totaldungeon commited on
Commit
287626c
1 Parent(s): 8f99064

Upload PPO LunarLander-v2 trained agent

Browse files
README.md ADDED
@@ -0,0 +1,37 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: stable-baselines3
3
+ tags:
4
+ - LunarLander-v2
5
+ - deep-reinforcement-learning
6
+ - reinforcement-learning
7
+ - stable-baselines3
8
+ model-index:
9
+ - name: PPO
10
+ results:
11
+ - task:
12
+ type: reinforcement-learning
13
+ name: reinforcement-learning
14
+ dataset:
15
+ name: LunarLander-v2
16
+ type: LunarLander-v2
17
+ metrics:
18
+ - type: mean_reward
19
+ value: 248.41 +/- 17.16
20
+ name: mean_reward
21
+ verified: false
22
+ ---
23
+
24
+ # **PPO** Agent playing **LunarLander-v2**
25
+ This is a trained model of a **PPO** agent playing **LunarLander-v2**
26
+ using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
27
+
28
+ ## Usage (with Stable-baselines3)
29
+ TODO: Add your code
30
+
31
+
32
+ ```python
33
+ from stable_baselines3 import ...
34
+ from huggingface_sb3 import load_from_hub
35
+
36
+ ...
37
+ ```
config.json ADDED
@@ -0,0 +1 @@
 
 
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 0x787c7dcf6320>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x787c7dcf63b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x787c7dcf6440>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x787c7dcf64d0>", "_build": "<function ActorCriticPolicy._build at 0x787c7dcf6560>", "forward": "<function ActorCriticPolicy.forward at 0x787c7dcf65f0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x787c7dcf6680>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x787c7dcf6710>", "_predict": "<function ActorCriticPolicy._predict at 0x787c7dcf67a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x787c7dcf6830>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x787c7dcf68c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x787c7dcf6950>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x787c7dc97e80>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1708755855903415310, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAD+qb1Ylp4/fcmYvbQIgL7/zay90nfFPAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.00044800000000000395, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVQwwAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpRHQGvc1Sn+AEuMAWyUTVkBjAF0lEdAoAUF+qioKnV9lChoBkdAb2A5FPSDy2gHTZEBaAhHQKAGIcDKYAt1fZQoaAZHQG+kC1JDmbNoB02AAWgIR0CgB9uuRs/IdX2UKGgGR0BtiuLgn+hoaAdNogFoCEdAoAkMQNCqqHV9lChoBkdAXx/2OAAhjmgHTegDaAhHQKAMfOerdWR1fZQoaAZHQGTHidBjWkJoB03oA2gIR0CgEEB8IAwPdX2UKGgGR0AzPZyuIRAbaAdNGgFoCEdAoBFBNj9XLnV9lChoBkdAb6/qpLmITGgHTe0CaAhHQKAUeo7V8Tl1fZQoaAZHQG9x77Kq4pdoB02jAWgIR0CgFa0k4WDZdX2UKGgGR0Bxf3l7tzCDaAdNfQFoCEdAoBdkEvCdjHV9lChoBkdAcZgmdRR/E2gHTXoBaAhHQKAYcuRLbpN1fZQoaAZHQGOColt0mt1oB03oA2gIR0CgG/do371qdX2UKGgGR0Bw5wAyVObiaAdNrwFoCEdAoB3LHKfWc3V9lChoBkdAcOSnDziCKGgHTYABaAhHQKAe3aQFLWZ1fZQoaAZHQHGUvaURnOBoB01uAWgIR0CgH+lUp/gBdX2UKGgGR0Bwlq03Ov+waAdNhQFoCEdAoCGazzErG3V9lChoBkdAbfoVdonKGWgHTZ8BaAhHQKAiw+mm+Cd1fZQoaAZHQHDNkk0Jng5oB01OAWgIR0CgI63qiXY2dX2UKGgGR0BtXOGwiaAnaAdNgAFoCEdAoCVlI9TxXnV9lChoBkdARWkt/WlMy2gHS/JoCEdAoCYbp5eJHnV9lChoBkdAaiVf779AHGgHTV0BaAhHQKAnNbjcVQB1fZQoaAZHQG+Dj2SMcZNoB02rAWgIR0CgKZuzhP0qdX2UKGgGR0Bq3PpB5X2eaAdNkQFoCEdAoCshTQ3PzHV9lChoBkdAbfphNM495mgHTXQBaAhHQKAsywkgOjJ1fZQoaAZHQG3SpfQa73BoB03UA2gIR0CgL69bX6IndX2UKGgGR0Bvynhl18suaAdNVgFoCEdAoDFF+NLlFXV9lChoBkdAcG0hWo3rEGgHTWQBaAhHQKAyS/NZ/1B1fZQoaAZHQGn3gYP5HmRoB01hAWgIR0CgM07HAAQydX2UKGgGR0ByZlp5/smfaAdNMgFoCEdAoDTOETQE6nV9lChoBkdAb6jJ9RaX8mgHTXIBaAhHQKA11pUxVQ11fZQoaAZHQGvOYS6DoQpoB01iAWgIR0CgNtXCsOoYdX2UKGgGR0BuXWFWXC0oaAdNpgFoCEdAoDifYlIEsHV9lChoBkdAcETmp2ll9WgHTW0BaAhHQKA5pm8ujAV1fZQoaAZHQGvh64+bExZoB01+AWgIR0CgO13aakRBdX2UKGgGR0BvrpPAO8TSaAdNYwFoCEdAoDxethd+onV9lChoBkdAb+LBxgiNbWgHTbgBaAhHQKA9ph73PAx1fZQoaAZHQHEabvkRzzVoB01tAWgIR0CgP3OP/7zkdX2UKGgGR0BwMTgiu+yraAdNqQFoCEdAoED9bJOnEXV9lChoBkdAb13BC2MKkWgHTWgBaAhHQKBDK3EyckN1fZQoaAZHQHFr/ZVXFLpoB02EAWgIR0CgRDtYKYzBdX2UKGgGR0Bs8yY3Ns3yaAdNVgFoCEdAoEU7HGS6lXV9lChoBkdAcCZGrjo6jmgHTVIBaAhHQKBG1g0j1PF1fZQoaAZHQHIEhhpg1FZoB02BAWgIR0CgR+qgZjx1dX2UKGgGR0BxJ1FMIu5CaAdNeAFoCEdAoEj7Z+QU6HV9lChoBkdAX1w2bXpW3mgHTegDaAhHQKBMb/o7muF1fZQoaAZHQG6t59/jKgZoB01kAWgIR0CgTgxRdhRZdX2UKGgGR0Bu872Jzkp7aAdNZwFoCEdAoE8QTZg5R3V9lChoBkdAcXXK5kK/mGgHTbEBaAhHQKBQRYmLLp11fZQoaAZHQG5aBi1AqutoB012AWgIR0CgUfd5Y5ktdX2UKGgGR0BuEPvQWvbHaAdNfwFoCEdAoFMaQtBfKXV9lChoBkdACFW/ag261GgHTRoBaAhHQKBT42l2vB91fZQoaAZHQHEUEupS75FoB01wAWgIR0CgVYcGTs6adX2UKGgGR0BX/ECvHLidaAdN6ANoCEdAoFmpcJMQE3V9lChoBkdAYJm+KTB68mgHTegDaAhHQKBdiOf/WDp1fZQoaAZHQHCRHAZbY9RoB03MAWgIR0CgXshk7OmjdX2UKGgGR0Bvr4vvjOs1aAdNaAFoCEdAoGBpuuRs/XV9lChoBkdAcFe8KG+K0mgHTWsBaAhHQKBha3mV7hN1fZQoaAZHQG/q/zz3AVRoB02xAWgIR0CgYqSXt0FKdX2UKGgGR0BwCHoq0+khaAdNYwFoCEdAoGQywD/2kHV9lChoBkdAbreM/hVENWgHTUkBaAhHQKBlKFX7tRh1fZQoaAZHQGroMoMKCxxoB02XAWgIR0CgZkvE87p3dX2UKGgGR0BwExhsqJ/HaAdNTgFoCEdAoGfdJtix3XV9lChoBkdAYebnlGPPs2gHTegDaAhHQKBrZL0SRKZ1fZQoaAZHQG+HbPppvgpoB01vAWgIR0CgbGlYEGJOdX2UKGgGR0BycKt/4IrwaAdNOQJoCEdAoG6gZsKsuHV9lChoBkdAbk3h0hePaWgHTaUBaAhHQKBwLutwJgN1fZQoaAZHQHISwnH/951oB01NAWgIR0CgcWNBv73xdX2UKGgGR0BuC4jUutfYaAdNnQFoCEdAoHOTGJemenV9lChoBkdAbjOJHiFTN2gHTWsBaAhHQKB0n4+KTB91fZQoaAZHQECAUi6g/TtoB00VAWgIR0CgdWsZxaPkdX2UKGgGR0BvPw9FF2FGaAdNzAFoCEdAoHdXL5h0AHV9lChoBkdAcBCRTCLuQmgHTVgBaAhHQKB4Vh99c8l1fZQoaAZHQHDU9vKlpGpoB00xAmgIR0CgeoMaS9uhdX2UKGgGR0BwE0MRYigTaAdNNQFoCEdAoHtgaNuLrHV9lChoBkdAcY7Hp8neBWgHTYoBaAhHQKB8eGB4D9x1fZQoaAZHQHDgvQrtmcxoB01UAWgIR0CgfgO76Hj7dX2UKGgGR0BwvmagElmfaAdNXQFoCEdAoH8HiPyTZHV9lChoBkdAbb3D2rXDnGgHTUQBaAhHQKB//xFRYRx1fZQoaAZHQG/sbiyY5T9oB01jAWgIR0CggZ/9Hc1wdX2UKGgGR0BA8qcNH6MzaAdNDQFoCEdAoIJk+aBqbnV9lChoBkdAcCbgQYk3TGgHTWgBaAhHQKCDYchkiEB1fZQoaAZHQHBt/EfkmyBoB02lA2gIR0Cghpv2oNutdX2UKGgGR0Bx5IsiB5HFaAdNJgJoCEdAoIltNzr/sHV9lChoBkdAcQh+lCTlk2gHTYcDaAhHQKCNBV8Ti851fZQoaAZHQGVv5NO/L1VoB03oA2gIR0CgkH5nlGPQdX2UKGgGR0BsIc3IdU83aAdNdQFoCEdAoJGQ1+AmRnV9lChoBkdAcRBU+cH4XWgHTbABaAhHQKCSxi5uqFR1fZQoaAZHQHCo71ZkkKNoB00uAWgIR0CglEOlGgBcdX2UKGgGR0BvkBh4MWoFaAdNVgFoCEdAoJU+IRAbAHV9lChoBkdAcdZsZHd43WgHTTwBaAhHQKCWLDVpbll1fZQoaAZHQHCvA1vVEuxoB00gAWgIR0Cgl6k3bVSXdX2UKGgGR0BxM1BJI1+BaAdNRQFoCEdAoJiQFJQLu3V9lChoBkdAcHL8xsVLz2gHTWcBaAhHQKCZk8jAzpJ1fZQoaAZHQGEGqwpvxYtoB03oA2gIR0CgnPj/VAiWdX2UKGgGR0Bw1G8yvcJuaAdN8gFoCEdAoJ8LYNAkcHV9lChoBkdAcUPz4UN8V2gHTUEBaAhHQKCgQKTjebd1fZQoaAZHQFyLVqN6w+toB03oA2gIR0CgpE0jcEeRdX2UKGgGR0Bm803yZrpJaAdN6ANoCEdAoKfseKbay3V9lChoBkdAZH4qMFUyYWgHTegDaAhHQKCrVC/oJRh1fZQoaAZHQG4bTAFgUlBoB02rAWgIR0CgrIBomG/OdWUu"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 3908, "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": 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-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.1.0+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 ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:43e9756d489e55f45db46d9372ae0907ad580b45714054d9a6c7506d7e642675
3
+ size 147426
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 2.0.0a5
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,99 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "policy_class": {
3
+ ":type:": "<class 'abc.ABCMeta'>",
4
+ ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==",
5
+ "__module__": "stable_baselines3.common.policies",
6
+ "__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 ",
7
+ "__init__": "<function ActorCriticPolicy.__init__ at 0x787c7dcf6320>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x787c7dcf63b0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x787c7dcf6440>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x787c7dcf64d0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x787c7dcf6560>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x787c7dcf65f0>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x787c7dcf6680>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x787c7dcf6710>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x787c7dcf67a0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x787c7dcf6830>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x787c7dcf68c0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x787c7dcf6950>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x787c7dc97e80>"
21
+ },
22
+ "verbose": 1,
23
+ "policy_kwargs": {},
24
+ "num_timesteps": 1000448,
25
+ "_total_timesteps": 1000000,
26
+ "_num_timesteps_at_start": 0,
27
+ "seed": null,
28
+ "action_noise": null,
29
+ "start_time": 1708755855903415310,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "_last_obs": {
33
+ ":type:": "<class 'numpy.ndarray'>",
34
+ ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAAD+qb1Ylp4/fcmYvbQIgL7/zay90nfFPAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
35
+ },
36
+ "_last_episode_starts": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
39
+ },
40
+ "_last_original_obs": null,
41
+ "_episode_num": 0,
42
+ "use_sde": false,
43
+ "sde_sample_freq": -1,
44
+ "_current_progress_remaining": -0.00044800000000000395,
45
+ "_stats_window_size": 100,
46
+ "ep_info_buffer": {
47
+ ":type:": "<class 'collections.deque'>",
48
+ ":serialized:": "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"
49
+ },
50
+ "ep_success_buffer": {
51
+ ":type:": "<class 'collections.deque'>",
52
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
53
+ },
54
+ "_n_updates": 3908,
55
+ "observation_space": {
56
+ ":type:": "<class 'gymnasium.spaces.box.Box'>",
57
+ ":serialized:": "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",
58
+ "dtype": "float32",
59
+ "bounded_below": "[ True True True True True True True True]",
60
+ "bounded_above": "[ True True True True True True True True]",
61
+ "_shape": [
62
+ 8
63
+ ],
64
+ "low": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
65
+ "high": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
66
+ "low_repr": "[-90. -90. -5. -5. -3.1415927 -5.\n -0. -0. ]",
67
+ "high_repr": "[90. 90. 5. 5. 3.1415927 5.\n 1. 1. ]",
68
+ "_np_random": null
69
+ },
70
+ "action_space": {
71
+ ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
72
+ ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
73
+ "n": "4",
74
+ "start": "0",
75
+ "_shape": [],
76
+ "dtype": "int64",
77
+ "_np_random": null
78
+ },
79
+ "n_envs": 1,
80
+ "n_steps": 1024,
81
+ "gamma": 0.999,
82
+ "gae_lambda": 0.98,
83
+ "ent_coef": 0.01,
84
+ "vf_coef": 0.5,
85
+ "max_grad_norm": 0.5,
86
+ "batch_size": 64,
87
+ "n_epochs": 4,
88
+ "clip_range": {
89
+ ":type:": "<class 'function'>",
90
+ ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
91
+ },
92
+ "clip_range_vf": null,
93
+ "normalize_advantage": true,
94
+ "target_kl": null,
95
+ "lr_schedule": {
96
+ ":type:": "<class 'function'>",
97
+ ":serialized:": "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"
98
+ }
99
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5e5be059fdead593daecdd38abf3c73560a7053c453380f855dcfac9596b4757
3
+ size 88362
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0f5fe2b9e2bd79671d6f5db5ea30c8382e309a118d83a0736c24214677c5a2a6
3
+ size 43762
ppo-LunarLander-v2/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
3
+ size 864
ppo-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,9 @@
 
 
 
 
 
 
 
 
 
 
1
+ - OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
2
+ - Python: 3.10.12
3
+ - Stable-Baselines3: 2.0.0a5
4
+ - PyTorch: 2.1.0+cu121
5
+ - GPU Enabled: True
6
+ - Numpy: 1.25.2
7
+ - Cloudpickle: 2.2.1
8
+ - Gymnasium: 0.28.1
9
+ - OpenAI Gym: 0.25.2
replay.mp4 ADDED
Binary file (199 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 248.4143889, "std_reward": 17.164685094496985, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-02-24T07:27:08.379451"}