Upload PPO LunarLander-v2 trained agent

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: 237.86 +/- 17.05
+      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 0x7a89a580fa30>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a89a580fac0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a89a580fb50>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a89a580fbe0>", "_build": "<function ActorCriticPolicy._build at 0x7a89a580fc70>", "forward": "<function ActorCriticPolicy.forward at 0x7a89a580fd00>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a89a580fd90>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a89a580fe20>", "_predict": "<function ActorCriticPolicy._predict at 0x7a89a580feb0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a89a580ff40>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a89a5620040>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a89a56200d0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a89a57c20c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1716753864295321547, "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 Sun Apr 28 14:29:16 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "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 sha256:36d2948cb25869351d269cf21a67ae1c2397099a6313bd5a58b3b99f5d54bcb8
+size 148088

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 0x7a89a580fa30>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a89a580fac0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a89a580fb50>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a89a580fbe0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7a89a580fc70>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7a89a580fd00>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a89a580fd90>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a89a580fe20>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7a89a580feb0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a89a580ff40>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a89a5620040>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a89a56200d0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7a89a57c20c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1716753864295321547,
+    "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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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:13a260a0ce0ae5f7f265ef09a02b12ab954e89cab8289e594fe11d4f3015cf96
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2969e13fba3ca5a34f78b8cee24ca7575fb1b59ad59c712c32e9a0d9df2cc50b
+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 Sun Apr 28 14:29:16 UTC 2024
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.3.0+cu121
+- GPU Enabled: True
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 237.8575319378469, "std_reward": 17.050386723905305, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-05-26T20:46:46.661379"}