Upload result of first chapter of learning RL

README.md

@@ -0,0 +1,37 @@
+---
+library_name: stable-baselines3
+tags:
+- LunarLander-v2
+- deep-reinforcement-learning
+- reinforcement-learning
+- stable-baselines3
+model-index:
+- name: PPO
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: LunarLander-v2
+      type: LunarLander-v2
+    metrics:
+    - type: mean_reward
+      value: 255.18 +/- 27.02
+      name: mean_reward
+      verified: false
+---
+
+# **PPO** Agent playing **LunarLander-v2**
+This is a trained model of a **PPO** agent playing **LunarLander-v2**
+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 0x7897156efb50>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7897156efbe0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7897156efc70>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7897156efd00>", "_build": "<function ActorCriticPolicy._build at 0x7897156efd90>", "forward": "<function ActorCriticPolicy.forward at 0x7897156efe20>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7897156efeb0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7897156eff40>", "_predict": "<function ActorCriticPolicy._predict at 0x789715700040>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7897157000d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x789715700160>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7897157001f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7897156f90c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1710431118518055185, "learning_rate": 0.0003, "tensorboard_log": null, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.015808000000000044, "_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": 248, "observation_space": {":type:": "<class 'gymnasium.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "bounded_below": "[ True  True  True  True  True  True  True  True]", "bounded_above": "[ True  True  True  True  True  True  True  True]", "_shape": [8], "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]", "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]", "_np_random": null}, "action_space": {":type:": "<class 'gymnasium.spaces.discrete.Discrete'>", ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=", "n": "4", "start": "0", "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "n_steps": 1024, "gamma": 0.999, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 64, "n_epochs": 4, "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+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz8zqSowVTJhhZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"}, "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": "True", "Numpy": "1.25.2", "Cloudpickle": "2.2.1", "Gymnasium": "0.28.1", "OpenAI Gym": "0.25.2"}}

ppo-LunarLander-v2.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c4cdc681be49752f90248e0625d2539b07ef9829d3a96c0c5b522f29489c6bf0
+size 148084

ppo-LunarLander-v2/_stable_baselines3_version

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

ppo-LunarLander-v2/data

@@ -0,0 +1,99 @@
+{
+    "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 0x7897156efb50>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7897156efbe0>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7897156efc70>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7897156efd00>",
+        "_build": "<function ActorCriticPolicy._build at 0x7897156efd90>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7897156efe20>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7897156efeb0>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7897156eff40>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x789715700040>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7897157000d0>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x789715700160>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7897157001f0>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7897156f90c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1710431118518055185,
+    "learning_rate": 0.0003,
+    "tensorboard_log": null,
+    "_last_obs": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "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"
+    },
+    "_last_episode_starts": {
+        ":type:": "<class 'numpy.ndarray'>",
+        ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="
+    },
+    "_last_original_obs": null,
+    "_episode_num": 0,
+    "use_sde": false,
+    "sde_sample_freq": -1,
+    "_current_progress_remaining": -0.015808000000000044,
+    "_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": 248,
+    "observation_space": {
+        ":type:": "<class 'gymnasium.spaces.box.Box'>",
+        ":serialized:": "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",
+        "dtype": "float32",
+        "bounded_below": "[ True  True  True  True  True  True  True  True]",
+        "bounded_above": "[ True  True  True  True  True  True  True  True]",
+        "_shape": [
+            8
+        ],
+        "low": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
+        "high": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
+        "low_repr": "[-90.        -90.         -5.         -5.         -3.1415927  -5.\n  -0.         -0.       ]",
+        "high_repr": "[90.        90.         5.         5.         3.1415927  5.\n  1.         1.       ]",
+        "_np_random": null
+    },
+    "action_space": {
+        ":type:": "<class 'gymnasium.spaces.discrete.Discrete'>",
+        ":serialized:": "gAWV2wAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBAAAAAAAAACUhpRSlIwFc3RhcnSUaAhoDkMIAAAAAAAAAACUhpRSlIwGX3NoYXBllCmMBWR0eXBllGgOjApfbnBfcmFuZG9tlE51Yi4=",
+        "n": "4",
+        "start": "0",
+        "_shape": [],
+        "dtype": "int64",
+        "_np_random": null
+    },
+    "n_envs": 16,
+    "n_steps": 1024,
+    "gamma": 0.999,
+    "gae_lambda": 0.98,
+    "ent_coef": 0.01,
+    "vf_coef": 0.5,
+    "max_grad_norm": 0.5,
+    "batch_size": 64,
+    "n_epochs": 4,
+    "clip_range": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "gAWVxQIAAAAAAACMF2Nsb3VkcGlja2xlLmNsb3VkcGlja2xllIwOX21ha2VfZnVuY3Rpb26Uk5QoaACMDV9idWlsdGluX3R5cGWUk5SMCENvZGVUeXBllIWUUpQoSwFLAEsASwFLAUsTQwSIAFMAlE6FlCmMAV+UhZSMSS91c3IvbG9jYWwvbGliL3B5dGhvbjMuMTAvZGlzdC1wYWNrYWdlcy9zdGFibGVfYmFzZWxpbmVzMy9jb21tb24vdXRpbHMucHmUjARmdW5jlEuEQwIEAZSMA3ZhbJSFlCl0lFKUfZQojAtfX3BhY2thZ2VfX5SMGHN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbpSMCF9fbmFtZV9flIwec3RhYmxlX2Jhc2VsaW5lczMuY29tbW9uLnV0aWxzlIwIX19maWxlX1+UjEkvdXNyL2xvY2FsL2xpYi9weXRob24zLjEwL2Rpc3QtcGFja2FnZXMvc3RhYmxlX2Jhc2VsaW5lczMvY29tbW9uL3V0aWxzLnB5lHVOTmgAjBBfbWFrZV9lbXB0eV9jZWxslJOUKVKUhZR0lFKUjBxjbG91ZHBpY2tsZS5jbG91ZHBpY2tsZV9mYXN0lIwSX2Z1bmN0aW9uX3NldHN0YXRllJOUaB99lH2UKGgWaA2MDF9fcXVhbG5hbWVfX5SMGWNvbnN0YW50X2ZuLjxsb2NhbHM+LmZ1bmOUjA9fX2Fubm90YXRpb25zX1+UfZSMDl9fa3dkZWZhdWx0c19flE6MDF9fZGVmYXVsdHNfX5ROjApfX21vZHVsZV9flGgXjAdfX2RvY19flE6MC19fY2xvc3VyZV9flGgAjApfbWFrZV9jZWxslJOURz/JmZmZmZmahZRSlIWUjBdfY2xvdWRwaWNrbGVfc3VibW9kdWxlc5RdlIwLX19nbG9iYWxzX1+UfZR1hpSGUjAu"
+    },
+    "clip_range_vf": null,
+    "normalize_advantage": true,
+    "target_kl": null,
+    "lr_schedule": {
+        ":type:": "<class 'function'>",
+        ":serialized:": "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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6eea408cfd965ec5ad77bd67d2d2bfe48e904c4e54c4ff118c1709c6be172c00
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7235857684551a2df4c81d1183612f11ea75babddcd9a59b199cc596fac88e43
+size 43762

ppo-LunarLander-v2/pytorch_variables.pth

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

ppo-LunarLander-v2/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: True
+- Numpy: 1.25.2
+- Cloudpickle: 2.2.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

results.json

@@ -0,0 +1 @@
+{"mean_reward": 255.18354129999997, "std_reward": 27.02472723290791, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2024-03-14T16:17:41.380199"}