First try of Unit 1 CoLab with PPO trained with 1 million steps

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: 246.44 +/- 41.41
+      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 0x7bdb0e8b1900>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bdb0e8b1990>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bdb0e8b1a20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bdb0e8b1ab0>", "_build": "<function ActorCriticPolicy._build at 0x7bdb0e8b1b40>", "forward": "<function ActorCriticPolicy.forward at 0x7bdb0e8b1bd0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bdb0e8b1c60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bdb0e8b1cf0>", "_predict": "<function ActorCriticPolicy._predict at 0x7bdb0e8b1d80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bdb0e8b1e10>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bdb0e8b1ea0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bdb0e8b1f30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7bdb0e977e00>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1734909390566026526, "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_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": 248, "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu121", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.0", "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 sha256:000f44278260fdaefacf4e30704f01858a4c168739fac96ac56992263e3d0ea0
+size 148016

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 0x7bdb0e8b1900>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7bdb0e8b1990>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7bdb0e8b1a20>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7bdb0e8b1ab0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7bdb0e8b1b40>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7bdb0e8b1bd0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7bdb0e8b1c60>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7bdb0e8b1cf0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7bdb0e8b1d80>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7bdb0e8b1e10>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7bdb0e8b1ea0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7bdb0e8b1f30>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7bdb0e977e00>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1734909390566026526,
+    "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:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+    },
+    "_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": 248,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=",
+        "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:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
+        "n": "4",
+        "start": "0",
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "n_steps": 1024,
+    "gamma": 0.999,
+    "gae_lambda": 0.98,
+    "ent_coef": 0.01,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 4,
+    "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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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a810ca1c2f9900f0bcba21015b651e5df9e02837380bb065d19ecd90549f1c9e
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6b0d974c6300969b47c1ceb4f15d1870a6290f2d57e6be1989f2ef367757944
+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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.5.1+cu121
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 3.1.0
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 246.43619689999997, "std_reward": 41.40578577102013, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-12-22T23:46:11.144783"}