Config structure explainedΒΆ

  • cuda_devices: list of CUDA devices to use: one experiment on one CUDA device. cuda_devices=[0,1] means using zero-th and first devices.

  • config_name: name of config from configs folder with general settings: dataset, experiment setting (e.g. LC/ASM/PLASM), model checkpoints, hyperparameters etc.

  • config_path: path to config with general settings.

  • command: .py file to run. For AL experiments, use run_active_learning.py.

  • args: arguments to modify from a general config in the current experiment. acquisition_model.name=xlnet-base-cased means that _xlnet-base-cased_ will be used as an acquisition model.

  • seeds: random seeds to use. seeds=[4837, 23419] means that two separate experiments with the same settings (except for seed) will be run: one with seed == 4837, one with seed == 23419.