Upload DQN MountainCar-v0 trained agent

README.md

@@ -0,0 +1,36 @@
+---
+library_name: stable-baselines3
+tags:
+- MountainCar-v0
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: DQN
+  results:
+  - metrics:
+    - type: mean_reward
+      value: -200.00 +/- 0.00
+      name: mean_reward
+    task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: MountainCar-v0
+      type: MountainCar-v0
+---
+
+# **DQN** Agent playing **MountainCar-v0**
+This is a trained model of a **DQN** agent playing **MountainCar-v0**
+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:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=", "__module__": "stable_baselines3.dqn.policies", "__doc__": "\n    Policy class with Q-Value Net and target net for DQN\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 features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\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 DQNPolicy.__init__ at 0x7ff7dcd579e0>", "_build": "<function DQNPolicy._build at 0x7ff7dcd57a70>", "make_q_net": "<function DQNPolicy.make_q_net at 0x7ff7dcd57b00>", "forward": "<function DQNPolicy.forward at 0x7ff7dcd57b90>", "_predict": "<function DQNPolicy._predict at 0x7ff7dcd57c20>", "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7ff7dcd57cb0>", "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7ff7dcd57d40>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ff7dcdb8f00>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "gAWVYwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLAoWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAACamZm/KVyPvZRoCksChZSMAUOUdJRSlIwEaGlnaJRoEiiWCAAAAAAAAACamRk/KVyPPZRoCksChZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolgIAAAAAAAAAAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLAoWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYCAAAAAAAAAAEBlGghSwKFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu", "dtype": "float32", "_shape": [2], "low": "[-1.2  -0.07]", "high": "[0.6  0.07]", "bounded_below": "[ True  True]", "bounded_above": "[ True  True]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "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", "n": 3, "_shape": [], "dtype": "int64", "_np_random": "RandomState(MT19937)"}, "n_envs": 16, "num_timesteps": 500032, "_total_timesteps": 500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1660539531.933557, "learning_rate": 0.0001, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAALvxw767fnC7yeaTvnSNS7ywrb6+Yc+JuzyWrr73qv27njifvsXwPbzmyMW+e5pCu1X7hL79DGS8CVKovs6OJLx/J8u+o3pBul2/sb7oDgO8SKS0vr5HCLzqW8q+B02Ouryyp75//Be8ONOTvmm0S7wxs7y+biNquwmpt77vuKu7lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwKGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAAL0Qwr5jLm27XYqNvg9GQLxzhry+NcKFu5Cfqr4gKPK7GEmZvuXNNLyxQ8S+/TVBu9u1e77DHVa8ki2jvgtSHbzCxsq+MOxSuuamrb7c1fu7CmKwvjmzA7ydzcm+jEqVutjyor45tBC8lXWNvlZpQLzq3rq+xJ5guyX6tL60eKS7lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwKGlIwBQ5R0lFKULg=="}, "_episode_num": 2496, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -6.4000000000064e-05, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 7032, "buffer_size": 1000000, "batch_size": 32, "learning_starts": 50000, "tau": 1.0, "gamma": 0.99, "gradient_steps": 1, "optimize_memory_usage": false, "replay_buffer_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==", "__module__": "stable_baselines3.common.buffers", "__doc__": "\n    Replay buffer used in off-policy algorithms like SAC/TD3.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device:\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        of the replay buffer which reduces by almost a factor two the memory used,\n        at a cost of more complexity.\n        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n        and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n        Cannot be used in combination with handle_timeout_termination.\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ", "__init__": "<function ReplayBuffer.__init__ at 0x7ff7dcdae170>", "add": "<function ReplayBuffer.add at 0x7ff7dcdae200>", "sample": "<function ReplayBuffer.sample at 0x7ff7dcdae290>", "_get_samples": "<function ReplayBuffer._get_samples at 0x7ff7dcdae320>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7ff7dcdfcdb0>"}, "replay_buffer_kwargs": {}, "train_freq": {":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>", ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"}, "actor": null, "use_sde_at_warmup": false, "exploration_initial_eps": 1.0, "exploration_final_eps": 0.05, "exploration_fraction": 0.1, "target_update_interval": 625, "_n_calls": 31252, "max_grad_norm": 10, "exploration_rate": 0.05, "exploration_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022", "Python": "3.7.13", "Stable-Baselines3": "1.6.0", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

dqn-MountainCar-v0.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e1d879812b46ab85e7e7ea095bcdf63480ddef4e6665a212d6a66bf0958a44d4
+size 100422

dqn-MountainCar-v0/_stable_baselines3_version

@@ -0,0 +1 @@
+1.6.0

dqn-MountainCar-v0/data

@@ -0,0 +1,115 @@
+{
+    "policy_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVMAAAAAAAAACMHnN0YWJsZV9iYXNlbGluZXMzLmRxbi5wb2xpY2llc5SMCURRTlBvbGljeZSTlC4=",
+        "__module__": "stable_baselines3.dqn.policies",
+        "__doc__": "\n    Policy class with Q-Value Net and target net for DQN\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 features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\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 DQNPolicy.__init__ at 0x7ff7dcd579e0>",
+        "_build": "<function DQNPolicy._build at 0x7ff7dcd57a70>",
+        "make_q_net": "<function DQNPolicy.make_q_net at 0x7ff7dcd57b00>",
+        "forward": "<function DQNPolicy.forward at 0x7ff7dcd57b90>",
+        "_predict": "<function DQNPolicy._predict at 0x7ff7dcd57c20>",
+        "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7ff7dcd57cb0>",
+        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7ff7dcd57d40>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7ff7dcdb8f00>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "observation_space": {
+        ":type:": "<class 'gym.spaces.box.Box'>",
+        ":serialized:": "gAWVYwEAAAAAAACMDmd5bS5zcGFjZXMuYm94lIwDQm94lJOUKYGUfZQojAVkdHlwZZSMBW51bXB5lGgFk5SMAmY0lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGKMBl9zaGFwZZRLAoWUjANsb3eUjBJudW1weS5jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWCAAAAAAAAACamZm/KVyPvZRoCksChZSMAUOUdJRSlIwEaGlnaJRoEiiWCAAAAAAAAACamRk/KVyPPZRoCksChZRoFXSUUpSMDWJvdW5kZWRfYmVsb3eUaBIolgIAAAAAAAAAAQGUaAeMAmIxlImIh5RSlChLA4wBfJROTk5K/////0r/////SwB0lGJLAoWUaBV0lFKUjA1ib3VuZGVkX2Fib3ZllGgSKJYCAAAAAAAAAAEBlGghSwKFlGgVdJRSlIwKX25wX3JhbmRvbZROdWIu",
+        "dtype": "float32",
+        "_shape": [
+            2
+        ],
+        "low": "[-1.2  -0.07]",
+        "high": "[0.6  0.07]",
+        "bounded_below": "[ True  True]",
+        "bounded_above": "[ True  True]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gym.spaces.discrete.Discrete'>",
+        ":serialized:": "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",
+        "n": 3,
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": "RandomState(MT19937)"
+    },
+    "n_envs": 16,
+    "num_timesteps": 500032,
+    "_total_timesteps": 500000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1660539531.933557,
+    "learning_rate": 0.0001,
+    "tensorboard_log": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWVwQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsBSwFLE0MEiABTAJROhZQpjAFflIWUjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuAQwIAAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEgvdXNyL2xvY2FsL2xpYi9weXRob24zLjcvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUdU5OaACMEF9tYWtlX2VtcHR5X2NlbGyUk5QpUpSFlHSUUpSMHGNsb3VkcGlja2xlLmNsb3VkcGlja2xlX2Zhc3SUjBJfZnVuY3Rpb25fc2V0c3RhdGWUk5RoH32UfZQoaBZoDYwMX19xdWFsbmFtZV9flIwZY29uc3RhbnRfZm4uPGxvY2Fscz4uZnVuY5SMD19fYW5ub3RhdGlvbnNfX5R9lIwOX19rd2RlZmF1bHRzX1+UTowMX19kZWZhdWx0c19flE6MCl9fbW9kdWxlX1+UaBeMB19fZG9jX1+UTowLX19jbG9zdXJlX1+UaACMCl9tYWtlX2NlbGyUk5RHPxo24uscQy2FlFKUhZSMF19jbG91ZHBpY2tsZV9zdWJtb2R1bGVzlF2UjAtfX2dsb2JhbHNfX5R9lHWGlIZSMC4="
+    },
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAALvxw767fnC7yeaTvnSNS7ywrb6+Yc+JuzyWrr73qv27njifvsXwPbzmyMW+e5pCu1X7hL79DGS8CVKovs6OJLx/J8u+o3pBul2/sb7oDgO8SKS0vr5HCLzqW8q+B02Ouryyp75//Be8ONOTvmm0S7wxs7y+biNquwmpt77vuKu7lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwKGlIwBQ5R0lFKULg=="
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAEBAQEBAQEBAQEBAQEBAQGUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWV9QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaAAAAAAAAAAL0Qwr5jLm27XYqNvg9GQLxzhry+NcKFu5Cfqr4gKPK7GEmZvuXNNLyxQ8S+/TVBu9u1e77DHVa8ki2jvgtSHbzCxsq+MOxSuuamrb7c1fu7CmKwvjmzA7ydzcm+jEqVutjyor45tBC8lXWNvlZpQLzq3rq+xJ5guyX6tL60eKS7lIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwKGlIwBQ5R0lFKULg=="
+    },
+    "_episode_num": 2496,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -6.4000000000064e-05,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 7032,
+    "buffer_size": 1000000,
+    "batch_size": 32,
+    "learning_starts": 50000,
+    "tau": 1.0,
+    "gamma": 0.99,
+    "gradient_steps": 1,
+    "optimize_memory_usage": false,
+    "replay_buffer_class": {
+        ":type:": "<class 'abc.ABCMeta'>",
+        ":serialized:": "gAWVNQAAAAAAAACMIHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5idWZmZXJzlIwMUmVwbGF5QnVmZmVylJOULg==",
+        "__module__": "stable_baselines3.common.buffers",
+        "__doc__": "\n    Replay buffer used in off-policy algorithms like SAC/TD3.\n\n    :param buffer_size: Max number of element in the buffer\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param device:\n    :param n_envs: Number of parallel environments\n    :param optimize_memory_usage: Enable a memory efficient variant\n        of the replay buffer which reduces by almost a factor two the memory used,\n        at a cost of more complexity.\n        See https://github.com/DLR-RM/stable-baselines3/issues/37#issuecomment-637501195\n        and https://github.com/DLR-RM/stable-baselines3/pull/28#issuecomment-637559274\n        Cannot be used in combination with handle_timeout_termination.\n    :param handle_timeout_termination: Handle timeout termination (due to timelimit)\n        separately and treat the task as infinite horizon task.\n        https://github.com/DLR-RM/stable-baselines3/issues/284\n    ",
+        "__init__": "<function ReplayBuffer.__init__ at 0x7ff7dcdae170>",
+        "add": "<function ReplayBuffer.add at 0x7ff7dcdae200>",
+        "sample": "<function ReplayBuffer.sample at 0x7ff7dcdae290>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x7ff7dcdae320>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc_data object at 0x7ff7dcdfcdb0>"
+    },
+    "replay_buffer_kwargs": {},
+    "train_freq": {
+        ":type:": "<class 'stable_baselines3.common.type_aliases.TrainFreq'>",
+        ":serialized:": "gAWVYQAAAAAAAACMJXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi50eXBlX2FsaWFzZXOUjAlUcmFpbkZyZXGUk5RLBGgAjBJUcmFpbkZyZXF1ZW5jeVVuaXSUk5SMBHN0ZXCUhZRSlIaUgZQu"
+    },
+    "actor": null,
+    "use_sde_at_warmup": false,
+    "exploration_initial_eps": 1.0,
+    "exploration_final_eps": 0.05,
+    "exploration_fraction": 0.1,
+    "target_update_interval": 625,
+    "_n_calls": 31252,
+    "max_grad_norm": 10,
+    "exploration_rate": 0.05,
+    "exploration_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    }
+}

dqn-MountainCar-v0/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:96b770650f66a41534772164e79f8aae292e6c06260273e333ae443e459937cc
+size 41263

dqn-MountainCar-v0/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7598e2d5767f800e79a1ea2f2a88b3aecff04c4d8dbec1dec1f48fbd4c7fcfb0
+size 40449

dqn-MountainCar-v0/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
+size 431

dqn-MountainCar-v0/system_info.txt

@@ -0,0 +1,7 @@
+OS: Linux-5.4.188+-x86_64-with-Ubuntu-18.04-bionic #1 SMP Sun Apr 24 10:03:06 PDT 2022
+Python: 3.7.13
+Stable-Baselines3: 1.6.0
+PyTorch: 1.12.1+cu113
+GPU Enabled: True
+Numpy: 1.21.6
+Gym: 0.21.0

results.json

@@ -0,0 +1 @@
+{"mean_reward": -200.0, "std_reward": 0.0, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-08-15T05:10:14.805894"}