francescosabbarese commited on
Commit
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1 Parent(s): 5ec3be3

Upload folder using huggingface_hub

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Files changed (3) hide show
  1. README.md +1 -1
  2. replay.mp4 +2 -2
  3. sf_log.txt +145 -0
README.md CHANGED
@@ -15,7 +15,7 @@ model-index:
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  type: doom_health_gathering_supreme
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  metrics:
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  - type: mean_reward
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- value: 12.07 +/- 5.05
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  name: mean_reward
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  verified: false
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  ---
 
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  type: doom_health_gathering_supreme
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  metrics:
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  - type: mean_reward
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+ value: 10.25 +/- 4.97
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  name: mean_reward
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  verified: false
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  ---
replay.mp4 CHANGED
@@ -1,3 +1,3 @@
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  version https://git-lfs.github.com/spec/v1
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- oid sha256:e456ca48bb77120e2b62dbaf595592bcdf49923bf67d6d09f221ef8e3e3c73c9
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- size 23543324
 
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  version https://git-lfs.github.com/spec/v1
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+ oid sha256:73cade1b7c741fe9141d3bd76455c7715107bb078fb7600366c1a829064f2bba
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+ size 8751111
sf_log.txt CHANGED
@@ -2088,3 +2088,148 @@ vizdoom.vizdoom.SignalException: Signal SIGINT received. ViZDoom instance has be
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  [2025-02-27 20:51:49,459][00031] Avg episode rewards: #0: 30.366, true rewards: #0: 12.066
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  [2025-02-27 20:51:49,460][00031] Avg episode reward: 30.366, avg true_objective: 12.066
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  [2025-02-27 20:52:26,202][00031] Replay video saved to /kaggle/working/train_dir/default_experiment/replay.mp4!
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  [2025-02-27 20:51:49,459][00031] Avg episode rewards: #0: 30.366, true rewards: #0: 12.066
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  [2025-02-27 20:51:49,460][00031] Avg episode reward: 30.366, avg true_objective: 12.066
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  [2025-02-27 20:52:26,202][00031] Replay video saved to /kaggle/working/train_dir/default_experiment/replay.mp4!
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+ [2025-02-27 20:52:29,435][00031] The model has been pushed to https://huggingface.co/francescosabbarese/rl_course_vizdoom_health_gathering_supreme
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+ [2025-02-27 20:52:29,469][00031] Loading existing experiment configuration from /kaggle/working/train_dir/default_experiment/config.json
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+ [2025-02-27 20:52:29,469][00031] Overriding arg 'num_workers' with value 1 passed from command line
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+ [2025-02-27 20:52:29,470][00031] Adding new argument 'no_render'=True that is not in the saved config file!
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+ [2025-02-27 20:52:29,471][00031] Adding new argument 'save_video'=True that is not in the saved config file!
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+ [2025-02-27 20:52:29,472][00031] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
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+ [2025-02-27 20:52:29,473][00031] Adding new argument 'video_name'=None that is not in the saved config file!
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+ [2025-02-27 20:52:29,475][00031] Adding new argument 'max_num_frames'=100000 that is not in the saved config file!
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+ [2025-02-27 20:52:29,475][00031] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
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+ [2025-02-27 20:52:29,476][00031] Adding new argument 'push_to_hub'=True that is not in the saved config file!
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+ [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!
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+ [2025-02-27 20:52:29,478][00031] Adding new argument 'policy_index'=0 that is not in the saved config file!
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+ [2025-02-27 20:52:29,479][00031] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
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+ [2025-02-27 20:52:29,480][00031] Adding new argument 'train_script'=None that is not in the saved config file!
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+ [2025-02-27 20:52:29,481][00031] Adding new argument 'enjoy_script'=None that is not in the saved config file!
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+ [2025-02-27 20:52:29,482][00031] Using frameskip 1 and render_action_repeat=4 for evaluation
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+ [2025-02-27 20:52:29,505][00031] RunningMeanStd input shape: (3, 72, 128)
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+ [2025-02-27 20:52:29,506][00031] RunningMeanStd input shape: (1,)
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+ [2025-02-27 20:52:29,517][00031] ConvEncoder: input_channels=3
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+ [2025-02-27 20:52:29,557][00031] Conv encoder output size: 512
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+ [2025-02-27 20:52:29,558][00031] Policy head output size: 512
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+ [2025-02-27 20:52:29,579][00031] Loading state from checkpoint /kaggle/working/train_dir/default_experiment/checkpoint_p0/checkpoint_000001292_10584064.pth...
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+ [2025-02-27 20:52:30,035][00031] Num frames 100...
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+ [2025-02-27 20:52:30,159][00031] Num frames 200...
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+ [2025-02-27 20:52:30,276][00031] Num frames 300...
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+ [2025-02-27 20:52:30,391][00031] Num frames 400...
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+ [2025-02-27 20:52:30,507][00031] Num frames 500...
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+ [2025-02-27 20:52:30,626][00031] Num frames 600...
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+ [2025-02-27 20:52:30,743][00031] Num frames 700...
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+ [2025-02-27 20:52:30,861][00031] Num frames 800...
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+ [2025-02-27 20:52:30,984][00031] Num frames 900...
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+ [2025-02-27 20:52:31,109][00031] Num frames 1000...
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+ [2025-02-27 20:52:31,233][00031] Num frames 1100...
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+ [2025-02-27 20:52:31,357][00031] Num frames 1200...
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+ [2025-02-27 20:52:31,481][00031] Num frames 1300...
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+ [2025-02-27 20:52:31,603][00031] Num frames 1400...
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+ [2025-02-27 20:52:31,722][00031] Num frames 1500...
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+ [2025-02-27 20:52:31,843][00031] Num frames 1600...
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+ [2025-02-27 20:52:31,966][00031] Num frames 1700...
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+ [2025-02-27 20:52:32,088][00031] Num frames 1800...
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+ [2025-02-27 20:52:32,249][00031] Avg episode rewards: #0: 52.849, true rewards: #0: 18.850
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+ [2025-02-27 20:52:32,250][00031] Avg episode reward: 52.849, avg true_objective: 18.850
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+ [2025-02-27 20:52:32,268][00031] Num frames 1900...
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+ [2025-02-27 20:52:32,391][00031] Num frames 2000...
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+ [2025-02-27 20:52:32,513][00031] Num frames 2100...
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+ [2025-02-27 20:52:32,631][00031] Num frames 2200...
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+ [2025-02-27 20:52:32,744][00031] Avg episode rewards: #0: 30.250, true rewards: #0: 11.250
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+ [2025-02-27 20:52:32,745][00031] Avg episode reward: 30.250, avg true_objective: 11.250
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+ [2025-02-27 20:52:32,803][00031] Num frames 2300...
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+ [2025-02-27 20:52:32,917][00031] Num frames 2400...
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+ [2025-02-27 20:52:33,034][00031] Num frames 2500...
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+ [2025-02-27 20:52:33,388][00031] Num frames 2800...
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+ [2025-02-27 20:52:33,507][00031] Num frames 2900...
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+ [2025-02-27 20:52:33,661][00031] Avg episode rewards: #0: 24.953, true rewards: #0: 9.953
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+ [2025-02-27 20:52:33,662][00031] Avg episode reward: 24.953, avg true_objective: 9.953
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+ [2025-02-27 20:52:33,679][00031] Num frames 3000...
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+ [2025-02-27 20:52:33,793][00031] Num frames 3100...
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+ [2025-02-27 20:52:33,914][00031] Num frames 3200...
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+ [2025-02-27 20:52:34,033][00031] Num frames 3300...
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+ [2025-02-27 20:52:34,151][00031] Num frames 3400...
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+ [2025-02-27 20:52:34,265][00031] Num frames 3500...
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+ [2025-02-27 20:52:34,498][00031] Num frames 3700...
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+ [2025-02-27 20:52:34,615][00031] Num frames 3800...
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+ [2025-02-27 20:52:34,691][00031] Avg episode rewards: #0: 22.545, true rewards: #0: 9.545
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+ [2025-02-27 20:52:34,692][00031] Avg episode reward: 22.545, avg true_objective: 9.545
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+ [2025-02-27 20:52:34,785][00031] Num frames 3900...
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+ [2025-02-27 20:52:34,924][00031] Num frames 4000...
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+ [2025-02-27 20:52:35,371][00031] Num frames 4300...
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+ [2025-02-27 20:52:35,498][00031] Num frames 4400...
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+ [2025-02-27 20:52:35,676][00031] Avg episode rewards: #0: 20.780, true rewards: #0: 8.980
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+ [2025-02-27 20:52:35,677][00031] Avg episode reward: 20.780, avg true_objective: 8.980
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+ [2025-02-27 20:52:35,691][00031] Num frames 4500...
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+ [2025-02-27 20:52:36,692][00031] Num frames 5300...
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+ [2025-02-27 20:52:36,854][00031] Avg episode rewards: #0: 20.643, true rewards: #0: 8.977
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+ [2025-02-27 20:52:36,854][00031] Avg episode reward: 20.643, avg true_objective: 8.977
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+ [2025-02-27 20:52:36,871][00031] Num frames 5400...
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+ [2025-02-27 20:52:38,206][00031] Num frames 6500...
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+ [2025-02-27 20:52:38,367][00031] Avg episode rewards: #0: 21.559, true rewards: #0: 9.416
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+ [2025-02-27 20:52:38,368][00031] Avg episode reward: 21.559, avg true_objective: 9.416
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+ [2025-02-27 20:52:38,380][00031] Num frames 6600...
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+ [2025-02-27 20:52:39,269][00031] Avg episode rewards: #0: 20.736, true rewards: #0: 9.111
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+ [2025-02-27 20:52:39,270][00031] Avg episode reward: 20.736, avg true_objective: 9.111
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+ [2025-02-27 20:52:39,283][00031] Num frames 7300...
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+ [2025-02-27 20:52:41,767][00031] Avg episode rewards: #0: 24.734, true rewards: #0: 10.290
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+ [2025-02-27 20:52:41,768][00031] Avg episode reward: 24.734, avg true_objective: 10.290
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+ [2025-02-27 20:52:42,681][00031] Num frames 10000...
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+ [2025-02-27 20:52:42,926][00031] Num frames 10200...
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+ [2025-02-27 20:52:43,046][00031] Avg episode rewards: #0: 24.353, true rewards: #0: 10.253
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+ [2025-02-27 20:52:43,047][00031] Avg episode reward: 24.353, avg true_objective: 10.253
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+ [2025-02-27 20:53:00,256][00031] Replay video saved to /kaggle/working/train_dir/default_experiment/replay.mp4!