lammi commited on
Commit
e0406de
1 Parent(s): bd841a1

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: 238.80 +/- 59.36
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 0x7fa2febcc430>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa2febcc4c0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa2febcc550>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa2febcc5e0>", "_build": "<function ActorCriticPolicy._build at 0x7fa2febcc670>", "forward": "<function ActorCriticPolicy.forward at 0x7fa2febcc700>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fa2febcc790>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa2febcc820>", "_predict": "<function ActorCriticPolicy._predict at 0x7fa2febcc8b0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa2febcc940>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa2febcc9d0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa2febcca60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7fa2febd0900>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1000448, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1681617077432397865, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAD0Ygb6mfJ0/ysfwvlYrl76IMoy+Ky2zPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 4692, "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": 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, "system_info": {"OS": "Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022", "Python": "3.9.16", "Stable-Baselines3": "1.8.0", "PyTorch": "2.0.0+cu118", "GPU Enabled": "True", "Numpy": "1.22.4", "Gym": "0.21.0"}}
ppo-LunarLander-v2.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8c0fe9dc15e47c562564c52e64a34abd01ed9f6618d93378ba4507af975d267a
3
+ size 146733
ppo-LunarLander-v2/_stable_baselines3_version ADDED
@@ -0,0 +1 @@
 
 
1
+ 1.8.0
ppo-LunarLander-v2/data ADDED
@@ -0,0 +1,96 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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 0x7fa2febcc430>",
8
+ "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7fa2febcc4c0>",
9
+ "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7fa2febcc550>",
10
+ "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7fa2febcc5e0>",
11
+ "_build": "<function ActorCriticPolicy._build at 0x7fa2febcc670>",
12
+ "forward": "<function ActorCriticPolicy.forward at 0x7fa2febcc700>",
13
+ "extract_features": "<function ActorCriticPolicy.extract_features at 0x7fa2febcc790>",
14
+ "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7fa2febcc820>",
15
+ "_predict": "<function ActorCriticPolicy._predict at 0x7fa2febcc8b0>",
16
+ "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7fa2febcc940>",
17
+ "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7fa2febcc9d0>",
18
+ "predict_values": "<function ActorCriticPolicy.predict_values at 0x7fa2febcca60>",
19
+ "__abstractmethods__": "frozenset()",
20
+ "_abc_impl": "<_abc._abc_data object at 0x7fa2febd0900>"
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": 1681617077432397865,
30
+ "learning_rate": 0.0003,
31
+ "tensorboard_log": null,
32
+ "lr_schedule": {
33
+ ":type:": "<class 'function'>",
34
+ ":serialized:": "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"
35
+ },
36
+ "_last_obs": {
37
+ ":type:": "<class 'numpy.ndarray'>",
38
+ ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAD0Ygb6mfJ0/ysfwvlYrl76IMoy+Ky2zPQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
39
+ },
40
+ "_last_episode_starts": {
41
+ ":type:": "<class 'numpy.ndarray'>",
42
+ ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
43
+ },
44
+ "_last_original_obs": null,
45
+ "_episode_num": 0,
46
+ "use_sde": false,
47
+ "sde_sample_freq": -1,
48
+ "_current_progress_remaining": -0.00044800000000000395,
49
+ "_stats_window_size": 100,
50
+ "ep_info_buffer": {
51
+ ":type:": "<class 'collections.deque'>",
52
+ ":serialized:": "gAWVfBAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIcceb/JY2bECUhpRSlIwBbJRNVgGMAXSUR0CpFg3QUpNLdX2UKGgGaAloD0MIFlCop4/vakCUhpRSlGgVTWUBaBZHQKkXV+8XenB1fZQoaAZoCWgPQwha2NMO/2RxQJSGlFKUaBVNVwFoFkdAqRisox59mnV9lChoBmgJaA9DCIC4q1fRNXBAlIaUUpRoFU1JAWgWR0CpGpSuyNXHdX2UKGgGaAloD0MIppwv9l4QM0CUhpRSlGgVS+9oFkdAqRtjKs+3Y3V9lChoBmgJaA9DCCXNH9PaQDNAlIaUUpRoFU0DAWgWR0CpHI3A/LTydX2UKGgGaAloD0MIG0rtRbRucUCUhpRSlGgVTVIBaBZHQKkeOFvAGjd1fZQoaAZoCWgPQwjFO8CTFlVuQJSGlFKUaBVNWQFoFkdAqSDC8lHBlHV9lChoBmgJaA9DCN9Q+GwdjBlAlIaUUpRoFUv9aBZHQKkiBnjhky11fZQoaAZoCWgPQwg90uC2tiw8QJSGlFKUaBVL9GgWR0CpI0M8YAKfdX2UKGgGaAloD0MIC0EOSli7cECUhpRSlGgVTYcBaBZHQKklulxffGd1fZQoaAZoCWgPQwjkZyPXTaU0QJSGlFKUaBVNEwFoFkdAqSaoSnLq2XV9lChoBmgJaA9DCNOlf0kqBG9AlIaUUpRoFU1pAWgWR0CpJ+NWU8msdX2UKGgGaAloD0MIpUxqaIMVakCUhpRSlGgVTUQBaBZHQKkpq/Firkt1fZQoaAZoCWgPQwiz7Elg8zhuQJSGlFKUaBVNTAFoFkdAqSrfnU2DQXV9lChoBmgJaA9DCA73kVsT62tAlIaUUpRoFU2PAWgWR0CpLGVrIo3KdX2UKGgGaAloD0MILoz0orYNcECUhpRSlGgVTXYBaBZHQKkua9IPK+11fZQoaAZoCWgPQwg3NGWnH+hHQJSGlFKUaBVNGQFoFkdAqS9bxVhkRXV9lChoBmgJaA9DCNjzNctlhm1AlIaUUpRoFU1wAWgWR0CpMLbkwN9ZdX2UKGgGaAloD0MIiKHVyZlBbUCUhpRSlGgVTVwBaBZHQKkykchkiEB1fZQoaAZoCWgPQwiWsaGbfY9tQJSGlFKUaBVNegFoFkdAqTQWPkq+anV9lChoBmgJaA9DCIrpQqw+T3BAlIaUUpRoFU2RAWgWR0CpNaKDK5kLdX2UKGgGaAloD0MIz2vsEtUFQ0CUhpRSlGgVTRABaBZHQKk3Lq1PWQR1fZQoaAZoCWgPQwjQ7Lq3oq1sQJSGlFKUaBVNfQFoFkdAqTiehysCDHV9lChoBmgJaA9DCB0EHa3qgG9AlIaUUpRoFU1oAWgWR0CpOmsz/IbPdX2UKGgGaAloD0MIYAFMGbi7bkCUhpRSlGgVTT8BaBZHQKk80QHzH0d1fZQoaAZoCWgPQwglAtU/iCVvQJSGlFKUaBVNQQFoFkdAqT6a/fwZwXV9lChoBmgJaA9DCNrHCn4bKjRAlIaUUpRoFU0MAWgWR0CpQAVrAP/adX2UKGgGaAloD0MIJ/p8lFGhcECUhpRSlGgVTU4BaBZHQKlCWEL6UJR1fZQoaAZoCWgPQwgX9UnuMBNuQJSGlFKUaBVNZQFoFkdAqUOxJCjUNXV9lChoBmgJaA9DCC82rRQCQW9AlIaUUpRoFU1MAWgWR0CpRPaHbh3rdX2UKGgGaAloD0MIEXLe/wdUcECUhpRSlGgVTVwBaBZHQKlG2nb7CSB1fZQoaAZoCWgPQwg+P4wQnqxxQJSGlFKUaBVNPgFoFkdAqUgAVwgkknV9lChoBmgJaA9DCHSWWYQiFnBAlIaUUpRoFU1NAWgWR0CpSTkq2BrfdX2UKGgGaAloD0MIRpc3h2tHbUCUhpRSlGgVTTsBaBZHQKlLAG7jDKp1fZQoaAZoCWgPQwhSmPc4041xQJSGlFKUaBVN0AFoFkdAqUzRa1TisHV9lChoBmgJaA9DCM0GmWTkWEBAlIaUUpRoFUv+aBZHQKlNsPFvQ4V1fZQoaAZoCWgPQwg+XHLc6fFwQJSGlFKUaBVNggFoFkdAqU/Wax5cDHV9lChoBmgJaA9DCKbUJeOYj2tAlIaUUpRoFU1FAWgWR0CpUQt9H+ZPdX2UKGgGaAloD0MIVS+/0yQmckCUhpRSlGgVTZUBaBZHQKlSnQ2MsH11fZQoaAZoCWgPQwjZJD/iV/ZIQJSGlFKUaBVNKQFoFkdAqVRX4TK1X3V9lChoBmgJaA9DCEetMH1vsXBAlIaUUpRoFU1XAWgWR0CpVaq+i8FqdX2UKGgGaAloD0MIuhRXlX0hb0CUhpRSlGgVTWYBaBZHQKlXl9PUKAt1fZQoaAZoCWgPQwgM5xpmaFFvQJSGlFKUaBVNYgFoFkdAqVsOcc2itnV9lChoBmgJaA9DCCe9b3ztinBAlIaUUpRoFU1JAmgWR0CpYDosiB5HdX2UKGgGaAloD0MI6DBfXoBGcUCUhpRSlGgVTUABaBZHQKliC0x/NJR1fZQoaAZoCWgPQwjn5EUm4BJwQJSGlFKUaBVNWAFoFkdAqWNa8WbgCXV9lChoBmgJaA9DCHpU/N8R+3BAlIaUUpRoFU2yAmgWR0CpZsn5rP+odX2UKGgGaAloD0MIptQl45h9cECUhpRSlGgVTZsBaBZHQKloYMoc7yR1fZQoaAZoCWgPQwg1ejVA6TtvQJSGlFKUaBVNkwFoFkdAqWnficXm/3V9lChoBmgJaA9DCEaU9gZfeW1AlIaUUpRoFU1+AWgWR0Cpa9qB/ZuidX2UKGgGaAloD0MIxCedSDCPYECUhpRSlGgVTegDaBZHQKlw5xNIsiB1fZQoaAZoCWgPQwjTa7OxkhRvQJSGlFKUaBVNgwFoFkdAqXJc/hVENXV9lChoBmgJaA9DCFLUmXsIA3JAlIaUUpRoFU1wAWgWR0Cpc+WYF7ladX2UKGgGaAloD0MIYWu28tKPckCUhpRSlGgVTY8BaBZHQKl3raFmFrV1fZQoaAZoCWgPQwjU8gNXeW9vQJSGlFKUaBVNYQFoFkdAqXmmRvFWGXV9lChoBmgJaA9DCLaeIRwzA25AlIaUUpRoFU19AWgWR0CpfPOQp4KQdX2UKGgGaAloD0MIwD+lSpSscUCUhpRSlGgVTWEBaBZHQKl+7lijL0V1fZQoaAZoCWgPQwgtYAK37u1wQJSGlFKUaBVNOAFoFkdAqYB7TnaFmHV9lChoBmgJaA9DCNhJfVma5HBAlIaUUpRoFU05AWgWR0CpgZoFvAGjdX2UKGgGaAloD0MIUTOkiuJ9bUCUhpRSlGgVTVMBaBZHQKmDh/OMVDd1fZQoaAZoCWgPQwhhN2xblOZvQJSGlFKUaBVNOgFoFkdAqYVfKB/ZunV9lChoBmgJaA9DCHUfgNQmI25AlIaUUpRoFU1sAWgWR0Cph0ltj0+UdX2UKGgGaAloD0MIXJAty1fPbkCUhpRSlGgVTUQBaBZHQKmJFegL7XR1fZQoaAZoCWgPQwgzFk1nZwNxQJSGlFKUaBVNTgFoFkdAqYpKqp97W3V9lChoBmgJaA9DCHdJnBXRXnBAlIaUUpRoFU1eAWgWR0Cpi5azVtoBdX2UKGgGaAloD0MI+1jBb0NkTkCUhpRSlGgVTQQBaBZHQKmNGuM+/xl1fZQoaAZoCWgPQwiVY7K4f2BuQJSGlFKUaBVNcgFoFkdAqY5hjnV5KXV9lChoBmgJaA9DCKQZi6azMHBAlIaUUpRoFU1jAWgWR0Cpj7e2mYShdX2UKGgGaAloD0MIfpBlwcT6cECUhpRSlGgVTYQBaBZHQKmRsX3xnWd1fZQoaAZoCWgPQwgjL2tigdxuQJSGlFKUaBVNZwFoFkdAqZOeFN+LFXV9lChoBmgJaA9DCFH0wMfgNXFAlIaUUpRoFU1AAWgWR0CplRkgOjIrdX2UKGgGaAloD0MI2h694f5PcECUhpRSlGgVTWkBaBZHQKmX8aLn9vV1fZQoaAZoCWgPQwgNF7mnK29wQJSGlFKUaBVNfgFoFkdAqZopRXOnmHV9lChoBmgJaA9DCEz75v7qumNAlIaUUpRoFU3oA2gWR0CpnwpH7P6bdX2UKGgGaAloD0MIvcXDe063cECUhpRSlGgVTU4BaBZHQKmgN6HCXQd1fZQoaAZoCWgPQwh3ZKw2/29BQJSGlFKUaBVL62gWR0CpobbSApazdX2UKGgGaAloD0MIFceBV8u8bUCUhpRSlGgVTWMBaBZHQKmjD6sQumJ1fZQoaAZoCWgPQwiNfcnGAwNmQJSGlFKUaBVN6ANoFkdAqafBFocrAnV9lChoBmgJaA9DCBQF+kTep3FAlIaUUpRoFU1MAWgWR0CpqOeevpyIdX2UKGgGaAloD0MIqfV+ox3Bb0CUhpRSlGgVTUQBaBZHQKmqlytmthd1fZQoaAZoCWgPQwgWNZiG4chwQJSGlFKUaBVNZgFoFkdAqav5aLXL/3V9lChoBmgJaA9DCEmdgCYCIXBAlIaUUpRoFU3TAWgWR0CprbpBHCoCdX2UKGgGaAloD0MIYqHWNO9mcUCUhpRSlGgVTUsBaBZHQKmvtHdXT3J1fZQoaAZoCWgPQwhFZ5lFqHxxQJSGlFKUaBVNZwFoFkdAqbFl8/lhgHV9lChoBmgJaA9DCGlWtg95dzvAlIaUUpRoFU0BAWgWR0CpspKdQO4HdX2UKGgGaAloD0MI/Uy9bhE/cUCUhpRSlGgVTT8BaBZHQKm1Lk1/DtR1fZQoaAZoCWgPQwh2pWWk3jZvQJSGlFKUaBVNTgFoFkdAqbb8PrfLtHV9lChoBmgJaA9DCN6ul6YIQnJAlIaUUpRoFU1oAWgWR0CpuIagVXV9dX2UKGgGaAloD0MI4V0u4jvBcUCUhpRSlGgVTW4CaBZHQKm7e41gpjN1fZQoaAZoCWgPQwjX9nZL8p1vQJSGlFKUaBVNQwFoFkdAqbyc9Mbm2nV9lChoBmgJaA9DCKd38X4cdHBAlIaUUpRoFU1VAWgWR0CpvmV5jYqYdX2UKGgGaAloD0MIjo8WZ4wocECUhpRSlGgVTUgBaBZHQKm/owX668R1fZQoaAZoCWgPQwjc9dIUgUpwQJSGlFKUaBVNTgFoFkdAqcDGndfsu3V9lChoBmgJaA9DCOs3E9MFjnBAlIaUUpRoFU3QAWgWR0CpwwC2+fyxdX2UKGgGaAloD0MIptQl4xhKbUCUhpRSlGgVTUYBaBZHQKnENQD3dsV1fZQoaAZoCWgPQwgaMEj6tD5xQJSGlFKUaBVNWAFoFkdAqcVuzIFNcnV9lChoBmgJaA9DCOAqTyAsUnJAlIaUUpRoFU1rAWgWR0Cpx0mVZ9uxdX2UKGgGaAloD0MIeNDsujfja0CUhpRSlGgVTVsBaBZHQKnIhFsHjZN1fZQoaAZoCWgPQwiqCg3EcvZyQJSGlFKUaBVNfQFoFkdAqcnnMt9QXXVlLg=="
53
+ },
54
+ "ep_success_buffer": {
55
+ ":type:": "<class 'collections.deque'>",
56
+ ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
57
+ },
58
+ "_n_updates": 4692,
59
+ "observation_space": {
60
+ ":type:": "<class 'gym.spaces.box.Box'>",
61
+ ":serialized:": "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",
62
+ "dtype": "float32",
63
+ "_shape": [
64
+ 8
65
+ ],
66
+ "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]",
67
+ "high": "[inf inf inf inf inf inf inf inf]",
68
+ "bounded_below": "[False False False False False False False False]",
69
+ "bounded_above": "[False False False False False False False False]",
70
+ "_np_random": null
71
+ },
72
+ "action_space": {
73
+ ":type:": "<class 'gym.spaces.discrete.Discrete'>",
74
+ ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu",
75
+ "n": 4,
76
+ "_shape": [],
77
+ "dtype": "int64",
78
+ "_np_random": null
79
+ },
80
+ "n_envs": 1,
81
+ "n_steps": 1024,
82
+ "gamma": 0.999,
83
+ "gae_lambda": 0.98,
84
+ "ent_coef": 0.01,
85
+ "vf_coef": 0.5,
86
+ "max_grad_norm": 0.5,
87
+ "batch_size": 64,
88
+ "n_epochs": 4,
89
+ "clip_range": {
90
+ ":type:": "<class 'function'>",
91
+ ":serialized:": "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"
92
+ },
93
+ "clip_range_vf": null,
94
+ "normalize_advantage": true,
95
+ "target_kl": null
96
+ }
ppo-LunarLander-v2/policy.optimizer.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:52423948ccf116a41456e8c1087546eb40be2dd2c90cfd3fbbd11b2026c120a2
3
+ size 87929
ppo-LunarLander-v2/policy.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:88a8724e6fe373b7a94bff28ed1d0081fa937328de3de1c78ea2ae6364997c07
3
+ size 43329
ppo-LunarLander-v2/pytorch_variables.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
3
+ size 431
ppo-LunarLander-v2/system_info.txt ADDED
@@ -0,0 +1,7 @@
 
 
 
 
 
 
 
 
1
+ - OS: Linux-5.10.147+-x86_64-with-glibc2.31 # 1 SMP Sat Dec 10 16:00:40 UTC 2022
2
+ - Python: 3.9.16
3
+ - Stable-Baselines3: 1.8.0
4
+ - PyTorch: 2.0.0+cu118
5
+ - GPU Enabled: True
6
+ - Numpy: 1.22.4
7
+ - Gym: 0.21.0
replay.mp4 ADDED
Binary file (250 kB). View file
 
results.json ADDED
@@ -0,0 +1 @@
 
 
1
+ {"mean_reward": 238.7996465541184, "std_reward": 59.35586924384239, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-16T04:53:24.797260"}