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: 287.80 +/- 12.35
+      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 0x788ebf751900>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x788ebf751990>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x788ebf751a20>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x788ebf751ab0>", "_build": "<function ActorCriticPolicy._build at 0x788ebf751b40>", "forward": "<function ActorCriticPolicy.forward at 0x788ebf751bd0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x788ebf751c60>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x788ebf751cf0>", "_predict": "<function ActorCriticPolicy._predict at 0x788ebf751d80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x788ebf751e10>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x788ebf751ea0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x788ebf751f30>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x788ebf6e2840>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": 344042492, "action_noise": null, "start_time": 1684372995405168368, "learning_rate": 0.0, "tensorboard_log": "tensorboard-logs/ppo-LunarLander-v2-stable-reward-penalize-time/LunarLander-v2", "_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": 13053, "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, "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": "[-1.5       -1.5       -5.        -5.        -3.1415927 -5.\n -0.        -0.       ]", "high": "[1.5       1.5       5.        5.        3.1415927 5.        1.\n 1.       ]", "low_repr": "[-1.5       -1.5       -5.        -5.        -3.1415927 -5.\n -0.        -0.       ]", "high_repr": "[1.5       1.5       5.        5.        3.1415927 5.        1.\n 1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 16, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2-TP.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6848db4cd18fa4fe6929ef2386810d96b2d23954e37eaf2fba9b713c3c72631c
+size 148040

ppo-LunarLander-v2-TP/_stable_baselines3_version

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

ppo-LunarLander-v2-TP/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 0x788ebf751900>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x788ebf751990>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x788ebf751a20>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x788ebf751ab0>",
+        "_build": "<function ActorCriticPolicy._build at 0x788ebf751b40>",
+        "forward": "<function ActorCriticPolicy.forward at 0x788ebf751bd0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x788ebf751c60>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x788ebf751cf0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x788ebf751d80>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x788ebf751e10>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x788ebf751ea0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x788ebf751f30>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x788ebf6e2840>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": 344042492,
+    "action_noise": null,
+    "start_time": 1684372995405168368,
+    "learning_rate": 0.0,
+    "tensorboard_log": "tensorboard-logs/ppo-LunarLander-v2-stable-reward-penalize-time/LunarLander-v2",
+    "_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": 13053,
+    "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,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "gAWVZgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAADAvwAAwL8AAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAwD8AAMA/AACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFNbLTEuNSAgICAgICAtMS41ICAgICAgIC01LiAgICAgICAgLTUuICAgICAgICAtMy4xNDE1OTI3IC01LgogLTAuICAgICAgICAtMC4gICAgICAgXZSMCWhpZ2hfcmVwcpSMS1sxLjUgICAgICAgMS41ICAgICAgIDUuICAgICAgICA1LiAgICAgICAgMy4xNDE1OTI3IDUuICAgICAgICAxLgogMS4gICAgICAgXZSMCl9ucF9yYW5kb22UTnViLg==",
+        "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": "[-1.5       -1.5       -5.        -5.        -3.1415927 -5.\n -0.        -0.       ]",
+        "high": "[1.5       1.5       5.        5.        3.1415927 5.        1.\n 1.       ]",
+        "low_repr": "[-1.5       -1.5       -5.        -5.        -3.1415927 -5.\n -0.        -0.       ]",
+        "high_repr": "[1.5       1.5       5.        5.        3.1415927 5.        1.\n 1.       ]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWVpgEAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgLjAJpOJSJiIeUUpQoSwNoD05OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZSMFG51bXB5LnJhbmRvbS5fcGlja2xllIwQX19nZW5lcmF0b3JfY3RvcpSTlIwFUENHNjSUhZRSlH2UKIwNYml0X2dlbmVyYXRvcpSMBVBDRzY0lIwFc3RhdGWUfZQoaCiKEV4K1MW9hy6CeXDlnP0wKqkAjANpbmOUihA3pWqn68r+ZmlikvjTpO9ndYwKaGFzX3VpbnQzMpRLAIwIdWludGVnZXKUSwB1YnViLg==",
+        "n": "4",
+        "start": "0",
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": "Generator(PCG64)"
+    },
+    "n_envs": 16,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    }
+}

ppo-LunarLander-v2-TP/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6570cfccc775418234cd54cf6b0eb8c14eeed952656103cffac1c36432ca0909
+size 88490

ppo-LunarLander-v2-TP/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:767f9a8e32d06b8bce7c420b7a746d2f6ffef8facd0ab4a9bd0d7f539f8f27e4
+size 43762

ppo-LunarLander-v2-TP/pytorch_variables.pth

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

ppo-LunarLander-v2-TP/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-5.15.120+-x86_64-with-glibc2.35 # 1 SMP Wed Aug 30 11:19:59 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.1.0+cu118
+- GPU Enabled: True
+- Numpy: 1.23.5
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 287.8039047612085, "std_reward": 12.346323590414212, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-12-07T12:50:23.369958"}