Test upload

README.md

@@ -0,0 +1,36 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - metrics:
+    - type: mean_reward
+      value: 274.13 +/- 12.12
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+---
+
+# **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 0x7fa20ba9d0e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa20ba9d170>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa20ba9d200>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa20ba9d290>", "_build": "<function ActorCriticPolicy._build at 0x7fa20ba9d320>", "forward": "<function ActorCriticPolicy.forward at 0x7fa20ba9d3b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa20ba9d440>", "_predict": "<function ActorCriticPolicy._predict at 0x7fa20ba9d4d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa20ba9d560>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa20ba9d5f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa20ba9d680>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7fa20ba76150>"}, "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": 1507328, "_total_timesteps": 1500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1657969167.2245035, "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": -0.004885333333333408, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 368, "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, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.6.0", "PyTorch": "1.12.0+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f3168e1ceb2ba3d362c689292cd178afb9375451ab1450036106fec91ed23833
+size 147046

ppo-LunarLander-v2/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.0

ppo-LunarLander-v2/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 0x7fa20ba9d0e0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa20ba9d170>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa20ba9d200>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa20ba9d290>",
+        "_build": "<function ActorCriticPolicy._build at 0x7fa20ba9d320>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7fa20ba9d3b0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa20ba9d440>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7fa20ba9d4d0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa20ba9d560>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa20ba9d5f0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa20ba9d680>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7fa20ba76150>"
+    },
+    "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": 1507328,
+    "_total_timesteps": 1500000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1657969167.2245035,
+    "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": -0.004885333333333408,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 368,
+    "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
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:858228253dca833a846c50931922125af24bc2960dec8ebb94d0af4839f21c13
+size 87865

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6c71564159c432550830333481b98e4f670d4f4432f5c70a6c0df30baec8e028
+size 43201

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 +1,7 @@
+OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
+Python: 3.7.13
+Stable-Baselines3: 1.6.0
+PyTorch: 1.12.0+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": 274.13380002520984, "std_reward": 12.117772843385417, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-07-16T11:25:54.219417"}