Unit-1 practice

.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:
+- 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: 267.45 +/- 20.03
+      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 0x7baaaed5c680>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7baaaed5c720>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7baaaed5c7c0>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7baaaed5c860>", "_build": "<function ActorCriticPolicy._build at 0x7baaaed5c900>", "forward": "<function ActorCriticPolicy.forward at 0x7baaaed5c9a0>", "extract_features": "<function ActorCriticPolicy.extract_features at 0x7baaaed5ca40>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7baaaed5cae0>", "_predict": "<function ActorCriticPolicy._predict at 0x7baaaed5cb80>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7baaaed5cc20>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7baaaed5ccc0>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7baaaed5cd60>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc._abc_data object at 0x7baaaeede1c0>"}, "verbose": 1, "policy_kwargs": {}, "num_timesteps": 1015808, "_total_timesteps": 1000000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1758639888999203024, "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="}, "_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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu", "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:": "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"}, "system_info": {"OS": "Linux-6.6.97+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Sep  6 09:54:41 UTC 2025", "Python": "3.11.13", "Stable-Baselines3": "2.0.0a5", "PyTorch": "2.6.0+cu124", "GPU Enabled": "True", "Numpy": "2.0.2", "Cloudpickle": "3.1.1", "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 sha256:0086ebc17860a06d36446de7f895ddcdc9774777c6267542213669222d6fec4e
+size 148075

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 0x7baaaed5c680>",
+        "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7baaaed5c720>",
+        "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7baaaed5c7c0>",
+        "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7baaaed5c860>",
+        "_build": "<function ActorCriticPolicy._build at 0x7baaaed5c900>",
+        "forward": "<function ActorCriticPolicy.forward at 0x7baaaed5c9a0>",
+        "extract_features": "<function ActorCriticPolicy.extract_features at 0x7baaaed5ca40>",
+        "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7baaaed5cae0>",
+        "_predict": "<function ActorCriticPolicy._predict at 0x7baaaed5cb80>",
+        "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7baaaed5cc20>",
+        "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7baaaed5ccc0>",
+        "predict_values": "<function ActorCriticPolicy.predict_values at 0x7baaaed5cd60>",
+        "__abstractmethods__": "frozenset()",
+        "_abc_impl": "<_abc._abc_data object at 0x7baaaeede1c0>"
+    },
+    "verbose": 1,
+    "policy_kwargs": {},
+    "num_timesteps": 1015808,
+    "_total_timesteps": 1000000,
+    "_num_timesteps_at_start": 0,
+    "seed": null,
+    "action_noise": null,
+    "start_time": 1758639888999203024,
+    "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:": "gAWVhAAAAAAAAACME251bXB5Ll9jb3JlLm51bWVyaWOUjAtfZnJvbWJ1ZmZlcpSTlCiWEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCYjGUiYiHlFKUKEsDjAF8lE5OTkr/////Sv////9LAHSUYksQhZSMAUOUdJRSlC4="
+    },
+    "_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:": "gAWV3AAAAAAAAACMGWd5bW5hc2l1bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpSMFm51bXB5Ll9jb3JlLm11bHRpYXJyYXmUjAZzY2FsYXKUk5SMBW51bXB5lIwFZHR5cGWUk5SMAmk4lImIh5RSlChLA4wBPJROTk5K/////0r/////SwB0lGJDCAQAAAAAAAAAlIaUUpSMBXN0YXJ0lGgIaA5DCAAAAAAAAAAAlIaUUpSMBl9zaGFwZZQpjAVkdHlwZZRoDowKX25wX3JhbmRvbZROdWIu",
+        "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:": "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"
+    }
+}

ppo-LunarLander-v2/policy.optimizer.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d5b28ca5271dc0863e7fe6e2feb0f77cf11c54a239e0512c41559c43234b097f
+size 88362

ppo-LunarLander-v2/policy.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5aa7b0a1cbc1dccf75587ce71639ec974313ac6417768764152d01c0807d719c
+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-6.6.97+-x86_64-with-glibc2.35 # 1 SMP PREEMPT_DYNAMIC Sat Sep  6 09:54:41 UTC 2025
+- Python: 3.11.13
+- Stable-Baselines3: 2.0.0a5
+- PyTorch: 2.6.0+cu124
+- GPU Enabled: True
+- Numpy: 2.0.2
+- Cloudpickle: 3.1.1
+- Gymnasium: 0.28.1
+- OpenAI Gym: 0.25.2

replay.mp4

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3b33c15ebae462c9bbefe64ae7e5e5a27000ba90c9404dc7e0c6fa8c9bb639fc
+size 165454

results.json

@@ -0,0 +1 @@
+{"mean_reward": 267.4484228999999, "std_reward": 20.033032564673142, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2025-09-23T15:28:08.824080"}