Upload PPO LunarLander-v2 trained agent

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+replay.mp4 filter=lfs diff=lfs merge=lfs -text

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: 252.37 +/- 16.78
+      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 0x79be3154fc40>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79be3154fce0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79be3154fd80>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79be3154fe20>", "_build": "<function ActorCriticPolicy._build at 0x79be3154fec0>", "forward": "<function ActorCriticPolicy.forward at 0x79be3154ff60>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x79be31558040>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79be315580e0>", "_predict": "<function ActorCriticPolicy._predict at 0x79be31558180>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79be31558220>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79be315582c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x79be31558360>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x79be4ce55900>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1739309090684476958, "learning_rate": 0.0003, "tensorboard_log": null, "_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, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVPAwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHFeMHGCI1uMAWyUTRIBjAF0lEdAkajBUWEbpHV9lChoBkdAcUZ9mHxjKGgHTS8BaAhHQJGpznEETxp1fZQoaAZHQG8zCTUy57RoB006AWgIR0CRqpw3YL9ddX2UKGgGR0BwxVdD6WPcaAdN9wFoCEdAkaqcBuGbkXV9lChoBkdAbryWMS9M9WgHTS0BaAhHQJGqt4/u9e11fZQoaAZHQG6/kauOjqRoB00zAWgIR0CRq2v8IiTudX2UKGgGR0Bvu3WFvhqCaAdNEAFoCEdAkavtD2Jzk3V9lChoBkdAWkXLMcIZ62gHTegDaAhHQJGr9pGnXNF1fZQoaAZHQG7vNIClrM1oB02nAWgIR0CRrP4DcM3IdX2UKGgGR0BkYoiC8OCoaAdN6ANoCEdAka1N8NQTEnV9lChoBkdAbu1/lQuVX2gHTS0BaAhHQJGtbpV0cOt1fZQoaAZHQHIfGvbGm1poB00cAWgIR0CRrhHHWBjGdX2UKGgGR0BvIkXN1QqJaAdNWAFoCEdAka5HuRcNY3V9lChoBkdAcaEN2ki2UmgHTSsBaAhHQJGuZNRFZxJ1fZQoaAZHQD7LVnVXmvJoB0vZaAhHQJGvSgte2NN1fZQoaAZHQHAihJmNBGBoB02NAWgIR0CRsromois5dX2UKGgGR0BxNqkZaV2SaAdNVQFoCEdAkbLyFPBSDXV9lChoBkdAbf2umrKeTWgHTT4BaAhHQJGzZ+rlvIh1fZQoaAZHQG/WFsYVIqdoB00rAWgIR0CRs3FRpDeCdX2UKGgGR0BxvfUgB91EaAdNNQFoCEdAkbPC3PRiPXV9lChoBkdAbZYovSMLnmgHTREBaAhHQJGz1WluWKN1fZQoaAZHQHEPbiqABktoB00oAWgIR0CRtImEXcgydX2UKGgGR0BwrQFV1fVqaAdNTgFoCEdAkbVOTibUgHV9lChoBkdAcm+zf779AGgHTRsBaAhHQJG1pd/rjYJ1fZQoaAZHQHDwWS+xnnNoB00SAWgIR0CRtpl41P30dX2UKGgGR0BtqFVea8YiaAdNNwFoCEdAkbaqbONYKnV9lChoBkdARLxi1AqusGgHS+hoCEdAkbaxDgIhQnV9lChoBkdAcYVvUBnzx2gHTZMBaAhHQJG2zROUMXt1fZQoaAZHQG3Te4TbnHNoB01RAWgIR0CRtunCwbEQdX2UKGgGR0BwboL8aXKKaAdNLwFoCEdAkbcYFeOXFHV9lChoBkdAb9+XQ+lj3GgHTU8BaAhHQJG4D6InBtV1fZQoaAZHQHGdOyu6mO5oB00lAWgIR0CRuyLuhK15dX2UKGgGR0BwrDbHp8neaAdNLwFoCEdAkbu2mxdIG3V9lChoBkdAb5jFn7Hhj2gHTUEBaAhHQJG817mdRSB1fZQoaAZHQG8iOYYzi0hoB000AWgIR0CRvaoLXtjTdX2UKGgGR0BxcA6ySmqHaAdNHQFoCEdAkb20cS5AhXV9lChoBkdAcAroE0SAY2gHTWcBaAhHQJG+p/gBLf11fZQoaAZHQG6wSElE7XBoB01rAWgIR0CRvvgiNbTudX2UKGgGR0BvBBuhsZYQaAdNFQFoCEdAkb+1F6RhdHV9lChoBkdAcfEVMVUMomgHTTEBaAhHQJG/9rLyMDR1fZQoaAZHQG7SY7aIvaloB00+AWgIR0CRwHc3EQ5FdX2UKGgGR0Bys8wrUb1iaAdNQQFoCEdAkcDcI7eVLXV9lChoBkdAcwK4n4O+ZmgHTXMBaAhHQJHBEWnCO3l1fZQoaAZHQHKvYcrAgxJoB01rAWgIR0CRwcmA9V3mdX2UKGgGR8AyOkXDWK/EaAdL32gIR0CRwqaCcwxndX2UKGgGR0BxgPFLnLaFaAdNUgFoCEdAkcLhY3eenXV9lChoBkdATn3NA1Nxl2gHS9BoCEdAkcQr8rI5pHV9lChoBkdAcRhtUGVzIWgHTRgBaAhHQJHaZ7w8W9F1fZQoaAZHQEz0lenhsIpoB0v+aAhHQJHbNLFn7Hh1fZQoaAZHQEerTUAksz5oB0vlaAhHQJHbR6u4gA91fZQoaAZHQHG0ynk1dgRoB00iAWgIR0CR25/FzdULdX2UKGgGR0BRxAkHD766aAdLwmgIR0CR3CAmReTndX2UKGgGR0Btr+nVG0/oaAdNNAFoCEdAkd36vzOHFnV9lChoBkdAcR862fChvmgHTSEBaAhHQJHeWveP7vZ1fZQoaAZHQHJNW+K0lZ5oB00uAWgIR0CR3oUlAu7IdX2UKGgGR0Bx5/uKGcnWaAdNwQJoCEdAkd60JKJ2uHV9lChoBkdAb/ypobn5i2gHTTIBaAhHQJHfW+49X911fZQoaAZHQHKBb4etCAtoB00kAWgIR0CR4F4TsY2sdX2UKGgGR0Bw6e7btZ3caAdNBwFoCEdAkeBoUrTYunV9lChoBkdAbjxYnv2GqWgHTV0BaAhHQJHhUZsKsuF1fZQoaAZHQHCrHX7Lt/poB006AWgIR0CR4jJgLJCCdX2UKGgGR0ByzkqJ/G2kaAdNGAFoCEdAkeQogRsdk3V9lChoBkdAcNfUTL4etGgHTUsBaAhHQJHk951Ng0F1fZQoaAZHQHFuG7SRbKRoB01fAWgIR0CR5Qqy4Wk8dX2UKGgGR0BxzDM4cWCVaAdNQgFoCEdAkeWeTzND+nV9lChoBkdAcMuxcVxjrmgHTTgBaAhHQJHmXbL2YfJ1fZQoaAZHQHIldATqSoxoB01UAWgIR0CR5r5eJHiFdX2UKGgGR0BwZgHiWE9MaAdNAQFoCEdAkebHlKbrknV9lChoBkdAcgest03fh2gHTT8BaAhHQJHoer7wazh1fZQoaAZHQHIAE0vXbudoB00XAWgIR0CR6JWmxdIHdX2UKGgGR0Bv0ir92ovSaAdNMwFoCEdAkeifVAiV0XV9lChoBkdAce8NqQA+6mgHTZoDaAhHQJHpSlJpWWB1fZQoaAZHQHDYVeWv8qFoB00VAWgIR0CR6XqREF4cdX2UKGgGR0BtLgX668QJaAdNFQFoCEdAkepK4YrJ83V9lChoBkdAcBhfkWAPNGgHTW4BaAhHQJHsAH1OCXh1fZQoaAZHQHGSnXiBGx5oB00zAWgIR0CR7An6l+EzdX2UKGgGR0BwYWlj3EhraAdNBQFoCEdAkex3QMQVbnV9lChoBkdAcjeQhwEQoWgHTQYBaAhHQJHtO4pc5bR1fZQoaAZHQG1PPlU6xPhoB00jAWgIR0CR7iPGyX2NdX2UKGgGR0BuDytq59VnaAdNFgFoCEdAke5LlaKUFHV9lChoBkdAcM0BSDRMOGgHTQ0BaAhHQJHu+EsasIV1fZQoaAZHQG/1Hmig00poB00jAWgIR0CR70k/r0J4dX2UKGgGR0BwJGdH2AXmaAdNKAFoCEdAke/BzV+ZxHV9lChoBkdAcXTHlfZ26mgHTQwBaAhHQJHwXUhFEzB1fZQoaAZHQG45bJwKjSJoB00TAWgIR0CR8ZIgNgBtdX2UKGgGR0ByAglzEJjUaAdNOQFoCEdAkfHOERJ2+3V9lChoBkdAcBJ2rGR3eWgHTV4BaAhHQJHy34Irvst1fZQoaAZHQHJOEXtShrZoB00iAWgIR0CR8ui7kGRndX2UKGgGR0BvqtIZqEeyaAdNDwFoCEdAkfQNXLeQ+3V9lChoBkdAcB8b8WKuS2gHTboCaAhHQJH0TPGACnx1fZQoaAZHQHI5GFSKm9BoB00TAWgIR0CR9KA1ejVQdX2UKGgGR0BsvGuaF23baAdNhQFoCEdAkfS8LORkmXV9lChoBkdAcQ+F5OafBmgHTTMBaAhHQJH1Hzwtrbh1fZQoaAZHQFHoFi8WbgFoB0vXaAhHQJH1c4Pwuul1fZQoaAZHQHAHwA2hqTNoB00cAWgIR0CR9knjQzDXdX2UKGgGR0BxlJWq94/vaAdNIgFoCEdAkfaUkKNQ03V9lChoBkdAcV7h4MWoFWgHTVsBaAhHQJH3Wt4iX6Z1fZQoaAZHQGzT7tRekYZoB00mAWgIR0CR+ItmL9/CdX2UKGgGR0BvQHmYBvJjaAdNGQFoCEdAkfjxOgxrSHV9lChoBkdAcNm6vaDf32gHTVEBaAhHQJH5HZlFtsN1ZS4="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 248, "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": 16, "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, "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": "3.11.11", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.5.1+cu124", "GPU Enabled": "True", "Numpy": "1.26.4", "Cloudpickle": "3.1.1", "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 sha256:3ac8f15d2e3741995e449e6b8aa9ef9225cecdaab6fb05467783a250157605fb
+size 148124

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 0x79be3154fc40>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x79be3154fce0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x79be3154fd80>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x79be3154fe20>",
+        "_build": "<function ActorCriticPolicy._build at 0x79be3154fec0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x79be3154ff60>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x79be31558040>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x79be315580e0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x79be31558180>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x79be31558220>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x79be315582c0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x79be31558360>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x79be4ce55900>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1739309090684476958,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_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,
+    "_stats_window_size": 100,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVPAwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHFeMHGCI1uMAWyUTRIBjAF0lEdAkajBUWEbpHV9lChoBkdAcUZ9mHxjKGgHTS8BaAhHQJGpznEETxp1fZQoaAZHQG8zCTUy57RoB006AWgIR0CRqpw3YL9ddX2UKGgGR0BwxVdD6WPcaAdN9wFoCEdAkaqcBuGbkXV9lChoBkdAbryWMS9M9WgHTS0BaAhHQJGqt4/u9e11fZQoaAZHQG6/kauOjqRoB00zAWgIR0CRq2v8IiTudX2UKGgGR0Bvu3WFvhqCaAdNEAFoCEdAkavtD2Jzk3V9lChoBkdAWkXLMcIZ62gHTegDaAhHQJGr9pGnXNF1fZQoaAZHQG7vNIClrM1oB02nAWgIR0CRrP4DcM3IdX2UKGgGR0BkYoiC8OCoaAdN6ANoCEdAka1N8NQTEnV9lChoBkdAbu1/lQuVX2gHTS0BaAhHQJGtbpV0cOt1fZQoaAZHQHIfGvbGm1poB00cAWgIR0CRrhHHWBjGdX2UKGgGR0BvIkXN1QqJaAdNWAFoCEdAka5HuRcNY3V9lChoBkdAcaEN2ki2UmgHTSsBaAhHQJGuZNRFZxJ1fZQoaAZHQD7LVnVXmvJoB0vZaAhHQJGvSgte2NN1fZQoaAZHQHAihJmNBGBoB02NAWgIR0CRsromois5dX2UKGgGR0BxNqkZaV2SaAdNVQFoCEdAkbLyFPBSDXV9lChoBkdAbf2umrKeTWgHTT4BaAhHQJGzZ+rlvIh1fZQoaAZHQG/WFsYVIqdoB00rAWgIR0CRs3FRpDeCdX2UKGgGR0BxvfUgB91EaAdNNQFoCEdAkbPC3PRiPXV9lChoBkdAbZYovSMLnmgHTREBaAhHQJGz1WluWKN1fZQoaAZHQHEPbiqABktoB00oAWgIR0CRtImEXcgydX2UKGgGR0BwrQFV1fVqaAdNTgFoCEdAkbVOTibUgHV9lChoBkdAcm+zf779AGgHTRsBaAhHQJG1pd/rjYJ1fZQoaAZHQHDwWS+xnnNoB00SAWgIR0CRtpl41P30dX2UKGgGR0BtqFVea8YiaAdNNwFoCEdAkbaqbONYKnV9lChoBkdARLxi1AqusGgHS+hoCEdAkbaxDgIhQnV9lChoBkdAcYVvUBnzx2gHTZMBaAhHQJG2zROUMXt1fZQoaAZHQG3Te4TbnHNoB01RAWgIR0CRtunCwbEQdX2UKGgGR0BwboL8aXKKaAdNLwFoCEdAkbcYFeOXFHV9lChoBkdAb9+XQ+lj3GgHTU8BaAhHQJG4D6InBtV1fZQoaAZHQHGdOyu6mO5oB00lAWgIR0CRuyLuhK15dX2UKGgGR0BwrDbHp8neaAdNLwFoCEdAkbu2mxdIG3V9lChoBkdAb5jFn7Hhj2gHTUEBaAhHQJG817mdRSB1fZQoaAZHQG8iOYYzi0hoB000AWgIR0CRvaoLXtjTdX2UKGgGR0BxcA6ySmqHaAdNHQFoCEdAkb20cS5AhXV9lChoBkdAcAroE0SAY2gHTWcBaAhHQJG+p/gBLf11fZQoaAZHQG6wSElE7XBoB01rAWgIR0CRvvgiNbTudX2UKGgGR0BvBBuhsZYQaAdNFQFoCEdAkb+1F6RhdHV9lChoBkdAcfEVMVUMomgHTTEBaAhHQJG/9rLyMDR1fZQoaAZHQG7SY7aIvaloB00+AWgIR0CRwHc3EQ5FdX2UKGgGR0Bys8wrUb1iaAdNQQFoCEdAkcDcI7eVLXV9lChoBkdAcwK4n4O+ZmgHTXMBaAhHQJHBEWnCO3l1fZQoaAZHQHKvYcrAgxJoB01rAWgIR0CRwcmA9V3mdX2UKGgGR8AyOkXDWK/EaAdL32gIR0CRwqaCcwxndX2UKGgGR0BxgPFLnLaFaAdNUgFoCEdAkcLhY3eenXV9lChoBkdATn3NA1Nxl2gHS9BoCEdAkcQr8rI5pHV9lChoBkdAcRhtUGVzIWgHTRgBaAhHQJHaZ7w8W9F1fZQoaAZHQEz0lenhsIpoB0v+aAhHQJHbNLFn7Hh1fZQoaAZHQEerTUAksz5oB0vlaAhHQJHbR6u4gA91fZQoaAZHQHG0ynk1dgRoB00iAWgIR0CR25/FzdULdX2UKGgGR0BRxAkHD766aAdLwmgIR0CR3CAmReTndX2UKGgGR0Btr+nVG0/oaAdNNAFoCEdAkd36vzOHFnV9lChoBkdAcR862fChvmgHTSEBaAhHQJHeWveP7vZ1fZQoaAZHQHJNW+K0lZ5oB00uAWgIR0CR3oUlAu7IdX2UKGgGR0Bx5/uKGcnWaAdNwQJoCEdAkd60JKJ2uHV9lChoBkdAb/ypobn5i2gHTTIBaAhHQJHfW+49X911fZQoaAZHQHKBb4etCAtoB00kAWgIR0CR4F4TsY2sdX2UKGgGR0Bw6e7btZ3caAdNBwFoCEdAkeBoUrTYunV9lChoBkdAbjxYnv2GqWgHTV0BaAhHQJHhUZsKsuF1fZQoaAZHQHCrHX7Lt/poB006AWgIR0CR4jJgLJCCdX2UKGgGR0ByzkqJ/G2kaAdNGAFoCEdAkeQogRsdk3V9lChoBkdAcNfUTL4etGgHTUsBaAhHQJHk951Ng0F1fZQoaAZHQHFuG7SRbKRoB01fAWgIR0CR5Qqy4Wk8dX2UKGgGR0BxzDM4cWCVaAdNQgFoCEdAkeWeTzND+nV9lChoBkdAcMuxcVxjrmgHTTgBaAhHQJHmXbL2YfJ1fZQoaAZHQHIldATqSoxoB01UAWgIR0CR5r5eJHiFdX2UKGgGR0BwZgHiWE9MaAdNAQFoCEdAkebHlKbrknV9lChoBkdAcgest03fh2gHTT8BaAhHQJHoer7wazh1fZQoaAZHQHIAE0vXbudoB00XAWgIR0CR6JWmxdIHdX2UKGgGR0Bv0ir92ovSaAdNMwFoCEdAkeifVAiV0XV9lChoBkdAce8NqQA+6mgHTZoDaAhHQJHpSlJpWWB1fZQoaAZHQHDYVeWv8qFoB00VAWgIR0CR6XqREF4cdX2UKGgGR0BtLgX668QJaAdNFQFoCEdAkepK4YrJ83V9lChoBkdAcBhfkWAPNGgHTW4BaAhHQJHsAH1OCXh1fZQoaAZHQHGSnXiBGx5oB00zAWgIR0CR7An6l+EzdX2UKGgGR0BwYWlj3EhraAdNBQFoCEdAkex3QMQVbnV9lChoBkdAcjeQhwEQoWgHTQYBaAhHQJHtO4pc5bR1fZQoaAZHQG1PPlU6xPhoB00jAWgIR0CR7iPGyX2NdX2UKGgGR0BuDytq59VnaAdNFgFoCEdAke5LlaKUFHV9lChoBkdAcM0BSDRMOGgHTQ0BaAhHQJHu+EsasIV1fZQoaAZHQG/1Hmig00poB00jAWgIR0CR70k/r0J4dX2UKGgGR0BwJGdH2AXmaAdNKAFoCEdAke/BzV+ZxHV9lChoBkdAcXTHlfZ26mgHTQwBaAhHQJHwXUhFEzB1fZQoaAZHQG45bJwKjSJoB00TAWgIR0CR8ZIgNgBtdX2UKGgGR0ByAglzEJjUaAdNOQFoCEdAkfHOERJ2+3V9lChoBkdAcBJ2rGR3eWgHTV4BaAhHQJHy34Irvst1fZQoaAZHQHJOEXtShrZoB00iAWgIR0CR8ui7kGRndX2UKGgGR0BvqtIZqEeyaAdNDwFoCEdAkfQNXLeQ+3V9lChoBkdAcB8b8WKuS2gHTboCaAhHQJH0TPGACnx1fZQoaAZHQHI5GFSKm9BoB00TAWgIR0CR9KA1ejVQdX2UKGgGR0BsvGuaF23baAdNhQFoCEdAkfS8LORkmXV9lChoBkdAcQ+F5OafBmgHTTMBaAhHQJH1Hzwtrbh1fZQoaAZHQFHoFi8WbgFoB0vXaAhHQJH1c4Pwuul1fZQoaAZHQHAHwA2hqTNoB00cAWgIR0CR9knjQzDXdX2UKGgGR0BxlJWq94/vaAdNIgFoCEdAkfaUkKNQ03V9lChoBkdAcV7h4MWoFWgHTVsBaAhHQJH3Wt4iX6Z1fZQoaAZHQGzT7tRekYZoB00mAWgIR0CR+ItmL9/CdX2UKGgGR0BvQHmYBvJjaAdNGQFoCEdAkfjxOgxrSHV9lChoBkdAcNm6vaDf32gHTVEBaAhHQJH5HZlFtsN1ZS4="
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 248,
+    "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": 16,
+    "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,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPzOpKjBVMmGFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6a568281b9fc12685291a97fe8a19245b97fce8644c429794447830bcaf6f27a
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:91f2d727bb4f8f445d0197a35213b5985103d1c16a7aff330cbc1f3301169ff3
+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: 3.11.11
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.5.1+cu124
+- GPU Enabled: True
+- Numpy: 1.26.4
+- Cloudpickle: 3.1.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:47915059574feff85450dfe45d785a80bf670893058de8d5ece2b02969b45e43
+size 189876

results.json

@@ -0,0 +1 @@
+{"mean_reward": 252.36731920662402, "std_reward": 16.777611014070512, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-02-11T21:47:08.877249"}