| !!python/object/apply:collections.OrderedDict | |
| - - - batch_size | |
| - 64 | |
| - - clip_range | |
| - 0.1 | |
| - - ent_coef | |
| - 0.000401762 | |
| - - gae_lambda | |
| - 0.92 | |
| - - gamma | |
| - 0.98 | |
| - - learning_rate | |
| - 2.0633e-05 | |
| - - max_grad_norm | |
| - 0.8 | |
| - - n_envs | |
| - 1 | |
| - - n_epochs | |
| - 20 | |
| - - n_steps | |
| - 512 | |
| - - n_timesteps | |
| - 1000000.0 | |
| - - normalize | |
| - '{''norm_obs'': True, ''norm_reward'': False}' | |
| - - policy | |
| - MlpPolicy | |
| - - policy_kwargs | |
| - dict(log_std_init=-2, ortho_init=False, activation_fn=nn.ReLU, net_arch=dict(pi=[256, | |
| 256], vf=[256, 256]) ) | |
| - - vf_coef | |
| - 0.58096 | |