To train the model, run
$ python main.py --train --model_name <name of your model>
This trains a model with default parameters:
- Training epochs:
--epoch 150
- Mini batch size:
--batch_size 64
- GRU units:
--rnn 20
- Length of sequence for training:
--len 40
- Dropout rate:
--drop 0.001
To test on a specific sequence in the test data and outputting a prediction sequence of your choice,
you can use the --test_sample
and --test_steps
flags.
For instance, running the command
$ python main.py --test --model_name <name of your model> --test_sample 0:30 --test_steps 10
will feed the model preprocessed samples from row index 0 to 30 as an input sequence and the it will predict the values that are 10 steps ahead.
--test_sample
is usually used with --plot_sample
to visualize the predicted samples against the target values.
$ python main.py --test --model_name <name of your model> --test_sample 0:30 --test_steps 10 --plot_sample