Model save

README.md

@@ -27,7 +27,7 @@ print(output["generated_text"])
 
 ## Training procedure
 
-[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/devamanyu/huggingface/runs/8zifsris)
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/devamanyu/huggingface/runs/h2s2xq8b)
 
 This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290).
 

all_results.json

@@ -2,8 +2,8 @@
     "epoch": 1.0,
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     "train_loss": 0.0,
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     "train_samples": 61134,
-    "train_samples_per_second": 41576.783,
-    "train_steps_per_second": 325.084
+    "train_samples_per_second": 71.79,
+    "train_steps_per_second": 0.561
 }

runs/Nov13_05-47-39_dvhaz-sleeper-cmh-gpu/events.out.tfevents.1731476944.dvhaz-sleeper-cmh-gpu.3057.0

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train_results.json

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     "epoch": 1.0,
     "total_flos": 0.0,
     "train_loss": 0.0,
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+    "train_runtime": 851.567,
     "train_samples": 61134,
-    "train_samples_per_second": 41576.783,
-    "train_steps_per_second": 325.084
+    "train_samples_per_second": 71.79,
+    "train_steps_per_second": 0.561
 }

trainer_state.json

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       "step": 478,
       "total_flos": 0.0,
       "train_loss": 0.0,
-      "train_runtime": 1.4704,
-      "train_samples_per_second": 41576.783,
-      "train_steps_per_second": 325.084
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+      "train_samples_per_second": 71.79,
+      "train_steps_per_second": 0.561
     }
   ],
   "logging_steps": 10,

training_args.bin

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