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  1. last_to_hit_frequency_2128/README.md +163 -0
  2. last_to_hit_frequency_2128/all_results.json +16 -0
  3. last_to_hit_frequency_2128/checkpoint-100000/config.json +31 -0
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  9. last_to_hit_frequency_2128/checkpoint-100000/scaler.pt +3 -0
  10. last_to_hit_frequency_2128/checkpoint-100000/scheduler.pt +3 -0
  11. last_to_hit_frequency_2128/checkpoint-100000/special_tokens_map.json +5 -0
  12. last_to_hit_frequency_2128/checkpoint-100000/tokenizer.json +0 -0
  13. last_to_hit_frequency_2128/checkpoint-100000/tokenizer_config.json +20 -0
  14. last_to_hit_frequency_2128/checkpoint-100000/trainer_state.json +0 -0
  15. last_to_hit_frequency_2128/checkpoint-100000/training_args.bin +3 -0
  16. last_to_hit_frequency_2128/checkpoint-100000/vocab.json +0 -0
  17. last_to_hit_frequency_2128/checkpoint-30000/config.json +31 -0
  18. last_to_hit_frequency_2128/checkpoint-30000/generation_config.json +6 -0
  19. last_to_hit_frequency_2128/checkpoint-30000/merges.txt +0 -0
  20. last_to_hit_frequency_2128/checkpoint-30000/model.safetensors +3 -0
  21. last_to_hit_frequency_2128/checkpoint-30000/optimizer.pt +3 -0
  22. last_to_hit_frequency_2128/checkpoint-30000/rng_state.pth +3 -0
  23. last_to_hit_frequency_2128/checkpoint-30000/scaler.pt +3 -0
  24. last_to_hit_frequency_2128/checkpoint-30000/scheduler.pt +3 -0
  25. last_to_hit_frequency_2128/checkpoint-30000/special_tokens_map.json +5 -0
  26. last_to_hit_frequency_2128/checkpoint-30000/tokenizer.json +0 -0
  27. last_to_hit_frequency_2128/checkpoint-30000/tokenizer_config.json +20 -0
  28. last_to_hit_frequency_2128/checkpoint-30000/trainer_state.json +0 -0
  29. last_to_hit_frequency_2128/checkpoint-30000/training_args.bin +3 -0
  30. last_to_hit_frequency_2128/checkpoint-30000/vocab.json +0 -0
  31. last_to_hit_frequency_2128/checkpoint-70000/config.json +31 -0
  32. last_to_hit_frequency_2128/checkpoint-70000/generation_config.json +6 -0
  33. last_to_hit_frequency_2128/checkpoint-70000/merges.txt +0 -0
  34. last_to_hit_frequency_2128/checkpoint-70000/model.safetensors +3 -0
  35. last_to_hit_frequency_2128/checkpoint-70000/optimizer.pt +3 -0
  36. last_to_hit_frequency_2128/checkpoint-70000/rng_state.pth +3 -0
  37. last_to_hit_frequency_2128/checkpoint-70000/scaler.pt +3 -0
  38. last_to_hit_frequency_2128/checkpoint-70000/scheduler.pt +3 -0
  39. last_to_hit_frequency_2128/checkpoint-70000/special_tokens_map.json +5 -0
  40. last_to_hit_frequency_2128/checkpoint-70000/tokenizer.json +0 -0
  41. last_to_hit_frequency_2128/checkpoint-70000/tokenizer_config.json +20 -0
  42. last_to_hit_frequency_2128/checkpoint-70000/trainer_state.json +0 -0
  43. last_to_hit_frequency_2128/checkpoint-70000/training_args.bin +3 -0
  44. last_to_hit_frequency_2128/checkpoint-70000/vocab.json +0 -0
  45. last_to_hit_frequency_2128/checkpoint-80000/config.json +31 -0
  46. last_to_hit_frequency_2128/checkpoint-80000/generation_config.json +6 -0
  47. last_to_hit_frequency_2128/checkpoint-80000/merges.txt +0 -0
  48. last_to_hit_frequency_2128/checkpoint-80000/model.safetensors +3 -0
  49. last_to_hit_frequency_2128/checkpoint-80000/optimizer.pt +3 -0
  50. last_to_hit_frequency_2128/checkpoint-80000/rng_state.pth +3 -0
last_to_hit_frequency_2128/README.md ADDED
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+ ---
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+ library_name: transformers
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: exceptions_exp2_last_to_hit_frequency_2128
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/craaaa/exceptions_exp2/runs/x4fq7vdf)
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+ # exceptions_exp2_last_to_hit_frequency_2128
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.5762
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+ - Accuracy: 0.3669
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0006
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 2128
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+ - gradient_accumulation_steps: 5
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+ - total_train_batch_size: 80
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.98) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 50.0
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Accuracy | Validation Loss |
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+ |:-------------:|:-------:|:------:|:--------:|:---------------:|
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+ | 4.8229 | 0.2913 | 1000 | 0.2537 | 4.7555 |
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+ | 4.3272 | 0.5826 | 2000 | 0.2996 | 4.2827 |
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+ | 4.142 | 0.8739 | 3000 | 0.3152 | 4.0961 |
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+ | 3.9925 | 1.1652 | 4000 | 0.3253 | 3.9905 |
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+ | 3.9195 | 1.4565 | 5000 | 0.3317 | 3.9143 |
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+ | 3.8842 | 1.7478 | 6000 | 0.3369 | 3.8600 |
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+ | 3.7443 | 2.0390 | 7000 | 0.3412 | 3.8168 |
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+ | 3.7503 | 2.3303 | 8000 | 0.3443 | 3.7862 |
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+ | 3.7376 | 2.6216 | 9000 | 0.3468 | 3.7569 |
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+ | 3.7244 | 2.9130 | 10000 | 0.3495 | 3.7275 |
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+ | 3.6353 | 3.2042 | 11000 | 0.3514 | 3.7176 |
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+ | 3.6428 | 3.4955 | 12000 | 0.3530 | 3.6977 |
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+ | 3.646 | 3.7868 | 13000 | 0.3546 | 3.6797 |
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+ | 3.5479 | 4.0781 | 14000 | 0.3563 | 3.6728 |
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+ | 3.5782 | 4.3694 | 15000 | 0.3572 | 3.6620 |
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+ | 3.5819 | 4.6607 | 16000 | 0.3583 | 3.6463 |
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+ | 3.5792 | 4.9520 | 17000 | 0.3595 | 3.6341 |
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+ | 3.512 | 5.2432 | 18000 | 0.3602 | 3.6385 |
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+ | 3.5208 | 5.5345 | 19000 | 0.3610 | 3.6262 |
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+ | 3.5273 | 5.8259 | 20000 | 0.3621 | 3.6148 |
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+ | 3.4475 | 6.1171 | 21000 | 0.3623 | 3.6193 |
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+ | 3.4806 | 6.4084 | 22000 | 0.3629 | 3.6127 |
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+ | 3.4748 | 6.6997 | 23000 | 0.3639 | 3.6005 |
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+ | 3.4908 | 6.9910 | 24000 | 0.3644 | 3.5943 |
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+ | 3.4153 | 7.2823 | 25000 | 0.3642 | 3.6025 |
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+ | 3.4552 | 7.5736 | 26000 | 0.3650 | 3.5934 |
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+ | 3.4603 | 7.8649 | 27000 | 0.3657 | 3.5852 |
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+ | 3.3745 | 8.1561 | 28000 | 0.3660 | 3.5920 |
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+ | 3.406 | 8.4474 | 29000 | 0.3660 | 3.5856 |
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+ | 3.429 | 8.7388 | 30000 | 0.3669 | 3.5762 |
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+ | 3.317 | 9.0300 | 31000 | 0.3673 | 3.5818 |
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+ | 3.3833 | 9.3213 | 32000 | 0.3672 | 3.5804 |
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+ | 3.3999 | 9.6126 | 33000 | 0.3681 | 3.5710 |
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+ | 3.4035 | 9.9039 | 34000 | 0.3680 | 3.5646 |
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+ | 3.3507 | 10.1952 | 35000 | 0.3683 | 3.5742 |
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+ | 3.3689 | 10.4865 | 36000 | 0.3684 | 3.5697 |
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+ | 3.379 | 10.7778 | 37000 | 0.3692 | 3.5598 |
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+ | 3.2905 | 11.0690 | 38000 | 0.3688 | 3.5722 |
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+ | 3.3332 | 11.3603 | 39000 | 0.3691 | 3.5677 |
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+ | 3.3602 | 11.6517 | 40000 | 0.3691 | 3.5606 |
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+ | 3.3818 | 11.9430 | 41000 | 0.3703 | 3.5513 |
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+ | 3.2924 | 12.2342 | 42000 | 0.3695 | 3.5651 |
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+ | 3.3339 | 12.5255 | 43000 | 0.3701 | 3.5587 |
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+ | 3.352 | 12.8168 | 44000 | 0.3709 | 3.5511 |
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+ | 3.2587 | 13.1081 | 45000 | 0.3704 | 3.5614 |
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+ | 3.3059 | 13.3994 | 46000 | 0.3704 | 3.5590 |
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+ | 3.3337 | 13.6907 | 47000 | 0.3709 | 3.5515 |
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+ | 3.3343 | 13.9820 | 48000 | 0.3714 | 3.5442 |
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+ | 3.2804 | 14.2732 | 49000 | 0.3708 | 3.5584 |
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+ | 3.3208 | 14.8559 | 51000 | 0.3716 | 3.5444 |
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+ | 3.2996 | 15.7297 | 54000 | 0.3719 | 3.5449 |
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+ | 3.2685 | 16.3123 | 56000 | 0.3718 | 3.5511 |
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+ | 3.2776 | 16.6036 | 57000 | 0.3719 | 3.5490 |
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+ | 3.3034 | 16.8949 | 58000 | 0.3726 | 3.5382 |
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+ | 3.2318 | 17.1861 | 59000 | 0.3719 | 3.5549 |
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+ | 3.2693 | 17.4775 | 60000 | 0.3726 | 3.5509 |
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+ | 3.2845 | 17.7688 | 61000 | 0.3728 | 3.5412 |
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+ | 3.2022 | 18.0600 | 62000 | 0.3724 | 3.5512 |
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+ | 3.2434 | 18.3513 | 63000 | 0.3726 | 3.5515 |
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+ | 3.2583 | 18.6426 | 64000 | 0.3728 | 3.5427 |
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+ | 3.2754 | 18.9339 | 65000 | 0.3732 | 3.5360 |
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+ | 3.1981 | 19.2252 | 66000 | 0.3726 | 3.5563 |
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+ | 3.2406 | 19.5165 | 67000 | 0.3731 | 3.5442 |
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+ | 3.2603 | 19.8078 | 68000 | 0.3735 | 3.5391 |
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+ | 3.1759 | 20.0990 | 69000 | 0.3731 | 3.5492 |
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+ | 3.2213 | 20.3904 | 70000 | 0.3732 | 3.5476 |
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+ | 3.2306 | 20.6817 | 71000 | 0.3734 | 3.5419 |
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+ | 3.259 | 20.9730 | 72000 | 0.3741 | 3.5322 |
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+ | 3.2027 | 21.2642 | 73000 | 0.3728 | 3.5526 |
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+ | 3.2301 | 21.5555 | 74000 | 0.3735 | 3.5442 |
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+ | 3.2353 | 21.8468 | 75000 | 0.3741 | 3.5360 |
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+ | 3.1793 | 22.1381 | 76000 | 0.3731 | 3.5540 |
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+ | 3.2118 | 22.4294 | 77000 | 0.3734 | 3.5473 |
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+ | 3.2325 | 22.7207 | 78000 | 0.3739 | 3.5397 |
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+ | 3.1549 | 23.0119 | 79000 | 0.3738 | 3.5458 |
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+ | 3.1875 | 23.3033 | 80000 | 0.3732 | 3.5524 |
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+ | 3.1815 | 23.5946 | 81000 | 3.5515 | 0.3736 |
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+ | 3.2017 | 23.8859 | 82000 | 3.5459 | 0.3737 |
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+ | 3.1608 | 24.1774 | 83000 | 3.5538 | 0.3733 |
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+ | 3.1977 | 24.4687 | 84000 | 3.5465 | 0.3740 |
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+ | 3.2052 | 24.7600 | 85000 | 3.5396 | 0.3745 |
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+ | 3.122 | 25.0513 | 86000 | 3.5503 | 0.3738 |
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+ | 3.1656 | 25.3426 | 87000 | 3.5481 | 0.3739 |
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+ | 3.1894 | 25.6339 | 88000 | 3.5432 | 0.3742 |
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+ | 3.1508 | 26.2164 | 90000 | 3.5524 | 0.3737 |
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+ | 3.1713 | 26.5077 | 91000 | 3.5424 | 0.3743 |
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+ | 3.1843 | 26.7991 | 92000 | 3.5353 | 0.3747 |
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+ | 3.1242 | 27.0903 | 93000 | 3.5492 | 0.3741 |
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+ | 3.1564 | 27.3816 | 94000 | 3.5455 | 0.3745 |
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+ | 3.1625 | 27.6729 | 95000 | 3.5386 | 0.3750 |
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+ | 3.1875 | 27.9642 | 96000 | 3.5359 | 0.3748 |
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+ | 3.1266 | 28.2555 | 97000 | 3.5481 | 0.3743 |
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+ | 3.1698 | 28.5468 | 98000 | 3.5439 | 0.3747 |
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+ | 3.1624 | 28.8381 | 99000 | 3.5402 | 0.3750 |
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+ | 3.1128 | 29.1293 | 100000 | 3.5496 | 0.3746 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.55.2
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+ - Pytorch 2.8.0+cu128
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+ - Datasets 4.0.0
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+ - Tokenizers 0.21.4
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