Upload model to Hugging Face

DQN-default.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:a31e8ea220793e410b9636b7630d4655f395bbc9ebb5ee7cd3eeaa2471c89ad2
 size 105963

DQN-default/data

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         "__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 0x7f271a077520>",
-        "_build": "<function DQNPolicy._build at 0x7f271a0775b0>",
-        "make_q_net": "<function DQNPolicy.make_q_net at 0x7f271a077640>",
-        "forward": "<function DQNPolicy.forward at 0x7f271a0776d0>",
-        "_predict": "<function DQNPolicy._predict at 0x7f271a077760>",
-        "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7f271a0777f0>",
-        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7f271a077880>",
+        "__init__": "<function DQNPolicy.__init__ at 0x7fe79b873520>",
+        "_build": "<function DQNPolicy._build at 0x7fe79b8735b0>",
+        "make_q_net": "<function DQNPolicy.make_q_net at 0x7fe79b873640>",
+        "forward": "<function DQNPolicy.forward at 0x7fe79b8736d0>",
+        "_predict": "<function DQNPolicy._predict at 0x7fe79b873760>",
+        "_get_constructor_parameters": "<function DQNPolicy._get_constructor_parameters at 0x7fe79b8737f0>",
+        "set_training_mode": "<function DQNPolicy.set_training_mode at 0x7fe79b873880>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7f271a47edc0>"
+        "_abc_impl": "<_abc._abc_data object at 0x7fe79b8868c0>"
     },
     "verbose": true,
     "policy_kwargs": {},
@@ -31,7 +31,7 @@
     },
     "action_space": {
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         "__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: PyTorch 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 0x7f271a073130>",
-        "add": "<function ReplayBuffer.add at 0x7f271a0731c0>",
-        "sample": "<function ReplayBuffer.sample at 0x7f271a073250>",
-        "_get_samples": "<function ReplayBuffer._get_samples at 0x7f271a0732e0>",
+        "__init__": "<function ReplayBuffer.__init__ at 0x7fe79b86f130>",
+        "add": "<function ReplayBuffer.add at 0x7fe79b86f1c0>",
+        "sample": "<function ReplayBuffer.sample at 0x7fe79b86f250>",
+        "_get_samples": "<function ReplayBuffer._get_samples at 0x7fe79b86f2e0>",
         "__abstractmethods__": "frozenset()",
-        "_abc_impl": "<_abc._abc_data object at 0x7f271a004440>"
+        "_abc_impl": "<_abc._abc_data object at 0x7fe79b9df8c0>"
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     "replay_buffer_kwargs": {},
     "train_freq": {

DQN-default/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0757cb0fb0c3e834a8c0c3084b7767353f7f7a63190b942d149a7b6c1c24a6f6
+oid sha256:1fbb4a01d457dd5b85b53c8aad221fa65067e43b448c7b61e5f795dc679ab826
 size 43951

DQN-default/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b2235cf58fc9c5886e0e0b91e80c09228965a04e9f7c5b0a26dc2e7df7812094
+oid sha256:34647f4c6bb65abf3a18b725174195a7d0a286af592272bac6f813209b7c0558
 size 43009

README.md

@@ -16,7 +16,7 @@ model-index:
       type: RoombaAToB
     metrics:
     - type: mean_reward
-      value: 178.76 +/- 216.79
+      value: -117.23 +/- 40.81
       name: mean_reward
       verified: false
 ---

config.json

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results.json

@@ -1 +1 @@
-{"mean_reward": 178.76040580000003, "std_reward": 216.78817163720936, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-08T16:24:15.943374"}
+{"mean_reward": -117.23120850000001, "std_reward": 40.80663827865989, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2023-04-08T16:28:53.667165"}