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Ant-v4-ppo_fix_continuous_action-seed2

Reinforcement Learning
TensorBoard
cleanrl
Ant-v4
deep-reinforcement-learning
custom-implementation
Eval Results
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sdpkjc commited on
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1 Parent(s): ac09b36

pushing model

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Files changed (10) hide show
  1. .gitattributes +2 -0
  2. README.md +1 -1
  3. events.out.tfevents.1704452182.4090-171.100796.0 → events.out.tfevents.1705688624.3090-172.2505274.0 +2 -2
  4. ppo_fix_continuous_action.cleanrl_model +0 -0
  5. ppo_fix_continuous_action.py +1 -1
  6. replay.mp4 +2 -2
  7. videos/Ant-v4__ppo_fix_continuous_action__2__1704452175-eval/rl-video-episode-8.mp4 +0 -3
  8. videos/{Ant-v4__ppo_fix_continuous_action__2__1704452175-eval → Ant-v4__ppo_fix_continuous_action__2__1705688616-eval}/rl-video-episode-0.mp4 +2 -2
  9. videos/{Ant-v4__ppo_fix_continuous_action__2__1704452175-eval → Ant-v4__ppo_fix_continuous_action__2__1705688616-eval}/rl-video-episode-1.mp4 +2 -2
  10. videos/Ant-v4__ppo_fix_continuous_action__2__1705688616-eval/rl-video-episode-8.mp4 +0 -0
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  videos/Ant-v4__ppo_fix_continuous_action__2__1704452175-eval/rl-video-episode-8.mp4 filter=lfs diff=lfs merge=lfs -text
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  videos/Ant-v4__ppo_fix_continuous_action__2__1704452175-eval/rl-video-episode-1.mp4 filter=lfs diff=lfs merge=lfs -text
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  videos/Ant-v4__ppo_fix_continuous_action__2__1704452175-eval/rl-video-episode-8.mp4 filter=lfs diff=lfs merge=lfs -text
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  videos/Ant-v4__ppo_fix_continuous_action__2__1704452175-eval/rl-video-episode-0.mp4 filter=lfs diff=lfs merge=lfs -text
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README.md CHANGED
@@ -16,7 +16,7 @@ model-index:
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  type: Ant-v4
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  metrics:
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  - type: mean_reward
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- value: 3539.06 +/- 1251.35
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  name: mean_reward
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  verified: false
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  ---
 
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  type: Ant-v4
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  metrics:
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  - type: mean_reward
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+ value: 2123.22 +/- 951.64
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  name: mean_reward
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  verified: false
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  ---
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ppo_fix_continuous_action.cleanrl_model CHANGED
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ppo_fix_continuous_action.py CHANGED
@@ -198,7 +198,7 @@ class NormalizeReward(gym.core.Wrapper, gym.utils.RecordConstructorArgs):
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  return obs, rews, terminateds, truncateds, infos
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  def reset(self, **kwargs):
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- self.returns = np.zeros(self.num_envs)
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  return self.env.reset(**kwargs)
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  def normalize(self, rews):
 
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  return obs, rews, terminateds, truncateds, infos
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  def reset(self, **kwargs):
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  def normalize(self, rews):
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