pushing trained lunar lander model

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: 268.86 +/- 11.55
+      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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7f43eb24aca0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f43eb24ad30>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f43eb24adc0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f43eb24ae50>", "_build": "<function ActorCriticPolicy._build at 0x7f43eb24aee0>", "forward": "<function ActorCriticPolicy.forward at 0x7f43eb24af70>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f43eb250040>", "_predict": "<function ActorCriticPolicy._predict at 0x7f43eb2500d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f43eb250160>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f43eb2501f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f43eb250280>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f43eb2c64b0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1671944926552847294, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_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, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 310, "n_steps": 2048, "gamma": 0.99, "gae_lambda": 0.95, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.16", "Stable-Baselines3": "1.6.2", "PyTorch": "1.13.0+cu116", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

lunar_lander_v1_ppo.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b03d30005022ef7b72d14ffcc007b088a834b4fb31b2af9b8b2c30670d23b40c
+size 147129

lunar_lander_v1_ppo/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.2

lunar_lander_v1_ppo/data

@@ -0,0 +1,94 @@
+{
+    "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 sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7f43eb24aca0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f43eb24ad30>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f43eb24adc0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f43eb24ae50>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f43eb24aee0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f43eb24af70>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f43eb250040>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f43eb2500d0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f43eb250160>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f43eb2501f0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f43eb250280>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f43eb2c64b0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "_shape": [
+            8
+        ],
+        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
+        "high": "[inf inf inf inf inf inf inf inf]",
+        "bounded_below": "[False False False False False False False False]",
+        "bounded_above": "[False False False False False False False False]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
+        "n": 4,
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1671944926552847294,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "_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,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 310,
+    "n_steps": 2048,
+    "gamma": 0.99,
+    "gae_lambda": 0.95,
+    "ent_coef": 0.0,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 10,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null
+}

lunar_lander_v1_ppo/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e275b584eacc7628bdc9353766d2cc6551a615dc35f800d03a0ca70f6d7d3fdb
+size 87929

lunar_lander_v1_ppo/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b54ca468ff6f918337a0b396ee6e046d62aa4bc08ece332e58f5de6739fc23df
+size 43201

lunar_lander_v1_ppo/pytorch_variables.pth

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

lunar_lander_v1_ppo/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022
+Python: 3.8.16
+Stable-Baselines3: 1.6.2
+PyTorch: 1.13.0+cu116
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 268.86171487558465, "std_reward": 11.548790945671744, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-25T05:36:32.194596"}