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: -207.98 +/- 53.49
+      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 0x7be026b18280>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7be026b18310>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7be026b183a0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7be026b18430>", "_build": "<function ActorCriticPolicy._build at 0x7be026b184c0>", "forward": "<function ActorCriticPolicy.forward at 0x7be026b18550>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7be026b185e0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7be026b18670>", "_predict": "<function ActorCriticPolicy._predict at 0x7be026b18700>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7be026b18790>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7be026b18820>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7be026b188b0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7be026b09400>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 114688, "_total_timesteps": 100000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1692510750878916577, "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": -0.1468799999999999, "_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": 32, "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=", "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "system_info": {"OS": "Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.0.1+cu118", "GPU Enabled": "True", "Numpy": "1.23.5", "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 sha256:070eed0e297aca8e7a7c5aaf124d77a5ea6763815c49ad226cbee1db9443168c
+size 146621

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 0x7be026b18280>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7be026b18310>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7be026b183a0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7be026b18430>",
+        "_build": "<function ActorCriticPolicy._build at 0x7be026b184c0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7be026b18550>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7be026b185e0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7be026b18670>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7be026b18700>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7be026b18790>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7be026b18820>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7be026b188b0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7be026b09400>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 114688,
+    "_total_timesteps": 100000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1692510750878916577,
+    "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": -0.1468799999999999,
+    "_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": 32,
+    "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:": "gAWV1QAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCloCmgOjApfbnBfcmFuZG9tlE51Yi4=",
+        "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7a633d0214b2e83b8ced0ad77960c51397a17fd12dc5a405c96c81601b2eff8d
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ba12baed40fb35dc9b11f40715473e488d07753b7e7310cb1fb5e27b969526a3
+size 43329

ppo-LunarLander-v2/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

ppo-LunarLander-v2/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-5.15.109+-x86_64-with-glibc2.35 # 1 SMP Fri Jun 9 10:57:30 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.0.1+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": -207.9764193, "std_reward": 53.4927693912416, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-08-20T06:13:11.001932"}