Batch 32 model

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 253.07 +/- 22.50
+      value: 263.32 +/- 21.39
       name: mean_reward
       verified: false
 ---

config.json

@@ -1 +1 @@
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If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\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 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 0x7f47509795e0>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f4750979670>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f4750979700>", "_build_mlp_extractor": "<function 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"
+        ":serialized:": 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UCtO3S3JAlIaUUpRoFU0aAWgWR0C84r2wRoRJdX2UKGgGaAloD0MIWvPjLy1UcUCUhpRSlGgVTQsBaBZHQLzi0lS0jTt1fZQoaAZoCWgPQwgwgVt38xpwQJSGlFKUaBVL/mgWR0C84uHvx6OYdX2UKGgGaAloD0MIWMhcGdQgckCUhpRSlGgVTRQBaBZHQLzi6LV4HHF1fZQoaAZoCWgPQwgvM2yUdQduQJSGlFKUaBVNNQFoFkdAvOM2Sr5qM3V9lChoBmgJaA9DCFMFo5I693BAlIaUUpRoFU0zAWgWR0C841ALmZE2dX2UKGgGaAloD0MIzApFup/WbUCUhpRSlGgVTSkBaBZHQLzjWRtgrpd1fZQoaAZoCWgPQwhsCmR2Fs5vQJSGlFKUaBVNIQFoFkdAvONzz19ORHV9lChoBmgJaA9DCJ8gsd09c21AlIaUUpRoFU0pAWgWR0C8438houf3dX2UKGgGaAloD0MIH4XrUbh8ckCUhpRSlGgVTV4BaBZHQLzjiZwn6VN1fZQoaAZoCWgPQwh7E0NyMhRvQJSGlFKUaBVNAwFoFkdAvOOb+m3vyHV9lChoBmgJaA9DCLqkarsJYXJAlIaUUpRoFU0yAWgWR0C8467yhBZ7dWUu"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
@@ -82,7 +82,7 @@
     "ent_coef": 0.01,
     "vf_coef": 0.5,
     "max_grad_norm": 0.5,
-    "batch_size": 64,
+    "batch_size": 32,
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