Upload model to Hugging Face

PPO-default.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:4288bd487cda593b2f9cb8c95e2f16ee9183739634687db1b25d481c03fd5a5a
-size 142143
+oid sha256:446c99342e9de0afd360f64479b1ee266a4e5d7fdc72db97f038023ca12d1f7c
+size 142219

PPO-default/data

@@ -4,20 +4,20 @@
         ":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 0x7f94a37f0e50>",
-        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f94a37f0ee0>",
-        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f94a37f0f70>",
-        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f94a37f1000>",
-        "_build": "<function ActorCriticPolicy._build at 0x7f94a37f1090>",
-        "forward": "<function ActorCriticPolicy.forward at 0x7f94a37f1120>",
-        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f94a37f11b0>",
-        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f94a37f1240>",
-        "_predict": "<function ActorCriticPolicy._predict at 0x7f94a37f12d0>",
-        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f94a37f1360>",
-        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f94a37f13f0>",
-        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f94a37f1480>",
+        "__init__": "<function ActorCriticPolicy.__init__ at 0x7f0bed1e4e50>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0bed1e4ee0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0bed1e4f70>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0bed1e5000>",
+        "_build": "<function ActorCriticPolicy._build at 0x7f0bed1e5090>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7f0bed1e5120>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f0bed1e51b0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0bed1e5240>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7f0bed1e52d0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0bed1e5360>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0bed1e53f0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0bed1e5480>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7f94a37e8e00>"
+        "_abc_impl": "<_abc._abc_data object at 0x7f0bed1e8a80>"
     },
     "verbose": true,
     "policy_kwargs": {},
@@ -48,7 +48,7 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1681095209129206403,
+    "start_time": 1681096448530961476,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -57,7 +57,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "gAWVxQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZQAAAAAAAAAM+jK0OjNx+/AADIQgAAyEIAAMhCP5kCQ1ZEX78AAMhCAADIQgAAyEITTONCVK+JvwAAyEIAAMhCAADIQjXcIEOGIB7AAADIQgAAyEIAAMhClIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwWGlIwBQ5R0lFKULg=="
+        ":serialized:": "gAWVxQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZQAAAAAAAAAG+sMkLn5Ka/AADIQgAAyEIAAMhC6z+sQV8jxL8AAMhCAADIQgAAyEIYmiVDFvklvwAAyEIAAMhCAADIQkhP0UEl9bG/AADIQgAAyEIAAMhClIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwWGlIwBQ5R0lFKULg=="
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -70,7 +70,7 @@
     "_current_progress_remaining": -0.0035199999999999676,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",

PPO-default/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8b011b0c90bcba7cebd6cbd8337ae188bbbde0b4e060a747e19c7d3f5845ecbc
+oid sha256:8686d319dcae62281e95cf7bebe513e28f62a3a851f372dab1e15a0defd87ddc
 size 84857

PPO-default/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b36ad44ab094a450eaa0551bcd8e6e0cbd799e0c48a2af285aaabccbf4039f8f
+oid sha256:dda0114b61b87856eaba5020fc76d884eb374eea8b01c2a7f17b108aaf7df910
 size 41857

README.md

@@ -16,7 +16,7 @@ model-index:
       type: RoombaAToB-Hardcoded
     metrics:
     - type: mean_reward
-      value: -381.25 +/- 0.00
+      value: -26.74 +/- 0.00
       name: mean_reward
       verified: false
 ---

config.json

@@ -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 0x7f94a37f0e50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f94a37f0ee0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f94a37f0f70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f94a37f1000>", "_build": "<function ActorCriticPolicy._build at 0x7f94a37f1090>", "forward": "<function ActorCriticPolicy.forward at 0x7f94a37f1120>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f94a37f11b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f94a37f1240>", "_predict": "<function ActorCriticPolicy._predict at 0x7f94a37f12d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f94a37f1360>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f94a37f13f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f94a37f1480>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f94a37e8e00>"}, "verbose": true, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [5], "low": "[0. 0. 0. 0. 0.]", "high": "[5.2000000e+05 3.1415927e+00 1.0000000e+02 1.0000000e+02 1.0000000e+02]", "bounded_below": "[ True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True]", "_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": 4, "num_timesteps": 401408, "_total_timesteps": 400000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1681095209129206403, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "gAWV4QIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMVy9ob21lL25vaXNlYnJpZGdlLy5sb2NhbC9saWIvcHl0aG9uMy4xMC9zaXRlLXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZSMBGZ1bmOUS4JDAgQBlIwDdmFslIWUKXSUUpR9lCiMC19fcGFja2FnZV9flIwYc3RhYmxlX2Jhc2VsaW5lczMuY29tbW9ulIwIX19uYW1lX1+UjB5zdGFibGVfYmFzZWxpbmVzMy5jb21tb24udXRpbHOUjAhfX2ZpbGVfX5SMVy9ob21lL25vaXNlYnJpZGdlLy5sb2NhbC9saWIvcHl0aG9uMy4xMC9zaXRlLXBhY2thZ2VzL3N0YWJsZV9iYXNlbGluZXMzL2NvbW1vbi91dGlscy5weZR1Tk5oAIwQX21ha2VfZW1wdHlfY2VsbJSTlClSlIWUdJRSlIwcY2xvdWRwaWNrbGUuY2xvdWRwaWNrbGVfZmFzdJSMEl9mdW5jdGlvbl9zZXRzdGF0ZZSTlGgffZR9lChoFmgNjAxfX3F1YWxuYW1lX1+UjBljb25zdGFudF9mbi48bG9jYWxzPi5mdW5jlIwPX19hbm5vdGF0aW9uc19flH2UjA5fX2t3ZGVmYXVsdHNfX5ROjAxfX2RlZmF1bHRzX1+UTowKX19tb2R1bGVfX5RoF4wHX19kb2NfX5ROjAtfX2Nsb3N1cmVfX5RoAIwKX21ha2VfY2VsbJSTlEc/M6kqMFUyYYWUUpSFlIwXX2Nsb3VkcGlja2xlX3N1Ym1vZHVsZXOUXZSMC19fZ2xvYmFsc19flH2UdYaUhlIwLg=="}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVxQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZQAAAAAAAAAM+jK0OjNx+/AADIQgAAyEIAAMhCP5kCQ1ZEX78AAMhCAADIQgAAyEITTONCVK+JvwAAyEIAAMhCAADIQjXcIEOGIB7AAADIQgAAyEIAAMhClIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwWGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0035199999999999676, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 490, "n_steps": 2048, "gamma": 0.95, "gae_lambda": 0.5, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.19.0-35-generic-x86_64-with-glibc2.35 # 36~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Feb 17 15:17:25 UTC 2", "Python": "3.10.9", "Stable-Baselines3": "1.7.0", "PyTorch": "2.0.0", "GPU Enabled": "True", "Numpy": "1.23.5", "Gym": "0.21.0"}}
+{"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 0x7f0bed1e4e50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f0bed1e4ee0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f0bed1e4f70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f0bed1e5000>", "_build": "<function ActorCriticPolicy._build at 0x7f0bed1e5090>", "forward": "<function ActorCriticPolicy.forward at 0x7f0bed1e5120>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7f0bed1e51b0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f0bed1e5240>", "_predict": "<function ActorCriticPolicy._predict at 0x7f0bed1e52d0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f0bed1e5360>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f0bed1e53f0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f0bed1e5480>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7f0bed1e8a80>"}, "verbose": true, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [5], "low": "[0. 0. 0. 0. 0.]", "high": "[5.2000000e+05 3.1415927e+00 1.0000000e+02 1.0000000e+02 1.0000000e+02]", "bounded_below": "[ True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True]", "_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": 4, "num_timesteps": 401408, "_total_timesteps": 400000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1681096448530961476, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVxQAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJZQAAAAAAAAAG+sMkLn5Ka/AADIQgAAyEIAAMhC6z+sQV8jxL8AAMhCAADIQgAAyEIYmiVDFvklvwAAyEIAAMhCAADIQkhP0UEl9bG/AADIQgAAyEIAAMhClIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksESwWGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYEAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwSFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0035199999999999676, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 490, "n_steps": 2048, "gamma": 0.95, "gae_lambda": 0.5, "ent_coef": 0.0, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 10, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.19.0-35-generic-x86_64-with-glibc2.35 # 36~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Feb 17 15:17:25 UTC 2", "Python": "3.10.9", "Stable-Baselines3": "1.7.0", "PyTorch": "2.0.0", "GPU Enabled": "True", "Numpy": "1.23.5", "Gym": "0.21.0"}}

results.json

@@ -1 +1 @@
-{"mean_reward": -381.2454888916018, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-09T20:00:52.174899"}
+{"mean_reward": -26.743673095701944, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-09T20:21:31.253308"}