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### TRAINING LOG |
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wandb: Run history: |
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wandb: eval/loss █▆▅▄▃▃▂▂▁▁▁ |
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wandb: eval/runtime ▁▃▂▃▃▃▃█▃▄▁ |
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wandb: eval/samples_per_second █▆▇▆▆▆▆▁▆▄█ |
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wandb: eval/steps_per_second █▆▇▆▆▆▆▁▆▄█ |
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wandb: train/epoch ▁▁▁▂▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
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wandb: train/global_step ▁▁▁▂▂▂▂▂▂▃▃▃▃▃▄▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███ |
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wandb: train/learning_rate ▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁▁ |
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wandb: train/loss █▄▄▅▃▅▃▃▄▅▃▃▃▄▃▃▃▃▂▂▂▂▃▂▄▂▃▂▂▂▂▂▃▂▁▃▂▂▂▁ |
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wandb: train/total_flos ▁ |
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wandb: train/train_loss ▁ |
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wandb: train/train_runtime ▁ |
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wandb: train/train_samples_per_second ▁ |
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wandb: train/train_steps_per_second ▁ |
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wandb: |
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wandb: Run summary: |
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wandb: eval/loss 0.27314 |
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wandb: eval/runtime 129.6563 |
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wandb: eval/samples_per_second 7.713 |
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wandb: eval/steps_per_second 7.713 |
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wandb: train/epoch 0.53 |
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wandb: train/global_step 1875 |
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wandb: train/learning_rate 0.0002 |
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wandb: train/loss 0.258 |
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wandb: train/total_flos 1.9547706216175334e+17 |
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wandb: train/train_loss 0.30445 |
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wandb: train/train_runtime 13368.3721 |
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wandb: train/train_samples_per_second 2.244 |
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wandb: train/train_steps_per_second 0.14 |
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wandb: |
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wandb: 🚀 View run happy-deluge-17 at: https://wandb.ai/metric/llm_finetune_multiwoz22.sh/runs/4epf9h85 |
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### INFERENCE LOG |
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TODO |