[20:54:28] ============================================================
[20:54:28] Exp 21: generated_road + generated_track, warm-started, v4 reward
[20:54:28]   Warm start: /home/paulh/projects/donkeycar-rl-autoresearch/agent/models/champion/model.zip
[20:54:28]   Sim 1: localhost:9091 -> generated_road
[20:54:28]   Sim 2: localhost:9093 -> generated_track
[20:54:28]   throttle_min=0.2, lr=0.000225, total=150,000
[20:54:28]   Checkpoints: every 10,000 steps
[20:54:28] ============================================================
[20:54:28] Creating DummyVecEnv with the two road tracks...
starting DonkeyGym env
Setting default: start_delay 5.0
Setting default: max_cte 8.0
Setting default: frame_skip 1
Setting default: cam_resolution (120, 160, 3)
Setting default: log_level 20
Setting default: steer_limit 1.0
Setting default: throttle_min 0.0
Setting default: throttle_max 1.0
loading scene generated_road
starting DonkeyGym env
Setting default: start_delay 5.0
Setting default: max_cte 8.0
Setting default: frame_skip 1
Setting default: cam_resolution (120, 160, 3)
Setting default: log_level 20
Setting default: steer_limit 1.0
Setting default: throttle_min 0.0
Setting default: throttle_max 1.0
loading scene generated_track
[20:54:30]   VecEnv num_envs=2, obs=(3, 120, 160)
[20:54:35] Warm-start model attached. Starting training...
---------------------------------
| rollout/           |          |
|    ep_len_mean     | 118      |
|    ep_rew_mean     | 102      |
| time/              |          |
|    fps             | 25       |
|    iterations      | 1        |
|    time_elapsed    | 162      |
|    total_timesteps | 18432    |
---------------------------------
----------------------------------------
| rollout/                |            |
|    ep_len_mean          | 118        |
|    ep_rew_mean          | 102        |
| time/                   |            |
|    fps                  | 17         |
|    iterations           | 2          |
|    time_elapsed         | 461        |
|    total_timesteps      | 22528      |
| train/                  |            |
|    approx_kl            | 0.02005615 |
|    clip_fraction        | 0.244      |
|    clip_range           | 0.2        |
|    entropy_loss         | -2.79      |
|    explained_variance   | -1.26      |
|    learning_rate        | 0.000225   |
|    loss                 | 21.8       |
|    n_updates            | 80         |
|    policy_gradient_loss | 0.0144     |
|    std                  | 0.979      |
|    value_loss           | 54.3       |
----------------------------------------