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README.md

@@ -1,41 +1,29 @@
-
-        # **PPO** Agent playing **PongNoFrameskip-v4**
-
-        This is a trained model of a **PPO** agent playing **PongNoFrameskip-v4**.
-        
 ---
-{
-  "tags": [
-    "PongNoFrameskip-v4",
-    "ppo",
-    "reinforcement-learning",
-    "stable-baselines3",
-    "deep-rl",
-    "atari"
-  ],
-  "model-index": [
-    {
-      "name": "PPO Pong Atari",
-      "results": [
-        {
-          "task": {
-            "type": "reinforcement-learning",
-            "name": "Pong"
-          },
-          "dataset": {
-            "name": "PongNoFrameskip-v4",
-            "type": "atari"
-          },
-          "metrics": [
-            {
-              "name": "Mean Reward",
-              "type": "mean_reward",
-              "value": "21.00 +/- 0.00"
-            }
-          ]
-        }
-      ]
-    }
-  ]
-}
+tags:
+- PongNoFrameskip-v4
+- ppo
+- reinforcement-learning
+- stable-baselines3
+- deep-rl
+- atari
+model-index:
+  - name: PPO Pong Atari
+    results:
+      - task:
+          type: reinforcement-learning
+          name: Pong
+        dataset:
+          name: PongNoFrameskip-v4
+          type: atari
+        metrics:
+          - name: Mean Reward
+            type: mean_reward
+            value: 21.00 +/- 0.00
 ---
+
+
+# **PPO** Agent playing **PongNoFrameskip-v4**
+
+This is a trained model of a **PPO** agent playing **PongNoFrameskip-v4**.
+
+To learn to use this model and train yours, check the Deep Reinforcement Learning Course on [Hugging Face](https://huggingface.co/deep-rl-course).

ppo_pong.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:9974534e114b6b7f4f61c4d8093c32a6a162b160fb3ab33b2f5d58edb55c43ae
-size 23100241
+oid sha256:1ce60ab54f7a1c69b4c971ea4c419c4cae54bf1bc01663073d460f0d3ccd47ae
+size 23100621

results.json

@@ -1 +1 @@
-{"env_id": "PongNoFrameskip-v4", "mean_reward": 21.0, "n_evaluation_episodes": 10, "eval_datetime": "2024-10-20T13:50:37.086070"}
+{"env_id": "PongNoFrameskip-v4", "mean_reward": 21.0, "n_evaluation_episodes": 10, "eval_datetime": "2024-10-20T13:53:31.793001"}