Uploading my first RL agent with architecture PPO and environment LunarLander-v2

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+replay.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 266.57 +/- 22.56
+      name: mean_reward
+      verified: false
+---
+
+# **PPO** Agent playing **LunarLander-v2**
+This is a trained model of a **PPO** agent playing **LunarLander-v2**
+using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
+
+## Usage (with Stable-baselines3)
+TODO: Add your code
+
+
+```python
+from stable_baselines3 import ...
+from huggingface_sb3 import load_from_hub
+
+...
+```

config.json

@@ -0,0 +1 @@
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\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 ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 ActorCriticPolicy.__init__ at 0x7e07cb2ad580>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e07cb2ad620>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e07cb2ad6c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e07cb2ad760>", "_build": "<function ActorCriticPolicy._build at 0x7e07cb2ad800>", "forward": "<function ActorCriticPolicy.forward at 0x7e07cb2ad8a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e07cb2ad940>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e07cb2ad9e0>", "_predict": "<function ActorCriticPolicy._predict at 0x7e07cb2ada80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e07cb2adb20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e07cb2adbc0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e07cb2adc60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7e07cb230c40>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1748895106750291512, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 310, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "gAWVdwIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBNudW1weS5fY29yZS5udW1lcmljlIwLX2Zyb21idWZmZXKUk5QolggAAAAAAAAAAQEBAQEBAQGUaAiMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLCIWUjAFDlHSUUpSMDWJvdW5kZWRfYWJvdmWUaBEolggAAAAAAAAAAQEBAQEBAQGUaBVLCIWUaBl0lFKUjAZfc2hhcGWUSwiFlIwDbG93lGgRKJYgAAAAAAAAAAAAtMIAALTCAACgwAAAoMDbD0nAAACgwAAAAIAAAACAlGgLSwiFlGgZdJRSlIwEaGlnaJRoESiWIAAAAAAAAAAAALRCAAC0QgAAoEAAAKBA2w9JQAAAoEAAAIA/AACAP5RoC0sIhZRoGXSUUpSMCGxvd19yZXBylIxbWy05MC4gICAgICAgIC05MC4gICAgICAgICAtNS4gICAgICAgICAtNS4gICAgICAgICAtMy4xNDE1OTI3ICAtNS4KICAtMC4gICAgICAgICAtMC4gICAgICAgXZSMCWhpZ2hfcmVwcpSMU1s5MC4gICAgICAgIDkwLiAgICAgICAgIDUuICAgICAgICAgNS4gICAgICAgICAzLjE0MTU5MjcgIDUuCiAgMS4gICAgICAgICAxLiAgICAgICBdlIwKX25wX3JhbmRvbZROdWIu", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ec41ce78141a8f44bb96be33f34b29588a189a555b9c4cc0e8062a305d2c551
+size 148019

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+2.0.0a5

ppo-LunarLander-v2/data

@@ -0,0 +1,99 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
+        "__module__": "stable_baselines3.common.policies",
+        "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\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 ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\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 share_features_extractor: If True, the features extractor is shared between the policy and value networks.\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 ActorCriticPolicy.__init__ at 0x7e07cb2ad580>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7e07cb2ad620>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7e07cb2ad6c0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7e07cb2ad760>",
+        "_build": "<function ActorCriticPolicy._build at 0x7e07cb2ad800>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7e07cb2ad8a0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7e07cb2ad940>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7e07cb2ad9e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7e07cb2ada80>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7e07cb2adb20>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7e07cb2adbc0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7e07cb2adc60>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7e07cb230c40>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1748895106750291512,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="
+    },
+    "_last_original_obs": null,
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.015808000000000044,
+    "_stats_window_size": 100,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 310,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "bounded_below": "[ True  True  True  True  True  True  True  True]",
+        "bounded_above": "[ True  True  True  True  True  True  True  True]",
+        "_shape": [
+            8
+        ],
+        "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
+        "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
+        "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
+        "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
+        "n": "4",
+        "start": "0",
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "n_steps": 2048,
+    "gamma": 0.99,
+    "gae_lambda": 0.95,
+    "ent_coef": 0.0,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 10,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eff7541f4b95ab287b2bb75f878d600b81179b4fcc589901ddc97c3b5a339850
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0f8e09d514f62c527be110f8ba7ac39a7b8f827d08c970dfc5a31cb61570b400
+size 43762

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
+size 864

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025
+- Python: 3.11.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.6.0+cu124
+- GPU Enabled: True
+- Numpy: 2.0.2
+- Cloudpickle: 3.1.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:72d5d00466cef9415ce95e0b66cd3c5e58cb64bf5ed5b004abc86faf2242cb97
+size 106860

results.json

@@ -0,0 +1 @@
+{"mean_reward": 266.5722807000001, "std_reward": 22.55936984824873, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-06-02T20:47:15.444049"}