Initial commit

README.md

@@ -16,22 +16,69 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 137.55 +/- 96.07
+      value: -638.18 +/- 102.53
       name: mean_reward
       verified: false
 ---
 
 # **DQN** Agent playing **LunarLander-v2**
 This is a trained model of a **DQN** agent playing **LunarLander-v2**
-using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
+and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).
 
-## Usage (with Stable-baselines3)
-TODO: Add your code
+The RL Zoo is a training framework for Stable Baselines3
+reinforcement learning agents,
+with hyperparameter optimization and pre-trained agents included.
 
+## Usage (with SB3 RL Zoo)
 
+RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
+SB3: https://github.com/DLR-RM/stable-baselines3<br/>
+SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
+
+Install the RL Zoo (with SB3 and SB3-Contrib):
+```bash
+pip install rl_zoo3
+```
+
+```
+# Download model and save it into the logs/ folder
+python -m rl_zoo3.load_from_hub --algo dqn --env LunarLander-v2 -orga nsanghi -f logs/
+python -m rl_zoo3.enjoy --algo dqn --env LunarLander-v2  -f logs/
+```
+
+If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
+```
+python -m rl_zoo3.load_from_hub --algo dqn --env LunarLander-v2 -orga nsanghi -f logs/
+python -m rl_zoo3.enjoy --algo dqn --env LunarLander-v2  -f logs/
+```
+
+## Training (with the RL Zoo)
+```
+python -m rl_zoo3.train --algo dqn --env LunarLander-v2 -f logs/
+# Upload the model and generate video (when possible)
+python -m rl_zoo3.push_to_hub --algo dqn --env LunarLander-v2 -f logs/ -orga nsanghi
+```
+
+## Hyperparameters
 ```python
-from stable_baselines3 import ...
-from huggingface_sb3 import load_from_hub
+OrderedDict([('batch_size', 128),
+             ('buffer_size', 50000),
+             ('exploration_final_eps', 0.1),
+             ('exploration_fraction', 0.12),
+             ('gamma', 0.99),
+             ('gradient_steps', -1),
+             ('learning_rate', 0.00063),
+             ('learning_starts', 0),
+             ('n_timesteps', 100000.0),
+             ('policy', 'MlpPolicy'),
+             ('policy_kwargs', 'dict(net_arch=[256, 256])'),
+             ('target_update_interval', 250),
+             ('train_freq', 4),
+             ('normalize', False)])
+```
 
-...
+# Environment Arguments
+```python
+{'render_mode': 'rgb_array'}
 ```

dqn-LunarLander-v2.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:86645a125750d55c5dd9ceef8cd6e8c46c2b66d69f82c2e95dcaac125169f66c
-size 106579
+oid sha256:7dc80afb4d016a2eaf89ebab1f076a93ca9ec24232affbac60ea73ea88eea3d6
+size 1129713

dqn-LunarLander-v2/data

@@ -5,85 +5,57 @@
         "__module__": "stable_baselines3.dqn.policies",
         "__annotations__": "{'q_net': <class 'stable_baselines3.dqn.policies.QNetwork'>, 'q_net_target': <class 'stable_baselines3.dqn.policies.QNetwork'>}",
         "__doc__": "\n    Policy class with Q-Value Net and target net for DQN\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 features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\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 DQNPolicy.__init__ at 0x7efd33b69310>",
-        "_build": "<function DQNPolicy._build at 0x7efd33b693a0>",
-        "make_q_net": "<function DQNPolicy.make_q_net at 0x7efd33b69430>",
-        "forward": "<function DQNPolicy.forward at 0x7efd33b694c0>",
-        "_predict": "<function DQNPolicy._predict at 0x7efd33b69550>",
-        "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7efd33b695e0>",
-        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7efd33b69670>",
+        "__init__": "<function DQNPolicy.__init__ at 0x7fdc7e944550>",
+        "_build": "<function DQNPolicy._build at 0x7fdc7e9445e0>",
+        "make_q_net": "<function DQNPolicy.make_q_net at 0x7fdc7e944670>",
+        "forward": "<function DQNPolicy.forward at 0x7fdc7e944700>",
+        "_predict": "<function DQNPolicy._predict at 0x7fdc7e944790>",
+        "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7fdc7e944820>",
+        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7fdc7e9448b0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7efd33b6b0c0>"
+        "_abc_impl": "<_abc._abc_data object at 0x7fdc7e947940>"
     },
     "verbose": 1,
-    "policy_kwargs": {},
-    "num_timesteps": 100000,
+    "policy_kwargs": {
+        "net_arch": [
+            256,
+            256
+        ]
+    },
+    "num_timesteps": 724,
     "_total_timesteps": 100000,
     "_num_timesteps_at_start": 0,
-    "seed": null,
+    "seed": 0,
     "action_noise": null,
-    "start_time": 1709621653573777784,
-    "learning_rate": 0.0001,
-    "tensorboard_log": null,
-    "_last_obs": {
-        ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAIBR6b3lvGw/iyDjPMnrLr4dUSI8S2h8vAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
+    "start_time": 1709621687586089877,
+    "learning_rate": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
     },
+    "tensorboard_log": null,
+    "_last_obs": null,
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
         ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAAGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
     },
     "_last_original_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAMDe6b3LuG0/iiDjPESdE77s7y48Y2h8vAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAECrMD5pK9U/dq4RPzCMDD6frHC+bVIGvgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
     },
-    "_episode_num": 614,
+    "_episode_num": 8,
     "use_sde": false,
     "sde_sample_freq": -1,
-    "_current_progress_remaining": 0.0,
+    "_current_progress_remaining": 0.99276,
     "_stats_window_size": 100,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "gAWVGAEAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHwHd+SbH6uW+MAWyUS1GMAXSUR0AZbjuKGcnWdX2UKGgGR8BO892ovSMMaAdLbWgIR0AltINmUW2xdX2UKGgGR8BUIQqI7/4qaAdLT2gIR0Az87Uoa1kUdX2UKGgGR8B1op5C4SYgaAdLdGgIR0A7xMewLVnVdX2UKGgGR8BXi6XSjQAuaAdLRmgIR0BOa1PFefI0dX2UKGgGR8BbMVMZgogFaAdLS2gIR0BZvFZLZi/gdX2UKGgGR8BtJijafzz3aAdLV2gIR0Bi1y2QXAM2dX2UKGgGR8BLctFBppN9aAdLSGgIR0Bn0oppeu3ddWUu"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 12500,
-    "buffer_size": 1000000,
-    "batch_size": 32,
-    "learning_starts": 50000,
-    "tau": 1.0,
-    "gamma": 0.99,
-    "gradient_steps": 1,
-    "optimize_memory_usage": false,
-    "replay_buffer_class": {
-        ":type:": "<class 'abc.ABCMeta'>",
-        ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
-        "__module__": "stable_baselines3.common.buffers",
-        "__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    ",
-        "__init__": "<function ReplayBuffer.__init__ at 0x7efd33bba8b0>",
-        "add": "<function ReplayBuffer.add at 0x7efd33bba940>",
-        "sample": "<function ReplayBuffer.sample at 0x7efd33bba9d0>",
-        "_get_samples": "<function ReplayBuffer._get_samples at 0x7efd33bbaa60>",
-        "_maybe_cast_dtype": "<staticmethod object at 0x7efd33bbf3d0>",
-        "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7efd33f2d240>"
-    },
-    "replay_buffer_kwargs": {},
-    "train_freq": {
-        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
-        ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
-    },
-    "use_sde_at_warmup": false,
-    "exploration_initial_eps": 1.0,
-    "exploration_final_eps": 0.1,
-    "exploration_fraction": 0.1,
-    "target_update_interval": 250,
-    "_n_calls": 100000,
-    "max_grad_norm": 10,
-    "exploration_rate": 0.1,
+    "_n_updates": 720,
     "observation_space": {
         ":type:": "<class 'gymnasium.spaces.box.Box'>",
         ":serialized:": "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",
@@ -101,7 +73,7 @@
     },
     "action_space": {
         ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
-        ":serialized:": "gAWVxgEAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZSMFG51bXB5LnJhbmRvbS5fcGlja2xllIwQX19nZW5lcmF0b3JfY3RvcpSTlIwFUENHNjSUaB+MFF9fYml0X2dlbmVyYXRvcl9jdG9ylJOUhpRSlH2UKIwNYml0X2dlbmVyYXRvcpSMBVBDRzY0lIwFc3RhdGWUfZQoaCqKEZjVN9mFTYBBIuRRlEAkHKUAjANpbmOUihB17S3+WRffTxY2l7BoR6QDdYwKaGFzX3VpbnQzMpRLAIwIdWludGVnZXKUigUYs6biAHVidWIu",
+        ":serialized:": "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",
         "n": "4",
         "start": "0",
         "_shape": [],
@@ -109,14 +81,47 @@
         "_np_random": "Generator(PCG64)"
     },
     "n_envs": 1,
+    "buffer_size": 1,
+    "batch_size": 128,
+    "learning_starts": 0,
+    "tau": 1.0,
+    "gamma": 0.99,
+    "gradient_steps": -1,
+    "optimize_memory_usage": false,
+    "replay_buffer_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
+        "__module__": "stable_baselines3.common.buffers",
+        "__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    ",
+        "__init__": "<function ReplayBuffer.__init__ at 0x7fdc7e9b8b80>",
+        "add": "<function ReplayBuffer.add at 0x7fdc7e9b8c10>",
+        "sample": "<function ReplayBuffer.sample at 0x7fdc7e9b8ca0>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x7fdc7e9b8d30>",
+        "_maybe_cast_dtype": "<staticmethod object at 0x7fdc7ea34df0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7fdc7e9b05c0>"
+    },
+    "replay_buffer_kwargs": {},
+    "train_freq": {
+        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
+        ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
+    },
+    "use_sde_at_warmup": false,
+    "exploration_initial_eps": 1.0,
+    "exploration_final_eps": 0.1,
+    "exploration_fraction": 0.12,
+    "target_update_interval": 250,
+    "_n_calls": 724,
+    "max_grad_norm": 10,
+    "exploration_rate": 0.9456999999999998,
     "lr_schedule": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "batch_norm_stats": [],
     "batch_norm_stats_target": [],
     "exploration_schedule": {
         ":type:": "<class 'function'>",
-        ":serialized:": "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"
+        ":serialized:": "gAWVjAMAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLBEsTQyxkAXwAGACIAWsEchCIAFMAiAJkAXwAGACIAIgCGAAUAIgBGwAXAFMAZABTAJROSwGGlCmMEnByb2dyZXNzX3JlbWFpbmluZ5SFlIxpL2hvbWUvbnNhbmdoaS9zYW5kYm94L2FwcmVzcy9kcmwtMmVkL3ZlbnYzOS9saWIvcHl0aG9uMy45L3NpdGUtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5RLcUMGAAEMAQQClIwDZW5klIwMZW5kX2ZyYWN0aW9ulIwFc3RhcnSUh5QpdJRSlH2UKIwLX19wYWNrYWdlX1+UjBhzdGFibGVfYmFzZWxpbmVzMy5jb21tb26UjAhfX25hbWVfX5SMHnN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi51dGlsc5SMCF9fZmlsZV9flIxpL2hvbWUvbnNhbmdoaS9zYW5kYm94L2FwcmVzcy9kcmwtMmVkL3ZlbnYzOS9saWIvcHl0aG9uMy45L3NpdGUtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUaB0pUpRoHSlSlIeUdJRSlGgAjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoI32UfZQoaBhoDYwMX19xdWFsbmFtZV9flIwbZ2V0X2xpbmVhcl9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UKGgKjAhidWlsdGluc5SMBWZsb2F0lJOUjAZyZXR1cm6UaC51jA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoGYwHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/uZmZmZmZmoWUUpRoNkc/vrhR64UeuIWUUpRoNkc/8AAAAAAAAIWUUpSHlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="
     }
 }

dqn-LunarLander-v2/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:687f677c3541ecea2308387873e5ae69a095be13c773aee6060523e3a1fbbdb0
-size 45216
+oid sha256:d23cc94e3d3af4ed7711415633baa414133cf7d025a7de2d4ca34b47f9419485
+size 558240

dqn-LunarLander-v2/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:88ff7a337da5cfa5079d8615c039ba47dfb775a2d89664a2cbc0382a07b7ab11
-size 44338
+oid sha256:ff5f4deb73f0a24c75f5e69235c87d7913f1b647e9ba6f0927925cf872bc0dac
+size 557362

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:71c62f7e3c3e91abd5d796a879eeccbe22f8252b304676b6dd0924191ad0b71c
-size 196345
+oid sha256:fe90af5c84d184044f7a991b157b553b2bd6e77fca38d3552a7e3d421e84c5f7
+size 230147

results.json

@@ -1 +1 @@
-{"mean_reward": 137.5536330541738, "std_reward": 96.07414787460716, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-05T12:45:15.589257"}
+{"mean_reward": -638.1819969999999, "std_reward": 102.53389534601408, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-05T13:35:44.587707"}