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README.md

@@ -5,7 +5,7 @@ tags:
 - reinforcement-learning
 - custom-implementation
 model-index:
-- name: q-Taxi-v3
+- name: q-taxi-v8
   results:
   - task:
       type: reinforcement-learning
@@ -15,7 +15,7 @@ model-index:
       type: Taxi-v3
     metrics:
     - type: mean_reward
-      value: 7.50 +/- 2.76
+      value: 8.29 +/- 2.44
       name: mean_reward
       verified: false
 ---
@@ -27,7 +27,7 @@ model-index:
 
   ```python
 
-  model = load_from_hub(repo_id="seynath/q-Taxi-v3", filename="q-learning.pkl")
+  model = load_from_hub(repo_id="TaTo69/q-taxi-v8", filename="q-learning.pkl")
 
   # Don't forget to check if you need to add additional attributes (is_slippery=False etc)
   env = gym.make(model["env_id"])

q-learning.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:582a734fd89b8827b82e7271949007d545ef65e5c474dc74c9b9aef0cd17af49
-size 24571
+oid sha256:c9262f6f9217f9a468194986545b145f59748d5e046cdf30fee91e87a9481caf
+size 24370

replay.mp4

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:96dd088ebca2a6cff025cbd2288b5b549b84a66a941aba057e771367dfde2609
-size 117089
+oid sha256:dcde69e6948be04ac9e626444ccc06690878a2c8bedb6c75a53a5ca1392f71b1
+size 118960

results.json

@@ -1 +1 @@
-{"env_id": "Taxi-v3", "mean_reward": 7.5, "n_eval_episodes": 100, "eval_datetime": "2025-12-17T18:58:57.235436"}
+{"env_id": "Taxi-v3", "mean_reward": 8.29, "n_eval_episodes": 100, "eval_datetime": "2023-11-03T21:16:55.684329"}