Test commit

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: -238.72 +/- 303.92
+      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 0x7f25a61ba440>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f25a61ba4d0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f25a61ba560>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f25a61ba5f0>", "_build": "<function ActorCriticPolicy._build at 0x7f25a61ba680>", "forward": "<function ActorCriticPolicy.forward at 0x7f25a61ba710>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f25a61ba7a0>", "_predict": "<function ActorCriticPolicy._predict at 0x7f25a61ba830>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f25a61ba8c0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f25a61ba950>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f25a61ba9e0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f25a6209570>"}, "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": 16384, "_total_timesteps": 500, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1666108972224042507, "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": -31.768, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 4, "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-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.7.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "GPU Enabled": "False", "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:a2da6181374d8f6f709bd38b9af3291d621ba86c3469f62f1d632644aad109cb
+size 146555

ppo-LunarLander-v2/_stable_baselines3_version

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

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 0x7f25a61ba440>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f25a61ba4d0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f25a61ba560>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f25a61ba5f0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f25a61ba680>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f25a61ba710>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f25a61ba7a0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f25a61ba830>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f25a61ba8c0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f25a61ba950>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f25a61ba9e0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f25a6209570>"
+    },
+    "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": 16384,
+    "_total_timesteps": 500,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1666108972224042507,
+    "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": -31.768,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 4,
+    "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:dccbc6a975bb5c51db3a47bb2d5811208a17f0448305dff96825dc866ba2852a
+size 87545

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:64f6692cc85db17c121d064f0312b7fd12ad00e7d6a30d60d003dfe19b80efab
+size 43073

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-5.10.133+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Fri Aug 26 08:44:51 UTC 2022
+Python: 3.7.15
+Stable-Baselines3: 1.6.2
+PyTorch: 1.12.1+cu113
+GPU Enabled: False
+Numpy: 1.21.6
+Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": -238.72395665983203, "std_reward": 303.92327179935086, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-10-18T16:10:01.702525"}