Upload first trained agent using PPO on LunarLander-v2

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: 257.65 +/- 19.13
+      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 0x7b5fcbe01000>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b5fcbe01090>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b5fcbe01120>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b5fcbe011b0>", "_build": "<function ActorCriticPolicy._build at 0x7b5fcbe01240>", "forward": "<function ActorCriticPolicy.forward at 0x7b5fcbe012d0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b5fcbe01360>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b5fcbe013f0>", "_predict": "<function ActorCriticPolicy._predict at 0x7b5fcbe01480>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b5fcbe01510>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b5fcbe015a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b5fcbe01630>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7b5fcbdaa0c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1710262090139389310, "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": 291, "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+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:dcd10dc1d9e04fed2cd9998b07cb3542e19b46364dbb11a3b9e46b671daac1cf
+size 148080

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 0x7b5fcbe01000>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7b5fcbe01090>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7b5fcbe01120>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7b5fcbe011b0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7b5fcbe01240>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7b5fcbe012d0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7b5fcbe01360>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7b5fcbe013f0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7b5fcbe01480>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7b5fcbe01510>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7b5fcbe015a0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7b5fcbe01630>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7b5fcbdaa0c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1710262090139389310,
+    "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": 291,
+    "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:e6f6af97cb76ec1a3f90aa517823cca99ebd15a0603791c22c9b432dc7bcbd6e
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:28cc578d12eb31570f07aeb5e483d64b3d2565f429d1ca99bd44334189a24020
+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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.1.0+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": 257.6485709, "std_reward": 19.13343224139998, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-12T17:24:11.513670"}