Upload PPO HalfCheetah-v4 trained agent

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+replay.mp4 filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- HalfCheetah-v4
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: HalfCheetah-v4
+      type: HalfCheetah-v4
+    metrics:
+    - type: mean_reward
+      value: 3533.14 +/- 501.87
+      name: mean_reward
+      verified: false
+---
+
+# **PPO** Agent playing **HalfCheetah-v4**
+This is a trained model of a **PPO** agent playing **HalfCheetah-v4**
+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:": "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 0x7c2e983f6320>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c2e983f63b0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c2e983f6440>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c2e983f64d0>", "_build": "<function ActorCriticPolicy._build at 0x7c2e983f6560>", "forward": "<function ActorCriticPolicy.forward at 0x7c2e983f65f0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c2e983f6680>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c2e983f6710>", "_predict": "<function ActorCriticPolicy._predict at 0x7c2e983f67a0>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c2e983f6830>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c2e983f68c0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c2e983f6950>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7c2e983f2080>"}, "verbose": 0, "policy_kwargs": {":type:": "<class 'dict'>", ":serialized:": "gAWVjgAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA1hY3RpdmF0aW9uX2ZulIwbdG9yY2gubm4ubW9kdWxlcy5hY3RpdmF0aW9ulIwEUmVMVZSTlIwIbmV0X2FyY2iUXZR9lCiMAnBplF2UKE0AAU0AAWWMAnZmlF2UKE0AAU0AAWV1YXUu", "log_std_init": -2, "ortho_init": false, "activation_fn": "<class 'torch.nn.modules.activation.ReLU'>", "net_arch": [{"pi": [256, 256], "vf": [256, 256]}]}, "num_timesteps": 800256, "_total_timesteps": 800000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1711907393914947525, "learning_rate": 2.0633e-05, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWV/QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaIAAAAAAAAAPb6yfPG+bu/YpoP60batj9x2iwnfCfFPzD1dRHNwbs/Dqo886Xe0r8Gk7uUQ9Xnv8/dEvGZeEW/WjFuD3Cq0b9X7dYYUVkDQAvaFImlFt+/ok6+8amxCED0iN46maEpwHjrUtNFZRtAHFlv9tIRKcAUEH5DL5MwwKBsTdtdKHa/RI0BBkzhIECUjAVudW1weZSMBWR0eXBllJOUjAJmOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwFLEYaUjAFDlHSUUpQu"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.000320000000000098, "_stats_window_size": 100, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 31260, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float64", "bounded_below": "[False False False False False False False False False False False False\n False False False False False]", "bounded_above": "[False False False False False False False False False False False False\n False False False False False]", "_shape": [17], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf]", "low_repr": "-inf", "high_repr": "inf", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True]", "_shape": [6], "low": "[-1. -1. -1. -1. -1. -1.]", "high": "[1. 1. 1. 1. 1. 1.]", "low_repr": "-1.0", "high_repr": "1.0", "_np_random": null}, "n_envs": 1, "n_steps": 512, "gamma": 0.98, "gae_lambda": 0.92, "ent_coef": 0.000401762, "vf_coef": 0.58096, "max_grad_norm": 0.8, "batch_size": 64, "n_epochs": 20, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "system_info": {"OS": "Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023", "Python": "3.10.12", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.2.1+cu121", "GPU Enabled": "False", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-HalfCheetah-v4.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e1a3443255833a08964b759b85d84248580734775847ff6581ed916e6d537281
+size 1743065

ppo-HalfCheetah-v4/_stable_baselines3_version

@@ -0,0 +1 @@
+2.0.0a5

ppo-HalfCheetah-v4/data

@@ -0,0 +1,123 @@
+{
+    "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 0x7c2e983f6320>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7c2e983f63b0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7c2e983f6440>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7c2e983f64d0>",
+        "_build": "<function ActorCriticPolicy._build at 0x7c2e983f6560>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7c2e983f65f0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7c2e983f6680>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7c2e983f6710>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7c2e983f67a0>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7c2e983f6830>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7c2e983f68c0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7c2e983f6950>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7c2e983f2080>"
+    },
+    "verbose": 0,
+    "policy_kwargs": {
+        ":type:": "<class 'dict'>",
+        ":serialized:": "gAWVjgAAAAAAAAB9lCiMDGxvZ19zdGRfaW5pdJRK/v///4wKb3J0aG9faW5pdJSJjA1hY3RpdmF0aW9uX2ZulIwbdG9yY2gubm4ubW9kdWxlcy5hY3RpdmF0aW9ulIwEUmVMVZSTlIwIbmV0X2FyY2iUXZR9lCiMAnBplF2UKE0AAU0AAWWMAnZmlF2UKE0AAU0AAWV1YXUu",
+        "log_std_init": -2,
+        "ortho_init": false,
+        "activation_fn": "<class 'torch.nn.modules.activation.ReLU'>",
+        "net_arch": [
+            {
+                "pi": [
+                    256,
+                    256
+                ],
+                "vf": [
+                    256,
+                    256
+                ]
+            }
+        ]
+    },
+    "num_timesteps": 800256,
+    "_total_timesteps": 800000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1711907393914947525,
+    "learning_rate": 2.0633e-05,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWV/QAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJaIAAAAAAAAAPb6yfPG+bu/YpoP60batj9x2iwnfCfFPzD1dRHNwbs/Dqo886Xe0r8Gk7uUQ9Xnv8/dEvGZeEW/WjFuD3Cq0b9X7dYYUVkDQAvaFImlFt+/ok6+8amxCED0iN46maEpwHjrUtNFZRtAHFlv9tIRKcAUEH5DL5MwwKBsTdtdKHa/RI0BBkzhIECUjAVudW1weZSMBWR0eXBllJOUjAJmOJSJiIeUUpQoSwOMATyUTk5OSv////9K/////0sAdJRiSwFLEYaUjAFDlHSUUpQu"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVdAAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYBAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSwGFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": null,
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.000320000000000098,
+    "_stats_window_size": 100,
+    "ep_info_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "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"
+    },
+    "ep_success_buffer": {
+        ":type:": "<class 'collections.deque'>",
+        ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
+    },
+    "_n_updates": 31260,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float64",
+        "bounded_below": "[False False False False False False False False False False False False\n False False False False False]",
+        "bounded_above": "[False False False False False False False False False False False False\n False False False False False]",
+        "_shape": [
+            17
+        ],
+        "low": "[-inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf -inf\n -inf -inf -inf]",
+        "high": "[inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf inf]",
+        "low_repr": "-inf",
+        "high_repr": "inf",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "bounded_below": "[ True  True  True  True  True  True]",
+        "bounded_above": "[ True  True  True  True  True  True]",
+        "_shape": [
+            6
+        ],
+        "low": "[-1. -1. -1. -1. -1. -1.]",
+        "high": "[1. 1. 1. 1. 1. 1.]",
+        "low_repr": "-1.0",
+        "high_repr": "1.0",
+        "_np_random": null
+    },
+    "n_envs": 1,
+    "n_steps": 512,
+    "gamma": 0.98,
+    "gae_lambda": 0.92,
+    "ent_coef": 0.000401762,
+    "vf_coef": 0.58096,
+    "max_grad_norm": 0.8,
+    "batch_size": 64,
+    "n_epochs": 20,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz71oqD2p4kThZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+    }
+}

ppo-HalfCheetah-v4/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5032f4e868648a4252eadc095b6eeee89f6e82579ca853e1b6a9b6695de77031
+size 1151201

ppo-HalfCheetah-v4/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:30e26c1aa1d0a272e7b4dba68d0b97cf042a944abcf06c08c808b641029a7930
+size 575215

ppo-HalfCheetah-v4/pytorch_variables.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0c35cea3b2e60fb5e7e162d3592df775cd400e575a31c72f359fb9e654ab00c5
+size 864

ppo-HalfCheetah-v4/system_info.txt

@@ -0,0 +1,9 @@
+- OS: Linux-6.1.58+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Nov 18 15:31:17 UTC 2023
+- Python: 3.10.12
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.2.1+cu121
+- GPU Enabled: False
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8edbf5a6029866eba71fbd2a993118e6cdaf44bff7251f19bf41c50f9cc514c7
+size 1369029

results.json

@@ -0,0 +1 @@
+{"mean_reward": 3533.138711190596, "std_reward": 501.8720457667742, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-31T18:36:52.980686"}