Upload folder using huggingface_hub

README.md

@@ -15,7 +15,7 @@ model-index:
       type: doom_health_gathering_supreme
     metrics:
     - type: mean_reward
-      value: 9.48 +/- 3.89
+      value: 12.07 +/- 5.05
       name: mean_reward
       verified: false
 ---

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:66918a96bf10ef1a90dc023f3fcb5d2d0ad2abfa462ef5d8eaf19e9366e50ba7
-size 17872303
+oid sha256:e456ca48bb77120e2b62dbaf595592bcdf49923bf67d6d09f221ef8e3e3c73c9
+size 23543324

sf_log.txt

@@ -1925,3 +1925,166 @@ vizdoom.vizdoom.SignalException: Signal SIGINT received. ViZDoom instance has be
 [2025-02-27 20:50:59,231][00031] Avg episode rewards: #0: 21.577, true rewards: #0: 9.477
 [2025-02-27 20:50:59,232][00031] Avg episode reward: 21.577, avg true_objective: 9.477
 [2025-02-27 20:51:28,387][00031] Replay video saved to /kaggle/working/train_dir/default_experiment/replay.mp4!
+[2025-02-27 20:51:33,964][00031] The model has been pushed to https://huggingface.co/francescosabbarese/rl_course_vizdoom_health_gathering_supreme
+[2025-02-27 20:51:33,987][00031] Loading existing experiment configuration from /kaggle/working/train_dir/default_experiment/config.json
+[2025-02-27 20:51:33,988][00031] Overriding arg 'num_workers' with value 1 passed from command line
+[2025-02-27 20:51:33,988][00031] Adding new argument 'no_render'=True that is not in the saved config file!
+[2025-02-27 20:51:33,989][00031] Adding new argument 'save_video'=True that is not in the saved config file!
+[2025-02-27 20:51:33,991][00031] Adding new argument 'video_frames'=1000000000.0 that is not in the saved config file!
+[2025-02-27 20:51:33,992][00031] Adding new argument 'video_name'=None that is not in the saved config file!
+[2025-02-27 20:51:33,992][00031] Adding new argument 'max_num_frames'=100000 that is not in the saved config file!
+[2025-02-27 20:51:33,994][00031] Adding new argument 'max_num_episodes'=10 that is not in the saved config file!
+[2025-02-27 20:51:33,994][00031] Adding new argument 'push_to_hub'=True that is not in the saved config file!
+[2025-02-27 20:51:33,995][00031] Adding new argument 'hf_repository'='francescosabbarese/rl_course_vizdoom_health_gathering_supreme' that is not in the saved config file!
+[2025-02-27 20:51:33,996][00031] Adding new argument 'policy_index'=0 that is not in the saved config file!
+[2025-02-27 20:51:33,997][00031] Adding new argument 'eval_deterministic'=False that is not in the saved config file!
+[2025-02-27 20:51:33,998][00031] Adding new argument 'train_script'=None that is not in the saved config file!
+[2025-02-27 20:51:34,000][00031] Adding new argument 'enjoy_script'=None that is not in the saved config file!
+[2025-02-27 20:51:34,000][00031] Using frameskip 1 and render_action_repeat=4 for evaluation
+[2025-02-27 20:51:34,025][00031] RunningMeanStd input shape: (3, 72, 128)
+[2025-02-27 20:51:34,026][00031] RunningMeanStd input shape: (1,)
+[2025-02-27 20:51:34,037][00031] ConvEncoder: input_channels=3
+[2025-02-27 20:51:34,077][00031] Conv encoder output size: 512
+[2025-02-27 20:51:34,078][00031] Policy head output size: 512
+[2025-02-27 20:51:34,104][00031] Loading state from checkpoint /kaggle/working/train_dir/default_experiment/checkpoint_p0/checkpoint_000001292_10584064.pth...
+[2025-02-27 20:51:34,563][00031] Num frames 100...
+[2025-02-27 20:51:34,690][00031] Num frames 200...
+[2025-02-27 20:51:34,811][00031] Num frames 300...
+[2025-02-27 20:51:34,937][00031] Num frames 400...
+[2025-02-27 20:51:35,060][00031] Num frames 500...
+[2025-02-27 20:51:35,175][00031] Num frames 600...
+[2025-02-27 20:51:35,292][00031] Num frames 700...
+[2025-02-27 20:51:35,408][00031] Num frames 800...
+[2025-02-27 20:51:35,537][00031] Num frames 900...
+[2025-02-27 20:51:35,655][00031] Num frames 1000...
+[2025-02-27 20:51:35,773][00031] Num frames 1100...
+[2025-02-27 20:51:35,889][00031] Num frames 1200...
+[2025-02-27 20:51:36,009][00031] Num frames 1300...
+[2025-02-27 20:51:36,115][00031] Avg episode rewards: #0: 37.440, true rewards: #0: 13.440
+[2025-02-27 20:51:36,116][00031] Avg episode reward: 37.440, avg true_objective: 13.440
+[2025-02-27 20:51:36,184][00031] Num frames 1400...
+[2025-02-27 20:51:36,303][00031] Num frames 1500...
+[2025-02-27 20:51:36,426][00031] Num frames 1600...
+[2025-02-27 20:51:36,544][00031] Num frames 1700...
+[2025-02-27 20:51:36,662][00031] Num frames 1800...
+[2025-02-27 20:51:36,778][00031] Num frames 1900...
+[2025-02-27 20:51:36,894][00031] Num frames 2000...
+[2025-02-27 20:51:37,010][00031] Num frames 2100...
+[2025-02-27 20:51:37,125][00031] Num frames 2200...
+[2025-02-27 20:51:37,239][00031] Num frames 2300...
+[2025-02-27 20:51:37,356][00031] Num frames 2400...
+[2025-02-27 20:51:37,472][00031] Num frames 2500...
+[2025-02-27 20:51:37,599][00031] Num frames 2600...
+[2025-02-27 20:51:37,725][00031] Num frames 2700...
+[2025-02-27 20:51:37,843][00031] Num frames 2800...
+[2025-02-27 20:51:37,960][00031] Num frames 2900...
+[2025-02-27 20:51:38,085][00031] Num frames 3000...
+[2025-02-27 20:51:38,209][00031] Num frames 3100...
+[2025-02-27 20:51:38,330][00031] Num frames 3200...
+[2025-02-27 20:51:38,450][00031] Num frames 3300...
+[2025-02-27 20:51:38,560][00031] Avg episode rewards: #0: 42.225, true rewards: #0: 16.725
+[2025-02-27 20:51:38,561][00031] Avg episode reward: 42.225, avg true_objective: 16.725
+[2025-02-27 20:51:38,627][00031] Num frames 3400...
+[2025-02-27 20:51:38,746][00031] Num frames 3500...
+[2025-02-27 20:51:38,866][00031] Num frames 3600...
+[2025-02-27 20:51:38,991][00031] Num frames 3700...
+[2025-02-27 20:51:39,110][00031] Num frames 3800...
+[2025-02-27 20:51:39,227][00031] Num frames 3900...
+[2025-02-27 20:51:39,344][00031] Num frames 4000...
+[2025-02-27 20:51:39,459][00031] Num frames 4100...
+[2025-02-27 20:51:39,576][00031] Num frames 4200...
+[2025-02-27 20:51:39,695][00031] Num frames 4300...
+[2025-02-27 20:51:39,811][00031] Num frames 4400...
+[2025-02-27 20:51:39,874][00031] Avg episode rewards: #0: 37.023, true rewards: #0: 14.690
+[2025-02-27 20:51:39,875][00031] Avg episode reward: 37.023, avg true_objective: 14.690
+[2025-02-27 20:51:39,985][00031] Num frames 4500...
+[2025-02-27 20:51:40,106][00031] Num frames 4600...
+[2025-02-27 20:51:40,226][00031] Num frames 4700...
+[2025-02-27 20:51:40,341][00031] Num frames 4800...
+[2025-02-27 20:51:40,459][00031] Num frames 4900...
+[2025-02-27 20:51:40,577][00031] Num frames 5000...
+[2025-02-27 20:51:40,694][00031] Num frames 5100...
+[2025-02-27 20:51:40,812][00031] Num frames 5200...
+[2025-02-27 20:51:40,928][00031] Num frames 5300...
+[2025-02-27 20:51:41,045][00031] Num frames 5400...
+[2025-02-27 20:51:41,159][00031] Num frames 5500...
+[2025-02-27 20:51:41,278][00031] Num frames 5600...
+[2025-02-27 20:51:41,405][00031] Num frames 5700...
+[2025-02-27 20:51:41,530][00031] Num frames 5800...
+[2025-02-27 20:51:41,679][00031] Avg episode rewards: #0: 36.947, true rewards: #0: 14.697
+[2025-02-27 20:51:41,680][00031] Avg episode reward: 36.947, avg true_objective: 14.697
+[2025-02-27 20:51:41,706][00031] Num frames 5900...
+[2025-02-27 20:51:41,827][00031] Num frames 6000...
+[2025-02-27 20:51:41,942][00031] Num frames 6100...
+[2025-02-27 20:51:42,058][00031] Num frames 6200...
+[2025-02-27 20:51:42,174][00031] Num frames 6300...
+[2025-02-27 20:51:42,293][00031] Num frames 6400...
+[2025-02-27 20:51:42,417][00031] Num frames 6500...
+[2025-02-27 20:51:42,541][00031] Num frames 6600...
+[2025-02-27 20:51:42,665][00031] Num frames 6700...
+[2025-02-27 20:51:42,789][00031] Num frames 6800...
+[2025-02-27 20:51:42,914][00031] Num frames 6900...
+[2025-02-27 20:51:43,038][00031] Num frames 7000...
+[2025-02-27 20:51:43,165][00031] Num frames 7100...
+[2025-02-27 20:51:43,287][00031] Num frames 7200...
+[2025-02-27 20:51:43,402][00031] Num frames 7300...
+[2025-02-27 20:51:43,517][00031] Num frames 7400...
+[2025-02-27 20:51:43,683][00031] Avg episode rewards: #0: 38.792, true rewards: #0: 14.992
+[2025-02-27 20:51:43,684][00031] Avg episode reward: 38.792, avg true_objective: 14.992
+[2025-02-27 20:51:43,690][00031] Num frames 7500...
+[2025-02-27 20:51:43,814][00031] Num frames 7600...
+[2025-02-27 20:51:43,937][00031] Num frames 7700...
+[2025-02-27 20:51:44,060][00031] Num frames 7800...
+[2025-02-27 20:51:44,182][00031] Num frames 7900...
+[2025-02-27 20:51:44,305][00031] Num frames 8000...
+[2025-02-27 20:51:44,425][00031] Num frames 8100...
+[2025-02-27 20:51:44,525][00031] Avg episode rewards: #0: 34.560, true rewards: #0: 13.560
+[2025-02-27 20:51:44,526][00031] Avg episode reward: 34.560, avg true_objective: 13.560
+[2025-02-27 20:51:44,605][00031] Num frames 8200...
+[2025-02-27 20:51:44,721][00031] Num frames 8300...
+[2025-02-27 20:51:44,837][00031] Num frames 8400...
+[2025-02-27 20:51:44,968][00031] Num frames 8500...
+[2025-02-27 20:51:45,084][00031] Num frames 8600...
+[2025-02-27 20:51:45,208][00031] Num frames 8700...
+[2025-02-27 20:51:45,326][00031] Num frames 8800...
+[2025-02-27 20:51:45,448][00031] Num frames 8900...
+[2025-02-27 20:51:45,620][00031] Avg episode rewards: #0: 32.271, true rewards: #0: 12.843
+[2025-02-27 20:51:45,621][00031] Avg episode reward: 32.271, avg true_objective: 12.843
+[2025-02-27 20:51:45,634][00031] Num frames 9000...
+[2025-02-27 20:51:45,754][00031] Num frames 9100...
+[2025-02-27 20:51:45,869][00031] Num frames 9200...
+[2025-02-27 20:51:45,988][00031] Num frames 9300...
+[2025-02-27 20:51:46,105][00031] Num frames 9400...
+[2025-02-27 20:51:46,219][00031] Num frames 9500...
+[2025-02-27 20:51:46,339][00031] Num frames 9600...
+[2025-02-27 20:51:46,451][00031] Num frames 9700...
+[2025-02-27 20:51:46,569][00031] Num frames 9800...
+[2025-02-27 20:51:46,685][00031] Num frames 9900...
+[2025-02-27 20:51:46,804][00031] Num frames 10000...
+[2025-02-27 20:51:46,924][00031] Num frames 10100...
+[2025-02-27 20:51:47,045][00031] Num frames 10200...
+[2025-02-27 20:51:47,164][00031] Num frames 10300...
+[2025-02-27 20:51:47,280][00031] Num frames 10400...
+[2025-02-27 20:51:47,406][00031] Num frames 10500...
+[2025-02-27 20:51:47,524][00031] Num frames 10600...
+[2025-02-27 20:51:47,646][00031] Num frames 10700...
+[2025-02-27 20:51:47,762][00031] Num frames 10800...
+[2025-02-27 20:51:47,899][00031] Avg episode rewards: #0: 34.712, true rewards: #0: 13.587
+[2025-02-27 20:51:47,900][00031] Avg episode reward: 34.712, avg true_objective: 13.587
+[2025-02-27 20:51:47,936][00031] Num frames 10900...
+[2025-02-27 20:51:48,061][00031] Num frames 11000...
+[2025-02-27 20:51:48,180][00031] Num frames 11100...
+[2025-02-27 20:51:48,296][00031] Num frames 11200...
+[2025-02-27 20:51:48,413][00031] Num frames 11300...
+[2025-02-27 20:51:48,532][00031] Num frames 11400...
+[2025-02-27 20:51:48,655][00031] Avg episode rewards: #0: 32.286, true rewards: #0: 12.731
+[2025-02-27 20:51:48,656][00031] Avg episode reward: 32.286, avg true_objective: 12.731
+[2025-02-27 20:51:48,707][00031] Num frames 11500...
+[2025-02-27 20:51:48,826][00031] Num frames 11600...
+[2025-02-27 20:51:48,946][00031] Num frames 11700...
+[2025-02-27 20:51:49,068][00031] Num frames 11800...
+[2025-02-27 20:51:49,196][00031] Num frames 11900...
+[2025-02-27 20:51:49,323][00031] Num frames 12000...
+[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!