cycle_README.md

README

Running the Training Cycle

To run the training cycle, ensure that the following parameters are properly configured in the configuration file:

Configuration Instructions:

1. Seed Configuration:

   • Set the seed to ensure reproducibility.

2. Buffer Settings:

   • Define the following parameters:
     • buffer_size: Size of the buffer.
     • seed_size: Initial size of the buffer.
     • buffer_step_size: Increment size for the buffer at each step.

3. Training Data Path:

   • Provide the path to the processed training data. The data should be in .npz file format.

4. Use Model Predictions or Random Selection:

   • Indicate whether to use model prediction scores or select randomly using the use_buffer_predictions parameter.

5. Step Configuration:

   • Set the step_num to define the number of steps in the cycle.

6. Training Parameters:

   • Specify the following:
     • max_epoch: Maximum number of epochs to train each model.
     • gpu_device: GPU device to be used for training.

7. Model Configurations:

   • Provide config files for each model.
   • Each model's configuration file should include:
     • The model type and name.
     • Basic configurations required for the model.

Running the Cycle:

To execute the training cycle, use the following command:

Use cycle experiment config file

python -m force_field_models.train.cycle -tc cycle_readme_example.yaml