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: -164.95 +/- 71.20
+      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 0x7aef1ac0bc70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7aef1ac0bd00>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7aef1ac0bd90>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7aef1ac0be20>", "_build": "<function ActorCriticPolicy._build at 0x7aef1ac0beb0>", "forward": "<function ActorCriticPolicy.forward at 0x7aef1ac0bf40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7aef1ac10040>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7aef1ac100d0>", "_predict": "<function ActorCriticPolicy._predict at 0x7aef1ac10160>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7aef1ac101f0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7aef1ac10280>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7aef1ac10310>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7aef1ada7580>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 16384, "_total_timesteps": 10000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1730132787486830740, "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": -0.6384000000000001, "_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": 4, "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": "2.5.0+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 sha256:53589ddbe8b777d51e4333a5885d4a6bf33b97c6bb2ba810856cc4aebd558174
+size 147880

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 0x7aef1ac0bc70>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7aef1ac0bd00>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7aef1ac0bd90>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7aef1ac0be20>",
+        "_build": "<function ActorCriticPolicy._build at 0x7aef1ac0beb0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7aef1ac0bf40>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7aef1ac10040>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7aef1ac100d0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7aef1ac10160>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7aef1ac101f0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7aef1ac10280>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7aef1ac10310>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7aef1ada7580>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 16384,
+    "_total_timesteps": 10000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1730132787486830740,
+    "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": -0.6384000000000001,
+    "_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": 4,
+    "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:": "gAWVrQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUaACMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFowEZnVuY5SMDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:02d93e3b6f9e1061f9974b0ba791f4f263cc007791a89b0a48760f1ed7ab224f
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:43158f382a4f1facd6636c43c9056c5978bc4f103e5f692ec77eae4ad85a803a
+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: 2.5.0+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": -164.95439397601876, "std_reward": 71.19781961866936, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-10-28T16:32:04.767489"}