate: float = 1e-3, - model_save_name: str = "brnn_model", + model_save_name: str = "nhits_model", force_reset: bool = True, save_checkpoints: bool = True, ) -> Tuple[ diff --git a/openbb_terminal/forecast/nhits_view.py b/openbb_terminal/forecast/nhits_view.py index d0c82250e6f..caf2f07bd98 100644 --- a/openbb_terminal/forecast/nhits_view.py +++ b/openbb_terminal/forecast/nhits_view.py @@ -39,7 +39,7 @@ def display_nhits_forecast( batch_size: int = 32, n_epochs: int = 100, learning_rate: float = 1e-3, - model_save_name: str = "rnn_model", + model_save_name: str = "nhits_model", force_reset: bool = True, save_checkpoints: bool = True, export: str = "", diff --git a/openbb_terminal/forecast/tcn_model.py b/openbb_terminal/forecast/tcn_model.py index ef1534aea49..9c0de7d2dbe 100644 --- a/openbb_terminal/forecast/tcn_model.py +++ b/openbb_terminal/forecast/tcn_model.py @@ -27,12 +27,12 @@ def get_tcn_data( input_chunk_length: int = 14, output_chunk_length: int = 5, dropout: float = 0.1, - num_filters: int = 6, + num_filters: int = 3, weight_norm: bool = True, dilation_base: int = 2, - n_epochs: int = 100, + n_epochs: int = 300, learning_rate: float = 1e-3, - batch_size: int = 800, + batch_size: int = 32, model_save_name: str = "tcn_model", force_reset: bool = True, save_checkpoints: bool = True, @@ -95,7 +95,6 @@ def get_tcn_data( Mean average precision error, Best TCN Model. """ - # TODO Check if torch GPU AVAILABLE use_scalers = True diff --git a/openbb_terminal/forecast/tcn_view.py b/openbb_terminal/forecast/tcn_view.py index 8b93028df33..793f35246ce 100644 --- a/openbb_terminal/forecast/tcn_view.py +++ b/openbb_terminal/forecast/tcn_view.py @@ -28,12 +28,12 @@ def display_tcn_forecast( input_chunk_length: int = 14, output_chunk_length: int = 5, dropout: float = 0.1, - num_filters: int = 6, + num_filters: int = 3, weight_norm: bool = True, dilation_base: int = 2, - n_epochs: int = 100, + n_epochs: int = 300, learning_rate: float = 1e-3, - batch_size: int = 800, + batch_size: int = 32, model_save_name: str = "tcn_model", force_reset: bool = True, save_checkpoints: bool = True, diff --git a/openbb_terminal/forecast/trans_model.py b/openbb_terminal/forecast/trans_model.py index ebdd621ae3a..dc94111571e 100644 --- a/openbb_terminal/forecast/trans_model.py +++ b/openbb_terminal/forecast/trans_model.py @@ -34,7 +34,7 @@ def get_trans_data( activation: str = "relu", dropout: float = 0.0, batch_size: int = 32, - n_epochs: int = 100, + n_epochs: int = 300, learning_rate: float = 1e-3, model_save_name: str = "trans_model", force_reset: bool = True, @@ -103,7 +103,6 @@ def get_trans_data( Mean average precision error, Best transformer Model. """ - # TODO Check if torch GPU AVAILABLE use_scalers = True diff --git a/openbb_terminal/forecast/trans_view.py b/openbb_terminal/forecast/trans_view.py index f59c615f8c7..5fde027f746 100644 --- a/openbb_terminal/forecast/trans_view.py +++ b/openbb_terminal/forecast/trans_view.py @@ -33,9 +33,9 @@ def display_trans_forecast( num_decoder_layers: int = 3, dim_feedforward: int = 512, activation: str = "relu", - dropout: float = 0.1, - batch_size: int = 16, - n_epochs: int = 100, + dropout: float = 0.0, + batch_size: int = 32, + n_epochs: int = 300, learning_rate: float = 1e-3, model_save_name: str = "trans_model", force_reset: bool = True, diff --git a/website/content/terminal/reference/forecast/nhits.md b/website/content/terminal/reference/forecast/nhits.md index adc4c134654..53b062ddbe4 100644 --- a/website/content/terminal/reference/forecast/nhits.md +++ b/website/content/terminal/reference/forecast/nhits.md @@ -22,9 +22,9 @@ nhits [--num-stacks NUM_STACKS] [--num-blocks NUM_BLOCKS] [--num-layers NUM_LAYE | num_stacks | The number of stacks that make up the model | 3 | True | None | | num_blocks | The number of blocks making up every stack | 1 | True | None | | num_layers | The number of fully connected layers | 2 | True | None | -| layer_widths | The number of neurons in each layer | 3 | True | None | +| layer_widths | The number of neurons in each layer | 512 | True | None | | activation | The desired activation | ReLU | True | ReLU, RReLU, PReLU, Softplus, Tanh, SELU, LeakyReLU, Sigmoid | -| maxpool1d | Whether to use max_pool_1d or AvgPool1d | False | True | None | +| maxpool1d | Whether to use max_pool_1d or AvgPool1d | True | True | None | | past_covariates | Past covariates(columns/features) in same dataset. Comma separated. | None | True | None | | all_past_covariates | Adds all rows as past covariates except for date and the target column. | False | True | None | | naive | Show the naive baseline for a model. | False | True | None | @@ -36,7 +36,7 @@ nhits [--num-stacks NUM_STACKS] [--num-blocks NUM_BLOCKS] [--num-layers NUM_LAYE | output_chunk_length | The length of the forecast of the model. | 5 | True | None | | force_reset | If set to True, any previously-existing model with the same name will be reset (all checkpoints will be discarded). | True | True | None | | save_checkpoints | Whether to automatically save the untrained model and checkpoints. | True | True | None | -| model_save_name | Name of the model to save. | tft_model | True | None | +| model_save_name | Name of the model to save. | nhits_model | True | None | | n_epochs | Number of epochs over which to train the model. | 300 | True | None | | dropout | Fraction of neurons affected by Dropout, from 0 to 1. | 0.1 | True | None | | batch_size | Number of time series (input and output) used in each training pass | 32 | True | None | |