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: 272.58 +/- 25.88
+      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 0x7a18654adc60>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a18654add00>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a18654adda0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a18654ade40>", "_build": "<function ActorCriticPolicy._build at 0x7a18654adee0>", "forward": "<function ActorCriticPolicy.forward at 0x7a18654adf80>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a18654ae020>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a18654ae0c0>", "_predict": "<function ActorCriticPolicy._predict at 0x7a18654ae160>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a18654ae200>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a18654ae2a0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a18654ae340>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7a18661195c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 901120, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1744965933772021289, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": 0.09887999999999997, "_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": 249, "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "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:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025", "Python": "3.11.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "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 sha256:69b0ab64329c97d01762a21556ba4322188936d3932f7536b9a3f351c48f99a9
+size 148057

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 0x7a18654adc60>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7a18654add00>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7a18654adda0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7a18654ade40>",
+        "_build": "<function ActorCriticPolicy._build at 0x7a18654adee0>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7a18654adf80>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7a18654ae020>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7a18654ae0c0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7a18654ae160>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7a18654ae200>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7a18654ae2a0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7a18654ae340>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7a18661195c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 901120,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1744965933772021289,
+    "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="
+    },
+    "_last_original_obs": null,
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": 0.09887999999999997,
+    "_stats_window_size": 100,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVDAwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQHM85FLFn7KMAWyUTQQBjAF0lEdAkNBYjB2wFHV9lChoBkdARpeo5xR2sGgHS7poCEdAkNFlhXr+pHV9lChoBkdAcI1uvllsg2gHS+FoCEdAkNHjiXIEKXV9lChoBkdAcAXXmNipemgHS/poCEdAkNImDxsl9nV9lChoBkdAcDsLofSx7mgHS/RoCEdAkNI/SpiqhnV9lChoBkdAciLxiobXH2gHS/xoCEdAkNKuYQarFXV9lChoBkdAcBNKL876pGgHS/1oCEdAkNLAfuCwr3V9lChoBkdAcF+DYAbQ1WgHTRoBaAhHQJDTfNQj2SN1fZQoaAZHQHBO7+98JD5oB0vlaAhHQJDTmmsNlRR1fZQoaAZHQHFcMYl6Z6VoB00BAWgIR0CQ06tsN2C/dX2UKGgGR0BwUI6QvHtGaAdNGQFoCEdAkNQ8BhhH9XV9lChoBkdAb3Q2BJ7LMmgHS+FoCEdAkNSJwsGxEHV9lChoBkdAcLjvYvnKXGgHS/JoCEdAkNTs/lhgE3V9lChoBkdAc1lixVyWA2gHS+RoCEdAkNVE6T4cm3V9lChoBkdAcHvUhV2ic2gHS/5oCEdAkNXWcnVoYnV9lChoBkdAcXV75Ec81WgHS+VoCEdAkNYmSZBsynV9lChoBkdAc3E7DVH4GmgHTUABaAhHQJDXSZtvXK91fZQoaAZHQHK14Lw4KhNoB0vQaAhHQJDXSQV9F4N1fZQoaAZHQG+7lPi1iONoB0vgaAhHQJDZvaK1og51fZQoaAZHQHFP2Ya5wwVoB0v8aAhHQJDbMslLOA11fZQoaAZHQHD+MawUxmFoB00PAWgIR0CQ249tMwlCdX2UKGgGR0Bt3eWSlnAZaAdL82gIR0CQ29jZL7GedX2UKGgGR0Bx9zhHbypaaAdL42gIR0CQ3MKf4AS4dX2UKGgGR0BupkB8x9G7aAdNAwFoCEdAkNzWXTmW+3V9lChoBkdAVN9FZxJd0WgHS75oCEdAkN6NIsiB5HV9lChoBkdAcXdtHQQcxWgHTQoBaAhHQJDe2A9V3ll1fZQoaAZHQHCc8274BWBoB00PAWgIR0CQ3uuJk5IZdX2UKGgGR0ByPo40dilSaAdL+2gIR0CQ3zezUqhEdX2UKGgGR0BKBQaBI4EPaAdLwWgIR0CQ4N3zMA3ldX2UKGgGR0ByTfIsAeaKaAdNBQFoCEdAkOFO0b961XV9lChoBkdAcjaezlcQiGgHS+ZoCEdAkOGHXyy2QXV9lChoBkdAcQtgyuZCwGgHTSEBaAhHQJDhv8iwB5p1fZQoaAZHQHLXJHI6r/9oB00RAWgIR0CQ4vy1NQCTdX2UKGgGR0BvzOwHJLdvaAdNDgFoCEdAkOTmjj7yhHV9lChoBkdAbqwTs6aLGmgHS/xoCEdAkOZGCEpRXXV9lChoBkdAcw3HjIaLoGgHS91oCEdAkOZNMGorF3V9lChoBkdAcQUpdKNADGgHS/5oCEdAkPtk3GXHBHV9lChoBkdAUxa/EfkmyGgHS8hoCEdAkPug4Otnw3V9lChoBkdAcHoxX4j8k2gHTRQBaAhHQJD71v2oNut1fZQoaAZHQEyPyFPBSDRoB0uvaAhHQJD8GtLcsUZ1fZQoaAZHQFZbWGRFI/ZoB0uqaAhHQJD8JNEgGKR1fZQoaAZHQHAiFBIFvAJoB0v0aAhHQJD8e3solUp1fZQoaAZHQHBMPzjFQ2xoB0vsaAhHQJD8uL9/BnB1fZQoaAZHQHN4lrhzeXRoB00qAWgIR0CQ/N9IPK+0dX2UKGgGR0ByN6pbUwztaAdNFgFoCEdAkP12wFC9iHV9lChoBkdAdCp6y0KJEmgHTU8BaAhHQJD9oRujynV1fZQoaAZHQHAxRwMpgCxoB00EAWgIR0CQ/lzV+Zw5dX2UKGgGR0Bxu5/x2B8QaAdNFAFoCEdAkP6c5fdAPnV9lChoBkdAcNF2UB4lhWgHTQABaAhHQJD+7bTMJQd1fZQoaAZHQHI1D2Bas6toB0voaAhHQJD/tGNJe3R1fZQoaAZHQHH0nkHUtqZoB0vpaAhHQJD/tSFXaJ11fZQoaAZHQHLVhm5DqnpoB00SAWgIR0CRAALAHmihdX2UKGgGR0BQ48+FDfFaaAdLrmgIR0CRAFXokiUxdX2UKGgGR0BwevPiT+vRaAdL52gIR0CRAJqGDcubdX2UKGgGR0Bxkj7O3UhFaAdL6mgIR0CRAN+V1Oj7dX2UKGgGR0Bvorj7yhBaaAdL8mgIR0CRAUeFtbcHdX2UKGgGR0BKgNsnAqNIaAdL1WgIR0CRAXe1a4c4dX2UKGgGR0BxB5AWznieaAdL/mgIR0CRAcoS+QEIdX2UKGgGR0BzeHFvQ4S6aAdNEwFoCEdAkQMWrS3LFHV9lChoBkdAcVK5byH2y2gHTUgBaAhHQJEDk9mpVCJ1fZQoaAZHQHFW9t2s7uFoB0vpaAhHQJEDxE/jbSJ1fZQoaAZHQHNgDAvcrRVoB0vTaAhHQJEEtbTtsvZ1fZQoaAZHQG3a7dadMCdoB000AWgIR0CRBNcmBvrGdX2UKGgGR0BwPaCcwxnGaAdNCwFoCEdAkQTlD4QBgnV9lChoBkdAcpTXtjTa02gHTUYBaAhHQJEFEngHeJp1fZQoaAZHQHC1xQizLOloB00TAWgIR0CRBXYSxqwhdX2UKGgGR0Bwy2w1R+BpaAdL8mgIR0CRBYBClabGdX2UKGgGR0BybiAZsKsuaAdL2mgIR0CRBiXbuc+adX2UKGgGR0ByAYL9deIEaAdL8mgIR0CRBiR15jYqdX2UKGgGR0ByXk6Lfk3kaAdNCQFoCEdAkQZQbuMMqnV9lChoBkdAcr5B/qgRLGgHTQABaAhHQJEGsjVx0dR1fZQoaAZHQG/s8v/R3NdoB0vkaAhHQJEG/Npudf91fZQoaAZHQHKPvwVj7Q9oB0vcaAhHQJEHL/dZaFF1fZQoaAZHQG9IircTJyRoB01GAWgIR0CRCRxlxwQ2dX2UKGgGR0BxdA9HMEA6aAdL6GgIR0CRCWQ1rIo3dX2UKGgGR0Bw8PJ4jbBXaAdNBAFoCEdAkQl3WFvhqHV9lChoBkdAT1MR8MNMG2gHS8doCEdAkQneanaWX3V9lChoBkdAcqrEgntv42gHTS4BaAhHQJEK/5tWMjx1fZQoaAZHQHBOat1ZDAtoB0v+aAhHQJELGjesPrh1fZQoaAZHQHEIiULUkOZoB0vpaAhHQJELItnPE891fZQoaAZHQHBfFsYVIqdoB0v0aAhHQJELdNBWxQl1fZQoaAZHQHJeKXv6TGJoB0veaAhHQJELoy1uzhR1fZQoaAZHQHIYMT8HfMxoB00ZAWgIR0CRC7fixVyWdX2UKGgGR0BtLGs90RvnaAdL7GgIR0CRDBtygf2cdX2UKGgGR0BxrFCzC1qnaAdNMQFoCEdAkQwiqMm4RXV9lChoBkdAckeRUWEbpGgHTQoBaAhHQJEMi1TisGR1fZQoaAZHQHGppSrHU+doB00GAWgIR0CRDTgSvkimdX2UKGgGR0ByhY9nscABaAdNGgFoCEdAkQ1wwTM7l3V9lChoBkdAcV/ib2Dg62gHTR0BaAhHQJEN6yprDZV1fZQoaAZHQG3moXj2i+NoB0v1aAhHQJEPPKKYRd11fZQoaAZHQHLz8KkVN6BoB0v5aAhHQJEPyweNkvt1fZQoaAZHQHGg/nOjZctoB00WAWgIR0CRD8/5+H8CdX2UKGgGR0BwooFX7tRfaAdNHQFoCEdAkRA+chC+lHV9lChoBkdAcypVlwtJ4GgHS+JoCEdAkREIzzmOl3V9lChoBkdAcYR1UVBUrGgHS+toCEdAkREsRYigTXV9lChoBkdAcj05lvqC6GgHTQYBaAhHQJEROmQ8wHt1fZQoaAZHQHC0BHbypaRoB00KAWgIR0CREdLDhtLtdX2UKGgGR0Bxnx8BuGbkaAdL7GgIR0CREl+5OJtSdX2UKGgGR0By4pHhCMP0aAdNMgFoCEdAkRKNDx9XtHV9lChoBkdAcJB4vN/vv2gHTQ0BaAhHQJESslb/wRZ1ZS4="
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 249,
+    "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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
+        "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:": "gAWV1gIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwiVAZcAiQFTAJROhZQpjAFflIWUjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjExL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lIwEZnVuY5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUS4RDCPiAANgPEogKlEMAlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTEvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpRoAIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaCF9lH2UKGgYjARmdW5jlIwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBmMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHP8mZmZmZmZqFlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="
+    },
+    "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 sha256:8480878c964f9c2c87fdf28a6446599eb00e63c0b30e0caf480b5a0217344f93
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:08b107de617affd6102434758045c1b92038a9165ca1bd46f4ad52d495a38cb7
+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-6.1.123+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sun Mar 30 16:01:29 UTC 2025
+- Python: 3.11.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.6.0+cu124
+- GPU Enabled: True
+- Numpy: 2.0.2
+- 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:bdb765d850f10da8eb77dd1077a34933fdfebede66974d9090a5410fc13962d2
+size 144436

results.json

@@ -0,0 +1 @@
+{"mean_reward": 272.58321184127965, "std_reward": 25.88475691916565, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-04-18T09:05:11.584339"}