Commit
•
3815326
1
Parent(s):
fef00e3
Upload PPO LunarLander-v2 trained agent
Browse files- README.md +1 -1
- config.json +1 -1
- ppo-LunarLander-v2.zip +2 -2
- ppo-LunarLander-v2/data +9 -9
- ppo-LunarLander-v2/policy.optimizer.pth +1 -1
- ppo-LunarLander-v2/policy.pth +1 -1
- replay.mp4 +0 -0
- results.json +1 -1
README.md
CHANGED
@@ -16,7 +16,7 @@ model-index:
|
|
16 |
type: LunarLander-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
-
value:
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
|
|
16 |
type: LunarLander-v2
|
17 |
metrics:
|
18 |
- type: mean_reward
|
19 |
+
value: 232.69 +/- 72.48
|
20 |
name: mean_reward
|
21 |
verified: false
|
22 |
---
|
config.json
CHANGED
@@ -1 +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 0x795dac5daa70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x795dac5dab00>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x795dac5dab90>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x795dac5dac20>", "_build": "<function ActorCriticPolicy._build at 0x795dac5dacb0>", "forward": "<function ActorCriticPolicy.forward at 0x795dac5dad40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x795dac5dadd0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x795dac5dae60>", "_predict": "<function ActorCriticPolicy._predict at 0x795dac5daef0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x795dac5daf80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x795dac5db010>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x795dac5db0a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x795dac5d6fc0>"}, "verbose": 0, "policy_kwargs": {}, "num_timesteps": 25600, "_total_timesteps": 25000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1715267606692551837, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAAK3tVj5lbIk/GB1pu4tchr7Kek8/NpyRPgAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": -0.02400000000000002, "_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": 100, "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:": "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", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "n_steps": 1024, "gamma": 0.59, "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": "2.2.1+cu121", "GPU Enabled": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}
|
|
|
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 0x795dac5daa70>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x795dac5dab00>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x795dac5dab90>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x795dac5dac20>", "_build": "<function ActorCriticPolicy._build at 0x795dac5dacb0>", "forward": "<function ActorCriticPolicy.forward at 0x795dac5dad40>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x795dac5dadd0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x795dac5dae60>", "_predict": "<function ActorCriticPolicy._predict at 0x795dac5daef0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x795dac5daf80>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x795dac5db010>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x795dac5db0a0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x795dac5d6fc0>"}, "verbose": 0, "policy_kwargs": {}, "num_timesteps": 2000896, "_total_timesteps": 2000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1715268258968784491, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAABrPbL3Yn6o+UtLGvMnVv76O5cG8r/6FvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////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": 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:": "gAWVogEAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlIwUbnVtcHkucmFuZG9tLl9waWNrbGWUjBBfX2dlbmVyYXRvcl9jdG9ylJOUjAVQQ0c2NJRoG4wUX19iaXRfZ2VuZXJhdG9yX2N0b3KUk5SGlFKUfZQojA1iaXRfZ2VuZXJhdG9ylIwFUENHNjSUjAVzdGF0ZZR9lChoJooRrdoXSMHAW2vRLvx5sP6+0gCMA2luY5SKELlaNghOKnRUvYIHOXwXLjR1jApoYXNfdWludDMylEsAjAh1aW50ZWdlcpRKHhPnU3VidWIu", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": "Generator(PCG64)"}, "n_envs": 1, "n_steps": 2048, "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": "2.2.1+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
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:5bdeee827974570c252a2badcb4e0763ab970ffb0f8fa7d7db17562d32537d2d
|
3 |
+
size 147608
|
ppo-LunarLander-v2/data
CHANGED
@@ -21,17 +21,17 @@
|
|
21 |
},
|
22 |
"verbose": 0,
|
23 |
"policy_kwargs": {},
|
24 |
-
"num_timesteps":
|
25 |
-
"_total_timesteps":
|
26 |
"_num_timesteps_at_start": 0,
|
27 |
"seed": null,
|
28 |
"action_noise": null,
|
29 |
-
"start_time":
|
30 |
"learning_rate": 0.0003,
|
31 |
"tensorboard_log": null,
|
32 |
"_last_obs": {
|
33 |
":type:": "<class 'numpy.ndarray'>",
|
34 |
-
":serialized:": "
|
35 |
},
|
36 |
"_last_episode_starts": {
|
37 |
":type:": "<class 'numpy.ndarray'>",
|
@@ -41,17 +41,17 @@
|
|
41 |
"_episode_num": 0,
|
42 |
"use_sde": false,
|
43 |
"sde_sample_freq": -1,
|
44 |
-
"_current_progress_remaining": -0.
|
45 |
"_stats_window_size": 100,
|
46 |
"ep_info_buffer": {
|
47 |
":type:": "<class 'collections.deque'>",
|
48 |
-
":serialized:": "
|
49 |
},
|
50 |
"ep_success_buffer": {
|
51 |
":type:": "<class 'collections.deque'>",
|
52 |
":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
|
53 |
},
|
54 |
-
"_n_updates":
|
55 |
"observation_space": {
|
56 |
":type:": "<class 'gymnasium.spaces.box.Box'>",
|
57 |
":serialized:": "gAWVdgIAAAAAAACMFGd5bW5hc2l1bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lIwFZHR5cGWUk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMDWJvdW5kZWRfYmVsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAAABAQEBAQEBAZRoCIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksIhZSMAUOUdJRSlIwNYm91bmRlZF9hYm92ZZRoESiWCAAAAAAAAAABAQEBAQEBAZRoFUsIhZRoGXSUUpSMBl9zaGFwZZRLCIWUjANsb3eUaBEoliAAAAAAAAAAAAC0wgAAtMIAAKDAAACgwNsPScAAAKDAAAAAgAAAAICUaAtLCIWUaBl0lFKUjARoaWdolGgRKJYgAAAAAAAAAAAAtEIAALRCAACgQAAAoEDbD0lAAACgQAAAgD8AAIA/lGgLSwiFlGgZdJRSlIwIbG93X3JlcHKUjFtbLTkwLiAgICAgICAgLTkwLiAgICAgICAgIC01LiAgICAgICAgIC01LiAgICAgICAgIC0zLjE0MTU5MjcgIC01LgogIC0wLiAgICAgICAgIC0wLiAgICAgICBdlIwJaGlnaF9yZXBylIxTWzkwLiAgICAgICAgOTAuICAgICAgICAgNS4gICAgICAgICA1LiAgICAgICAgIDMuMTQxNTkyNyAgNS4KICAxLiAgICAgICAgIDEuICAgICAgIF2UjApfbnBfcmFuZG9tlE51Yi4=",
|
@@ -77,8 +77,8 @@
|
|
77 |
"_np_random": "Generator(PCG64)"
|
78 |
},
|
79 |
"n_envs": 1,
|
80 |
-
"n_steps":
|
81 |
-
"gamma": 0.
|
82 |
"gae_lambda": 0.98,
|
83 |
"ent_coef": 0.01,
|
84 |
"vf_coef": 0.5,
|
|
|
21 |
},
|
22 |
"verbose": 0,
|
23 |
"policy_kwargs": {},
|
24 |
+
"num_timesteps": 2000896,
|
25 |
+
"_total_timesteps": 2000000,
|
26 |
"_num_timesteps_at_start": 0,
|
27 |
"seed": null,
|
28 |
"action_noise": null,
|
29 |
+
"start_time": 1715268258968784491,
|
30 |
"learning_rate": 0.0003,
|
31 |
"tensorboard_log": null,
|
32 |
"_last_obs": {
|
33 |
":type:": "<class 'numpy.ndarray'>",
|
34 |
+
":serialized:": "gAWVlQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYgAAAAAAAAABrPbL3Yn6o+UtLGvMnVv76O5cG8r/6FvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksBSwiGlIwBQ5R0lFKULg=="
|
35 |
},
|
36 |
"_last_episode_starts": {
|
37 |
":type:": "<class 'numpy.ndarray'>",
|
|
|
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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",
|
|
|
77 |
"_np_random": "Generator(PCG64)"
|
78 |
},
|
79 |
"n_envs": 1,
|
80 |
+
"n_steps": 2048,
|
81 |
+
"gamma": 0.999,
|
82 |
"gae_lambda": 0.98,
|
83 |
"ent_coef": 0.01,
|
84 |
"vf_coef": 0.5,
|
ppo-LunarLander-v2/policy.optimizer.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 88362
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:e37a69b255b77a6a9ce741d2d25796c0033d2892be8919e1aa09cd7adacf673b
|
3 |
size 88362
|
ppo-LunarLander-v2/policy.pth
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 43762
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:5331e814c2e09a57e0b61d8f2a9af652213d4dd979d5a4daa94b532801667f07
|
3 |
size 43762
|
replay.mp4
CHANGED
Binary files a/replay.mp4 and b/replay.mp4 differ
|
|
results.json
CHANGED
@@ -1 +1 @@
|
|
1 |
-
{"mean_reward":
|
|
|
1 |
+
{"mean_reward": 232.69148809999996, "std_reward": 72.4840102419608, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-05-09T16:30:51.900430"}
|