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README.md

@@ -15,7 +15,7 @@ model-index:
       type: doom_health_gathering_supreme
     metrics:
     - type: mean_reward
-      value: 12.07 +/- 5.05
+      value: 10.25 +/- 4.97
       name: mean_reward
       verified: false
 ---

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e456ca48bb77120e2b62dbaf595592bcdf49923bf67d6d09f221ef8e3e3c73c9
-size 23543324
+oid sha256:73cade1b7c741fe9141d3bd76455c7715107bb078fb7600366c1a829064f2bba
+size 8751111

sf_log.txt

@@ -2088,3 +2088,148 @@ vizdoom.vizdoom.SignalException: Signal SIGINT received. ViZDoom instance has be
 [2025-02-27 20:51:49,459][00031] Avg episode rewards: #0: 30.366, true rewards: #0: 12.066
 [2025-02-27 20:51:49,460][00031] Avg episode reward: 30.366, avg true_objective: 12.066
 [2025-02-27 20:52:26,202][00031] Replay video saved to /kaggle/working/train_dir/default_experiment/replay.mp4!
+[2025-02-27 20:52:29,435][00031] The model has been pushed to https://huggingface.co/francescosabbarese/rl_course_vizdoom_health_gathering_supreme
+[2025-02-27 20:52:29,469][00031] Loading existing experiment configuration from /kaggle/working/train_dir/default_experiment/config.json
+[2025-02-27 20:52:29,469][00031] Overriding arg 'num_workers' with value 1 passed from command line
+[2025-02-27 20:52:29,470][00031] Adding new argument 'no_render'=True that is not in the saved config file!
+[2025-02-27 20:52:29,471][00031] Adding new argument 'save_video'=True that is not in the saved config file!
+[2025-02-27 20:52:29,472][00031] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
+[2025-02-27 20:52:29,473][00031] Adding new argument 'video_name'=None that is not in the saved config file!
+[2025-02-27 20:52:29,475][00031] Adding new argument 'max_num_frames'=100000 that is not in the saved config file!
+[2025-02-27 20:52:29,475][00031] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
+[2025-02-27 20:52:29,476][00031] Adding new argument 'push_to_hub'=True that is not in the saved config file!
+[2025-02-27 20:52:29,478][00031] Adding new argument 'hf_repository'='francescosabbarese/rl_course_vizdoom_health_gathering_supreme' that is not in the saved config file!
+[2025-02-27 20:52:29,478][00031] Adding new argument 'policy_index'=0 that is not in the saved config file!
+[2025-02-27 20:52:29,479][00031] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
+[2025-02-27 20:52:29,480][00031] Adding new argument 'train_script'=None that is not in the saved config file!
+[2025-02-27 20:52:29,481][00031] Adding new argument 'enjoy_script'=None that is not in the saved config file!
+[2025-02-27 20:52:29,482][00031] Using frameskip 1 and render_action_repeat=4 for evaluation
+[2025-02-27 20:52:29,505][00031] RunningMeanStd input shape: (3, 72, 128)
+[2025-02-27 20:52:29,506][00031] RunningMeanStd input shape: (1,)
+[2025-02-27 20:52:29,517][00031] ConvEncoder: input_channels=3
+[2025-02-27 20:52:29,557][00031] Conv encoder output size: 512
+[2025-02-27 20:52:29,558][00031] Policy head output size: 512
+[2025-02-27 20:52:29,579][00031] Loading state from checkpoint /kaggle/working/train_dir/default_experiment/checkpoint_p0/checkpoint_000001292_10584064.pth...
+[2025-02-27 20:52:30,035][00031] Num frames 100...
+[2025-02-27 20:52:30,159][00031] Num frames 200...
+[2025-02-27 20:52:30,276][00031] Num frames 300...
+[2025-02-27 20:52:30,391][00031] Num frames 400...
+[2025-02-27 20:52:30,507][00031] Num frames 500...
+[2025-02-27 20:52:30,626][00031] Num frames 600...
+[2025-02-27 20:52:30,743][00031] Num frames 700...
+[2025-02-27 20:52:30,861][00031] Num frames 800...
+[2025-02-27 20:52:30,984][00031] Num frames 900...
+[2025-02-27 20:52:31,109][00031] Num frames 1000...
+[2025-02-27 20:52:31,233][00031] Num frames 1100...
+[2025-02-27 20:52:31,357][00031] Num frames 1200...
+[2025-02-27 20:52:31,481][00031] Num frames 1300...
+[2025-02-27 20:52:31,603][00031] Num frames 1400...
+[2025-02-27 20:52:31,722][00031] Num frames 1500...
+[2025-02-27 20:52:31,843][00031] Num frames 1600...
+[2025-02-27 20:52:31,966][00031] Num frames 1700...
+[2025-02-27 20:52:32,088][00031] Num frames 1800...
+[2025-02-27 20:52:32,249][00031] Avg episode rewards: #0: 52.849, true rewards: #0: 18.850
+[2025-02-27 20:52:32,250][00031] Avg episode reward: 52.849, avg true_objective: 18.850
+[2025-02-27 20:52:32,268][00031] Num frames 1900...
+[2025-02-27 20:52:32,391][00031] Num frames 2000...
+[2025-02-27 20:52:32,513][00031] Num frames 2100...
+[2025-02-27 20:52:32,631][00031] Num frames 2200...
+[2025-02-27 20:52:32,744][00031] Avg episode rewards: #0: 30.250, true rewards: #0: 11.250
+[2025-02-27 20:52:32,745][00031] Avg episode reward: 30.250, avg true_objective: 11.250
+[2025-02-27 20:52:32,803][00031] Num frames 2300...
+[2025-02-27 20:52:32,917][00031] Num frames 2400...
+[2025-02-27 20:52:33,034][00031] Num frames 2500...
+[2025-02-27 20:52:33,156][00031] Num frames 2600...
+[2025-02-27 20:52:33,272][00031] Num frames 2700...
+[2025-02-27 20:52:33,388][00031] Num frames 2800...
+[2025-02-27 20:52:33,507][00031] Num frames 2900...
+[2025-02-27 20:52:33,661][00031] Avg episode rewards: #0: 24.953, true rewards: #0: 9.953
+[2025-02-27 20:52:33,662][00031] Avg episode reward: 24.953, avg true_objective: 9.953
+[2025-02-27 20:52:33,679][00031] Num frames 3000...
+[2025-02-27 20:52:33,793][00031] Num frames 3100...
+[2025-02-27 20:52:33,914][00031] Num frames 3200...
+[2025-02-27 20:52:34,033][00031] Num frames 3300...
+[2025-02-27 20:52:34,151][00031] Num frames 3400...
+[2025-02-27 20:52:34,265][00031] Num frames 3500...
+[2025-02-27 20:52:34,382][00031] Num frames 3600...
+[2025-02-27 20:52:34,498][00031] Num frames 3700...
+[2025-02-27 20:52:34,615][00031] Num frames 3800...
+[2025-02-27 20:52:34,691][00031] Avg episode rewards: #0: 22.545, true rewards: #0: 9.545
+[2025-02-27 20:52:34,692][00031] Avg episode reward: 22.545, avg true_objective: 9.545
+[2025-02-27 20:52:34,785][00031] Num frames 3900...
+[2025-02-27 20:52:34,924][00031] Num frames 4000...
+[2025-02-27 20:52:35,082][00031] Num frames 4100...
+[2025-02-27 20:52:35,222][00031] Num frames 4200...
+[2025-02-27 20:52:35,371][00031] Num frames 4300...
+[2025-02-27 20:52:35,498][00031] Num frames 4400...
+[2025-02-27 20:52:35,676][00031] Avg episode rewards: #0: 20.780, true rewards: #0: 8.980
+[2025-02-27 20:52:35,677][00031] Avg episode reward: 20.780, avg true_objective: 8.980
+[2025-02-27 20:52:35,691][00031] Num frames 4500...
+[2025-02-27 20:52:35,819][00031] Num frames 4600...
+[2025-02-27 20:52:35,949][00031] Num frames 4700...
+[2025-02-27 20:52:36,074][00031] Num frames 4800...
+[2025-02-27 20:52:36,200][00031] Num frames 4900...
+[2025-02-27 20:52:36,324][00031] Num frames 5000...
+[2025-02-27 20:52:36,440][00031] Num frames 5100...
+[2025-02-27 20:52:36,565][00031] Num frames 5200...
+[2025-02-27 20:52:36,692][00031] Num frames 5300...
+[2025-02-27 20:52:36,854][00031] Avg episode rewards: #0: 20.643, true rewards: #0: 8.977
+[2025-02-27 20:52:36,854][00031] Avg episode reward: 20.643, avg true_objective: 8.977
+[2025-02-27 20:52:36,871][00031] Num frames 5400...
+[2025-02-27 20:52:36,997][00031] Num frames 5500...
+[2025-02-27 20:52:37,124][00031] Num frames 5600...
+[2025-02-27 20:52:37,250][00031] Num frames 5700...
+[2025-02-27 20:52:37,377][00031] Num frames 5800...
+[2025-02-27 20:52:37,501][00031] Num frames 5900...
+[2025-02-27 20:52:37,619][00031] Num frames 6000...
+[2025-02-27 20:52:37,737][00031] Num frames 6100...
+[2025-02-27 20:52:37,854][00031] Num frames 6200...
+[2025-02-27 20:52:37,970][00031] Num frames 6300...
+[2025-02-27 20:52:38,086][00031] Num frames 6400...
+[2025-02-27 20:52:38,206][00031] Num frames 6500...
+[2025-02-27 20:52:38,367][00031] Avg episode rewards: #0: 21.559, true rewards: #0: 9.416
+[2025-02-27 20:52:38,368][00031] Avg episode reward: 21.559, avg true_objective: 9.416
+[2025-02-27 20:52:38,380][00031] Num frames 6600...
+[2025-02-27 20:52:38,499][00031] Num frames 6700...
+[2025-02-27 20:52:38,626][00031] Num frames 6800...
+[2025-02-27 20:52:38,750][00031] Num frames 6900...
+[2025-02-27 20:52:38,871][00031] Num frames 7000...
+[2025-02-27 20:52:38,987][00031] Num frames 7100...
+[2025-02-27 20:52:39,105][00031] Num frames 7200...
+[2025-02-27 20:52:39,269][00031] Avg episode rewards: #0: 20.736, true rewards: #0: 9.111
+[2025-02-27 20:52:39,270][00031] Avg episode reward: 20.736, avg true_objective: 9.111
+[2025-02-27 20:52:39,283][00031] Num frames 7300...
+[2025-02-27 20:52:39,404][00031] Num frames 7400...
+[2025-02-27 20:52:39,529][00031] Num frames 7500...
+[2025-02-27 20:52:39,653][00031] Num frames 7600...
+[2025-02-27 20:52:39,769][00031] Num frames 7700...
+[2025-02-27 20:52:39,891][00031] Num frames 7800...
+[2025-02-27 20:52:40,011][00031] Num frames 7900...
+[2025-02-27 20:52:40,138][00031] Num frames 8000...
+[2025-02-27 20:52:40,264][00031] Num frames 8100...
+[2025-02-27 20:52:40,391][00031] Num frames 8200...
+[2025-02-27 20:52:40,515][00031] Num frames 8300...
+[2025-02-27 20:52:40,641][00031] Num frames 8400...
+[2025-02-27 20:52:40,769][00031] Num frames 8500...
+[2025-02-27 20:52:40,897][00031] Num frames 8600...
+[2025-02-27 20:52:41,020][00031] Num frames 8700...
+[2025-02-27 20:52:41,143][00031] Num frames 8800...
+[2025-02-27 20:52:41,267][00031] Num frames 8900...
+[2025-02-27 20:52:41,391][00031] Num frames 9000...
+[2025-02-27 20:52:41,513][00031] Num frames 9100...
+[2025-02-27 20:52:41,635][00031] Num frames 9200...
+[2025-02-27 20:52:41,767][00031] Avg episode rewards: #0: 24.734, true rewards: #0: 10.290
+[2025-02-27 20:52:41,768][00031] Avg episode reward: 24.734, avg true_objective: 10.290
+[2025-02-27 20:52:41,815][00031] Num frames 9300...
+[2025-02-27 20:52:41,937][00031] Num frames 9400...
+[2025-02-27 20:52:42,063][00031] Num frames 9500...
+[2025-02-27 20:52:42,186][00031] Num frames 9600...
+[2025-02-27 20:52:42,311][00031] Num frames 9700...
+[2025-02-27 20:52:42,434][00031] Num frames 9800...
+[2025-02-27 20:52:42,558][00031] Num frames 9900...
+[2025-02-27 20:52:42,681][00031] Num frames 10000...
+[2025-02-27 20:52:42,803][00031] Num frames 10100...
+[2025-02-27 20:52:42,926][00031] Num frames 10200...
+[2025-02-27 20:52:43,046][00031] Avg episode rewards: #0: 24.353, true rewards: #0: 10.253
+[2025-02-27 20:52:43,047][00031] Avg episode reward: 24.353, avg true_objective: 10.253
+[2025-02-27 20:53:00,256][00031] Replay video saved to /kaggle/working/train_dir/default_experiment/replay.mp4!