upload 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: 266.95 +/- 18.09
+      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 0x7f94f22113a0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f94f2211430>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f94f22114c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f94f2211550>", "_build": "<function ActorCriticPolicy._build at 0x7f94f22115e0>", "forward": "<function ActorCriticPolicy.forward at 0x7f94f2211670>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f94f2211700>", "_predict": "<function ActorCriticPolicy._predict at 0x7f94f2211790>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f94f2211820>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f94f22118b0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f94f2211940>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f94f220e2d0>"}, "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": 1670692416608462450, "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": 248, "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:": "gAWVwwIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4BDAgABlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSC91c3IvbG9jYWwvbGliL3B5dGhvbjMuOC9kaXN0LXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/yZmZmZmZmoWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "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"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d778f03b27aa04b30f086d7374a4726889e3a71ecef09885fce8b51a4276c012
+size 147210

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 0x7f94f22113a0>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f94f2211430>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f94f22114c0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f94f2211550>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f94f22115e0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f94f2211670>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f94f2211700>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f94f2211790>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f94f2211820>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f94f22118b0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f94f2211940>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7f94f220e2d0>"
+    },
+    "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": 1670692416608462450,
+    "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": 248,
+    "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 sha256:71b5e332a82143d30b64368b7e9dd541eba2353cd4850e3c6c2104d0a65a472d
+size 87929

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:80041d48758bca4b5ba7b52f8df223e1a48feb608ee71e83a02974c0bc47bdc6
+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-5.10.133+-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": 266.9546758505911, "std_reward": 18.08927627101383, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-10T17:33:17.086934"}