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  1. last_to_carry_frequency_5039/README.md +163 -0
  2. last_to_carry_frequency_5039/all_results.json +16 -0
  3. last_to_carry_frequency_5039/checkpoint-100000/config.json +31 -0
  4. last_to_carry_frequency_5039/checkpoint-100000/generation_config.json +6 -0
  5. last_to_carry_frequency_5039/checkpoint-100000/merges.txt +0 -0
  6. last_to_carry_frequency_5039/checkpoint-100000/model.safetensors +3 -0
  7. last_to_carry_frequency_5039/checkpoint-100000/optimizer.pt +3 -0
  8. last_to_carry_frequency_5039/checkpoint-100000/rng_state.pth +3 -0
  9. last_to_carry_frequency_5039/checkpoint-100000/scaler.pt +3 -0
  10. last_to_carry_frequency_5039/checkpoint-100000/scheduler.pt +3 -0
  11. last_to_carry_frequency_5039/checkpoint-100000/special_tokens_map.json +5 -0
  12. last_to_carry_frequency_5039/checkpoint-100000/tokenizer.json +0 -0
  13. last_to_carry_frequency_5039/checkpoint-100000/tokenizer_config.json +20 -0
  14. last_to_carry_frequency_5039/checkpoint-100000/trainer_state.json +0 -0
  15. last_to_carry_frequency_5039/checkpoint-100000/training_args.bin +3 -0
  16. last_to_carry_frequency_5039/checkpoint-100000/vocab.json +0 -0
  17. last_to_carry_frequency_5039/checkpoint-40000/config.json +31 -0
  18. last_to_carry_frequency_5039/checkpoint-40000/generation_config.json +6 -0
  19. last_to_carry_frequency_5039/checkpoint-40000/merges.txt +0 -0
  20. last_to_carry_frequency_5039/checkpoint-40000/model.safetensors +3 -0
  21. last_to_carry_frequency_5039/checkpoint-40000/optimizer.pt +3 -0
  22. last_to_carry_frequency_5039/checkpoint-40000/rng_state.pth +3 -0
  23. last_to_carry_frequency_5039/checkpoint-40000/scaler.pt +3 -0
  24. last_to_carry_frequency_5039/checkpoint-40000/scheduler.pt +3 -0
  25. last_to_carry_frequency_5039/checkpoint-40000/special_tokens_map.json +5 -0
  26. last_to_carry_frequency_5039/checkpoint-40000/tokenizer.json +0 -0
  27. last_to_carry_frequency_5039/checkpoint-40000/tokenizer_config.json +20 -0
  28. last_to_carry_frequency_5039/checkpoint-40000/trainer_state.json +0 -0
  29. last_to_carry_frequency_5039/checkpoint-40000/training_args.bin +3 -0
  30. last_to_carry_frequency_5039/checkpoint-40000/vocab.json +0 -0
  31. last_to_carry_frequency_5039/checkpoint-70000/config.json +31 -0
  32. last_to_carry_frequency_5039/checkpoint-70000/generation_config.json +6 -0
  33. last_to_carry_frequency_5039/checkpoint-70000/merges.txt +0 -0
  34. last_to_carry_frequency_5039/checkpoint-70000/model.safetensors +3 -0
  35. last_to_carry_frequency_5039/checkpoint-70000/optimizer.pt +3 -0
  36. last_to_carry_frequency_5039/checkpoint-70000/rng_state.pth +3 -0
  37. last_to_carry_frequency_5039/checkpoint-70000/scaler.pt +3 -0
  38. last_to_carry_frequency_5039/checkpoint-70000/scheduler.pt +3 -0
  39. last_to_carry_frequency_5039/checkpoint-70000/special_tokens_map.json +5 -0
  40. last_to_carry_frequency_5039/checkpoint-70000/tokenizer.json +0 -0
  41. last_to_carry_frequency_5039/checkpoint-70000/tokenizer_config.json +20 -0
  42. last_to_carry_frequency_5039/checkpoint-70000/trainer_state.json +0 -0
  43. last_to_carry_frequency_5039/checkpoint-70000/training_args.bin +3 -0
  44. last_to_carry_frequency_5039/checkpoint-70000/vocab.json +0 -0
  45. last_to_carry_frequency_5039/checkpoint-80000/config.json +31 -0
  46. last_to_carry_frequency_5039/checkpoint-80000/generation_config.json +6 -0
  47. last_to_carry_frequency_5039/checkpoint-80000/merges.txt +0 -0
  48. last_to_carry_frequency_5039/checkpoint-80000/model.safetensors +3 -0
  49. last_to_carry_frequency_5039/checkpoint-80000/optimizer.pt +3 -0
  50. last_to_carry_frequency_5039/checkpoint-80000/rng_state.pth +3 -0
last_to_carry_frequency_5039/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_carry_frequency_5039
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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/pdfh0a2i)
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+ # exceptions_exp2_last_to_carry_frequency_5039
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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: 3.5523
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+ - Accuracy: 0.3703
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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: 5039
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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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+ | 4.8139 | 0.2913 | 1000 | 0.2564 | 4.7430 |
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+ | 4.3314 | 0.5826 | 2000 | 0.3003 | 4.2777 |
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+ | 4.1456 | 0.8739 | 3000 | 0.3161 | 4.0925 |
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+ | 3.9995 | 1.1652 | 4000 | 0.3254 | 3.9842 |
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+ | 3.9264 | 1.4565 | 5000 | 0.3321 | 3.9122 |
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+ | 3.8863 | 1.7477 | 6000 | 0.3375 | 3.8526 |
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+ | 3.7364 | 2.0390 | 7000 | 0.3421 | 3.8106 |
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+ | 3.7524 | 2.3303 | 8000 | 0.3452 | 3.7800 |
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+ | 3.7308 | 2.6216 | 9000 | 0.3476 | 3.7496 |
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+ | 3.7161 | 2.9129 | 10000 | 0.3503 | 3.7257 |
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+ | 3.6277 | 3.2042 | 11000 | 0.3519 | 3.7127 |
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+ | 3.6408 | 3.4955 | 12000 | 0.3536 | 3.6919 |
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+ | 3.6222 | 3.7868 | 13000 | 0.3555 | 3.6751 |
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+ | 3.5328 | 4.0781 | 14000 | 0.3565 | 3.6696 |
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+ | 3.5641 | 4.3694 | 15000 | 0.3576 | 3.6570 |
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+ | 3.5766 | 4.6606 | 16000 | 0.3588 | 3.6437 |
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+ | 3.5779 | 4.9519 | 17000 | 0.3599 | 3.6337 |
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+ | 3.5007 | 5.2432 | 18000 | 0.3607 | 3.6343 |
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+ | 3.5119 | 5.5345 | 19000 | 0.3614 | 3.6213 |
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+ | 3.5305 | 5.8258 | 20000 | 0.3624 | 3.6105 |
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+ | 3.433 | 6.1171 | 21000 | 0.3628 | 3.6146 |
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+ | 3.4682 | 6.4084 | 22000 | 0.3635 | 3.6062 |
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+ | 3.4849 | 6.6997 | 23000 | 0.3641 | 3.5959 |
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+ | 3.4949 | 6.9910 | 24000 | 0.3648 | 3.5861 |
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+ | 3.4129 | 7.2823 | 25000 | 0.3650 | 3.5968 |
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+ | 3.4446 | 7.5736 | 26000 | 0.3656 | 3.5881 |
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+ | 3.4571 | 7.8648 | 27000 | 0.3665 | 3.5767 |
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+ | 3.3761 | 8.1561 | 28000 | 0.3660 | 3.5908 |
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+ | 3.4115 | 8.4474 | 29000 | 0.3668 | 3.5820 |
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+ | 3.4263 | 8.7387 | 30000 | 0.3674 | 3.5728 |
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+ | 3.3151 | 9.0300 | 31000 | 0.3672 | 3.5807 |
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+ | 3.3704 | 9.3213 | 32000 | 0.3676 | 3.5774 |
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+ | 3.3941 | 9.6126 | 33000 | 0.3684 | 3.5672 |
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+ | 3.4099 | 9.9039 | 34000 | 0.3685 | 3.5598 |
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+ | 3.3391 | 10.1952 | 35000 | 0.3687 | 3.5720 |
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+ | 3.3714 | 10.4865 | 36000 | 0.3689 | 3.5661 |
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+ | 3.3904 | 10.7777 | 37000 | 0.3692 | 3.5583 |
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+ | 3.2915 | 11.0690 | 38000 | 0.3692 | 3.5657 |
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+ | 3.3322 | 11.3603 | 39000 | 0.3696 | 3.5637 |
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+ | 3.3624 | 11.6516 | 40000 | 0.3703 | 3.5523 |
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+ | 3.3725 | 11.9429 | 41000 | 0.3707 | 3.5477 |
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+ | 3.3112 | 12.2342 | 42000 | 0.3703 | 3.5600 |
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+ | 3.3265 | 12.5255 | 43000 | 0.3705 | 3.5585 |
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+ | 3.3558 | 12.8168 | 44000 | 0.3710 | 3.5482 |
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+ | 3.2621 | 13.1081 | 45000 | 0.3707 | 3.5585 |
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+ | 3.3073 | 13.3994 | 46000 | 0.3709 | 3.5541 |
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+ | 3.3128 | 13.6906 | 47000 | 0.3715 | 3.5445 |
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+ | 3.3353 | 13.9819 | 48000 | 0.3719 | 3.5380 |
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+ | 3.2817 | 14.2732 | 49000 | 0.3712 | 3.5541 |
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+ | 3.2922 | 14.5645 | 50000 | 0.3717 | 3.5449 |
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+ | 3.3127 | 14.8558 | 51000 | 0.3721 | 3.5388 |
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+ | 3.24 | 15.1471 | 52000 | 0.3715 | 3.5560 |
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+ | 3.2817 | 15.4384 | 53000 | 0.3718 | 3.5509 |
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+ | 3.3085 | 15.7297 | 54000 | 0.3725 | 3.5396 |
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+ | 3.2036 | 16.0210 | 55000 | 0.3722 | 3.5509 |
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+ | 3.2468 | 16.3123 | 56000 | 0.3723 | 3.5500 |
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+ | 3.2721 | 16.6036 | 57000 | 0.3725 | 3.5433 |
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+ | 3.287 | 16.8948 | 58000 | 0.3729 | 3.5389 |
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+ | 3.2282 | 17.1861 | 59000 | 0.3723 | 3.5531 |
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+ | 3.259 | 17.4774 | 60000 | 0.3727 | 3.5445 |
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+ | 3.2744 | 17.7687 | 61000 | 0.3731 | 3.5403 |
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+ | 3.1841 | 18.0600 | 62000 | 0.3726 | 3.5517 |
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+ | 3.2267 | 18.3513 | 63000 | 0.3730 | 3.5450 |
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+ | 3.2562 | 18.6426 | 64000 | 0.3733 | 3.5392 |
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+ | 3.2731 | 18.9339 | 65000 | 0.3738 | 3.5309 |
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+ | 3.2079 | 19.2252 | 66000 | 0.3729 | 3.5485 |
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+ | 3.232 | 19.5165 | 67000 | 0.3732 | 3.5456 |
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+ | 3.2523 | 19.8077 | 68000 | 0.3737 | 3.5349 |
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+ | 3.1787 | 20.0990 | 69000 | 0.3732 | 3.5523 |
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+ | 3.2129 | 20.3903 | 70000 | 0.3735 | 3.5441 |
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+ | 3.2372 | 20.6816 | 71000 | 0.3736 | 3.5403 |
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+ | 3.2417 | 20.9729 | 72000 | 0.3744 | 3.5276 |
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+ | 3.1999 | 21.2642 | 73000 | 0.3732 | 3.5487 |
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+ | 3.2063 | 21.5555 | 74000 | 0.3740 | 3.5413 |
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+ | 3.2351 | 21.8468 | 75000 | 0.3744 | 3.5350 |
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+ | 3.1673 | 22.1381 | 76000 | 0.3734 | 3.5516 |
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+ | 3.1952 | 22.4294 | 77000 | 0.3741 | 3.5438 |
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+ | 3.2208 | 22.7207 | 78000 | 0.3745 | 3.5375 |
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+ | 3.1547 | 23.0119 | 79000 | 0.3741 | 3.5452 |
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+ | 3.1794 | 23.3032 | 80000 | 0.3740 | 3.5466 |
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+ | 3.1802 | 23.5945 | 81000 | 3.5514 | 0.3737 |
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+ | 3.1925 | 23.8858 | 82000 | 3.5414 | 0.3742 |
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+ | 3.1486 | 24.1771 | 83000 | 3.5541 | 0.3736 |
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+ | 3.1976 | 24.4684 | 84000 | 3.5431 | 0.3743 |
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+ | 3.203 | 24.7597 | 85000 | 3.5326 | 0.3748 |
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+ | 3.1274 | 25.0510 | 86000 | 3.5513 | 0.3740 |
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+ | 3.1714 | 25.3423 | 87000 | 3.5461 | 0.3741 |
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+ | 3.1892 | 25.6336 | 88000 | 3.5390 | 0.3749 |
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+ | 3.1966 | 25.9248 | 89000 | 3.5339 | 0.3752 |
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+ | 3.1437 | 26.2161 | 90000 | 3.5473 | 0.3744 |
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+ | 3.1676 | 26.5074 | 91000 | 3.5460 | 0.3747 |
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+ | 3.1991 | 26.7987 | 92000 | 3.5318 | 0.3752 |
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+ | 3.1179 | 27.0900 | 93000 | 3.5488 | 0.3746 |
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+ | 3.145 | 27.3813 | 94000 | 3.5459 | 0.3747 |
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+ | 3.1681 | 27.6726 | 95000 | 3.5362 | 0.3753 |
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+ | 3.1854 | 27.9639 | 96000 | 3.5326 | 0.3754 |
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+ | 3.1204 | 28.2552 | 97000 | 3.5484 | 0.3746 |
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+ | 3.1424 | 28.5465 | 98000 | 3.5429 | 0.3751 |
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+ | 3.1686 | 28.8378 | 99000 | 3.5335 | 0.3756 |
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+ | 3.1 | 29.1290 | 100000 | 3.5498 | 0.3748 |
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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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