first trained model uploaded!

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: 251.24 +/- 61.25
+      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 0x7f5ce0877b50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5ce0877be0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5ce0877c70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5ce0877d00>", "_build": "<function ActorCriticPolicy._build at 0x7f5ce0877d90>", "forward": "<function ActorCriticPolicy.forward at 0x7f5ce0877e20>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f5ce0877eb0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5ce0877f40>", "_predict": "<function ActorCriticPolicy._predict at 0x7f5ce0880040>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5ce08800d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5ce0880160>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5ce08801f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f5ce0a04500>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 800768, "_total_timesteps": 800000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1720960699198516033, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAJrXLjy2ErU/8nkIPy13jj3RqCW84BqfvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0009600000000000719, "_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": 4890, "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": 1, "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, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.3.0+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 sha256:0588303e9b464d34a5fb2bee5d8400cc19a3e914e4e741af2697b72adeb7b3c4
+size 147314

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 0x7f5ce0877b50>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f5ce0877be0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f5ce0877c70>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f5ce0877d00>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f5ce0877d90>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f5ce0877e20>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f5ce0877eb0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f5ce0877f40>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f5ce0880040>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f5ce08800d0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f5ce0880160>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f5ce08801f0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7f5ce0a04500>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 800768,
+    "_total_timesteps": 800000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1720960699198516033,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAJrXLjy2ErU/8nkIPy13jj3RqCW84BqfvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": null,
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.0009600000000000719,
+    "_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": 4890,
+    "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": 1,
+    "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:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+    },
+    "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:feda28690f032c140cc9c28619f672318a49b9dbe31af064beae96801a3398f0
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:472a7653c0ed3078b4ca083529eff923293c18fec42989342ea2b4c692b62613
+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-6.1.85+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.3.0+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": 251.2431455, "std_reward": 61.25251671034251, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-07-14T13:17:35.630617"}