10m timesteps SpaceInvaders

README.md

@@ -22,10 +22,13 @@ model-index:
 ---
 
 # **DQN** Agent playing **SpaceInvadersNoFrameskip-v4**
+
 This is a trained model of a **DQN** agent playing **SpaceInvadersNoFrameskip-v4**
 using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
 
+
 ## Usage (with Stable-baselines3)
+
 TODO: Add your code
 
 
@@ -34,4 +37,4 @@ from stable_baselines3 import ...
 from huggingface_sb3 import load_from_hub
 
 ...
-```
+```

dqn-SpaceInvadersNoFrameskip-v4.zip

@@ -1,3 +1,3 @@
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-size 27220531
+oid sha256:c6311eb6f415d93f7c9c53172878a68276abd230418678ff98468a978d1554e5
+size 27221660

dqn-SpaceInvadersNoFrameskip-v4/_stable_baselines3_version

@@ -1 +1 @@
-2.4.0
+2.5.0

dqn-SpaceInvadersNoFrameskip-v4/data

@@ -4,9 +4,9 @@
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         "__module__": "stable_baselines3.dqn.policies",
         "__doc__": "\n    Policy class for DQN when using images as input.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param features_extractor_class: Features extractor to use.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ",
-        "__init__": "<function CnnPolicy.__init__ at 0x7fd3ba84a480>",
+        "__init__": "<function CnnPolicy.__init__ at 0x78dc61faa3b0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7fd3ba843740>"
+        "_abc_impl": "<_abc._abc_data object at 0x78dc61fcc080>"
     },
     "verbose": 1,
     "policy_kwargs": {},
@@ -16,7 +16,10 @@
     "seed": 1632485984,
     "action_noise": null,
     "start_time": 1738801757428800604,
-    "learning_rate": 0.0001,
+    "learning_rate": {
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+    },
     "tensorboard_log": "runs/SpaceInvadersNoFrameskip-v4__dqn__1632485984__1738801755/SpaceInvadersNoFrameskip-v4",
     "_last_obs": null,
     "_last_episode_starts": {
@@ -81,18 +84,18 @@
         "__module__": "stable_baselines3.common.buffers",
         "__annotations__": "{'observations': <class 'numpy.ndarray'>, 'next_observations': <class 'numpy.ndarray'>, 'actions': <class 'numpy.ndarray'>, 'rewards': <class 'numpy.ndarray'>, 'dones': <class 'numpy.ndarray'>, 'timeouts': <class 'numpy.ndarray'>}",
         "__doc__": "\n    Replay buffer used in off-policy algorithms like SAC/TD3.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device: PyTorch device\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        of the replay buffer which reduces by almost a factor two the memory used,\n        at a cost of more complexity.\n        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n        and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n        Cannot be used in combination with handle_timeout_termination.\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ",
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         "__abstractmethods__": "frozenset()",
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+        "_abc_impl": "<_abc._abc_data object at 0x78dc6974fe40>"
     },
     "replay_buffer_kwargs": {},
     "train_freq": {
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@@ -102,14 +105,14 @@
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     }
 }

dqn-SpaceInvadersNoFrameskip-v4/system_info.txt

@@ -1,8 +1,8 @@
-- OS: Linux-5.15.167.4-microsoft-standard-WSL2-x86_64-with-glibc2.35 # 1 SMP Tue Nov 5 00:21:55 UTC 2024
-- Python: 3.11.0rc1
-- Stable-Baselines3: 2.4.0
-- PyTorch: 2.5.1+cu124
+- OS: Linux-6.8.0-52-generic-x86_64-with-glibc2.39 # 53-Ubuntu SMP PREEMPT_DYNAMIC Sat Jan 11 00:06:25 UTC 2025
+- Python: 3.10.12
+- Stable-Baselines3: 2.5.0
+- PyTorch: 2.6.0+cu124
 - GPU Enabled: True
 - Numpy: 2.2.2
-- Cloudpickle: 3.1.0
+- Cloudpickle: 3.1.1
 - Gymnasium: 1.0.0

results.json

@@ -1 +1 @@
-{"mean_reward": 739.5, "std_reward": 253.18422146729444, "is_deterministic": false, "n_eval_episodes": 10, "eval_datetime": "2025-02-06T13:19:37.679632"}
+{"mean_reward": 739.5, "std_reward": 253.18422146729444, "is_deterministic": false, "n_eval_episodes": 10, "eval_datetime": "2025-02-06T13:35:28.511766"}