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  1. last_to_carry_frequency_3591/README.md +172 -0
  2. last_to_carry_frequency_3591/all_results.json +16 -0
  3. last_to_carry_frequency_3591/checkpoint-100000/config.json +31 -0
  4. last_to_carry_frequency_3591/checkpoint-100000/generation_config.json +6 -0
  5. last_to_carry_frequency_3591/checkpoint-100000/merges.txt +0 -0
  6. last_to_carry_frequency_3591/checkpoint-100000/model.safetensors +3 -0
  7. last_to_carry_frequency_3591/checkpoint-100000/optimizer.pt +3 -0
  8. last_to_carry_frequency_3591/checkpoint-100000/rng_state.pth +3 -0
  9. last_to_carry_frequency_3591/checkpoint-100000/scaler.pt +3 -0
  10. last_to_carry_frequency_3591/checkpoint-100000/scheduler.pt +3 -0
  11. last_to_carry_frequency_3591/checkpoint-100000/special_tokens_map.json +5 -0
  12. last_to_carry_frequency_3591/checkpoint-100000/tokenizer.json +0 -0
  13. last_to_carry_frequency_3591/checkpoint-100000/tokenizer_config.json +20 -0
  14. last_to_carry_frequency_3591/checkpoint-100000/trainer_state.json +0 -0
  15. last_to_carry_frequency_3591/checkpoint-100000/training_args.bin +3 -0
  16. last_to_carry_frequency_3591/checkpoint-100000/vocab.json +0 -0
  17. last_to_carry_frequency_3591/checkpoint-40000/config.json +31 -0
  18. last_to_carry_frequency_3591/checkpoint-40000/generation_config.json +6 -0
  19. last_to_carry_frequency_3591/checkpoint-40000/merges.txt +0 -0
  20. last_to_carry_frequency_3591/checkpoint-40000/model.safetensors +3 -0
  21. last_to_carry_frequency_3591/checkpoint-40000/optimizer.pt +3 -0
  22. last_to_carry_frequency_3591/checkpoint-40000/rng_state.pth +3 -0
  23. last_to_carry_frequency_3591/checkpoint-40000/scaler.pt +3 -0
  24. last_to_carry_frequency_3591/checkpoint-40000/scheduler.pt +3 -0
  25. last_to_carry_frequency_3591/checkpoint-40000/special_tokens_map.json +5 -0
  26. last_to_carry_frequency_3591/checkpoint-40000/tokenizer.json +0 -0
  27. last_to_carry_frequency_3591/checkpoint-40000/tokenizer_config.json +20 -0
  28. last_to_carry_frequency_3591/checkpoint-40000/trainer_state.json +0 -0
  29. last_to_carry_frequency_3591/checkpoint-40000/training_args.bin +3 -0
  30. last_to_carry_frequency_3591/checkpoint-40000/vocab.json +0 -0
  31. last_to_carry_frequency_3591/checkpoint-70000/config.json +31 -0
  32. last_to_carry_frequency_3591/checkpoint-70000/generation_config.json +6 -0
  33. last_to_carry_frequency_3591/checkpoint-70000/merges.txt +0 -0
  34. last_to_carry_frequency_3591/checkpoint-70000/model.safetensors +3 -0
  35. last_to_carry_frequency_3591/checkpoint-70000/optimizer.pt +3 -0
  36. last_to_carry_frequency_3591/checkpoint-70000/rng_state.pth +3 -0
  37. last_to_carry_frequency_3591/checkpoint-70000/scaler.pt +3 -0
  38. last_to_carry_frequency_3591/checkpoint-70000/scheduler.pt +3 -0
  39. last_to_carry_frequency_3591/checkpoint-70000/special_tokens_map.json +5 -0
  40. last_to_carry_frequency_3591/checkpoint-70000/tokenizer.json +0 -0
  41. last_to_carry_frequency_3591/checkpoint-70000/tokenizer_config.json +20 -0
  42. last_to_carry_frequency_3591/checkpoint-70000/trainer_state.json +0 -0
  43. last_to_carry_frequency_3591/checkpoint-70000/training_args.bin +3 -0
  44. last_to_carry_frequency_3591/checkpoint-70000/vocab.json +0 -0
  45. last_to_carry_frequency_3591/checkpoint-80000/config.json +31 -0
  46. last_to_carry_frequency_3591/checkpoint-80000/generation_config.json +6 -0
  47. last_to_carry_frequency_3591/checkpoint-80000/merges.txt +0 -0
  48. last_to_carry_frequency_3591/checkpoint-80000/model.safetensors +3 -0
  49. last_to_carry_frequency_3591/checkpoint-80000/optimizer.pt +3 -0
  50. last_to_carry_frequency_3591/checkpoint-80000/rng_state.pth +3 -0
last_to_carry_frequency_3591/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_3591
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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/vhpyxavw)
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+ # exceptions_exp2_last_to_carry_frequency_3591
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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: 3.5589
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+ - Accuracy: 0.3697
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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: 3591
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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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+ | 4.7962 | 0.2913 | 1000 | 0.2567 | 4.7344 |
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+ | 4.3297 | 0.5826 | 2000 | 0.3001 | 4.2781 |
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+ | 4.1356 | 0.8739 | 3000 | 0.3163 | 4.0931 |
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+ | 3.9823 | 1.1652 | 4000 | 0.3256 | 3.9840 |
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+ | 3.9224 | 1.4565 | 5000 | 0.3325 | 3.9082 |
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+ | 3.8689 | 1.7477 | 6000 | 0.3377 | 3.8534 |
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+ | 3.7404 | 2.0390 | 7000 | 0.3417 | 3.8115 |
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+ | 3.7497 | 2.3303 | 8000 | 0.3445 | 3.7814 |
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+ | 3.7349 | 2.6216 | 9000 | 0.3472 | 3.7521 |
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+ | 3.7105 | 2.9129 | 10000 | 0.3500 | 3.7253 |
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+ | 3.6434 | 3.2042 | 11000 | 0.3516 | 3.7147 |
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+ | 3.6371 | 3.4955 | 12000 | 0.3532 | 3.6968 |
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+ | 3.6378 | 3.7868 | 13000 | 0.3549 | 3.6765 |
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+ | 3.5409 | 4.0781 | 14000 | 0.3559 | 3.6729 |
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+ | 3.5582 | 4.3694 | 15000 | 0.3572 | 3.6609 |
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+ | 3.5766 | 4.6606 | 16000 | 0.3583 | 3.6448 |
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+ | 3.5799 | 4.9519 | 17000 | 0.3594 | 3.6335 |
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+ | 3.5054 | 5.2432 | 18000 | 0.3597 | 3.6386 |
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+ | 3.5171 | 5.5345 | 19000 | 0.3608 | 3.6258 |
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+ | 3.5228 | 5.8258 | 20000 | 0.3619 | 3.6150 |
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+ | 3.4441 | 6.1171 | 21000 | 0.3622 | 3.6197 |
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+ | 3.4712 | 6.4084 | 22000 | 0.3629 | 3.6118 |
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+ | 3.4774 | 6.6997 | 23000 | 0.3637 | 3.6026 |
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+ | 3.4949 | 6.9910 | 24000 | 0.3646 | 3.5923 |
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+ | 3.4218 | 7.2823 | 25000 | 0.3645 | 3.5995 |
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+ | 3.4403 | 7.5736 | 26000 | 0.3651 | 3.5926 |
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+ | 3.4593 | 7.8648 | 27000 | 0.3657 | 3.5831 |
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+ | 3.3779 | 8.1561 | 28000 | 0.3657 | 3.5912 |
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+ | 3.4106 | 8.4474 | 29000 | 0.3662 | 3.5861 |
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+ | 3.4274 | 8.7387 | 30000 | 0.3668 | 3.5749 |
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+ | 3.332 | 9.0300 | 31000 | 0.3671 | 3.5860 |
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+ | 3.3749 | 9.3213 | 32000 | 0.3674 | 3.5790 |
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+ | 3.4044 | 9.6126 | 33000 | 0.3678 | 3.5717 |
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+ | 3.4161 | 9.9039 | 34000 | 0.3685 | 3.5642 |
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+ | 3.3287 | 10.1952 | 35000 | 0.3681 | 3.5778 |
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+ | 3.3742 | 10.4865 | 36000 | 0.3685 | 3.5686 |
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+ | 3.3907 | 10.7777 | 37000 | 0.3693 | 3.5602 |
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+ | 3.2882 | 11.0690 | 38000 | 0.3688 | 3.5726 |
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+ | 3.3313 | 11.3603 | 39000 | 0.3687 | 3.5706 |
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+ | 3.3608 | 11.6516 | 40000 | 0.3697 | 3.5589 |
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+ | 3.3646 | 11.9429 | 41000 | 0.3702 | 3.5512 |
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+ | 3.3161 | 12.2342 | 42000 | 0.3698 | 3.5660 |
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+ | 3.3344 | 12.5255 | 43000 | 0.3699 | 3.5577 |
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+ | 3.3424 | 12.8168 | 44000 | 0.3705 | 3.5492 |
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+ | 3.2629 | 13.1081 | 45000 | 0.3698 | 3.5673 |
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+ | 3.3083 | 13.3994 | 46000 | 0.3703 | 3.5576 |
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+ | 3.3251 | 13.6906 | 47000 | 0.3711 | 3.5514 |
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+ | 3.3287 | 13.9819 | 48000 | 0.3713 | 3.5429 |
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+ | 3.2769 | 14.2732 | 49000 | 0.3708 | 3.5584 |
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+ | 3.3032 | 14.5645 | 50000 | 0.3714 | 3.5491 |
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+ | 3.3342 | 14.8558 | 51000 | 0.3717 | 3.5436 |
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+ | 3.2565 | 15.1471 | 52000 | 0.3714 | 3.5586 |
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+ | 3.2866 | 15.4384 | 53000 | 0.3714 | 3.5542 |
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+ | 3.2947 | 15.7297 | 54000 | 0.3719 | 3.5451 |
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+ | 3.2092 | 16.0210 | 55000 | 0.3714 | 3.5539 |
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+ | 3.2696 | 16.3123 | 56000 | 0.3719 | 3.5537 |
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+ | 3.2885 | 16.6036 | 57000 | 0.3720 | 3.5494 |
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+ | 3.294 | 16.8948 | 58000 | 0.3725 | 3.5372 |
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+ | 3.2344 | 17.1861 | 59000 | 0.3720 | 3.5538 |
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+ | 3.2505 | 17.4774 | 60000 | 0.3720 | 3.5486 |
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+ | 3.2791 | 17.7687 | 61000 | 0.3728 | 3.5400 |
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+ | 3.1939 | 18.0600 | 62000 | 0.3722 | 3.5512 |
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+ | 3.2342 | 18.3513 | 63000 | 0.3721 | 3.5512 |
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+ | 3.2567 | 18.6426 | 64000 | 0.3728 | 3.5424 |
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+ | 3.2814 | 18.9339 | 65000 | 0.3734 | 3.5325 |
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+ | 3.2312 | 19.2252 | 66000 | 0.3725 | 3.5551 |
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+ | 3.2426 | 19.5165 | 67000 | 0.3727 | 3.5481 |
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+ | 3.2532 | 19.8077 | 68000 | 0.3732 | 3.5412 |
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+ | 3.1692 | 20.0990 | 69000 | 0.3728 | 3.5526 |
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+ | 3.2148 | 20.3903 | 70000 | 0.3729 | 3.5470 |
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+ | 3.2312 | 20.6816 | 71000 | 0.3731 | 3.5397 |
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+ | 3.2604 | 20.9729 | 72000 | 0.3737 | 3.5335 |
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+ | 3.1903 | 21.2642 | 73000 | 0.3731 | 3.5486 |
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+ | 3.2295 | 21.5555 | 74000 | 0.3734 | 3.5450 |
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+ | 3.2327 | 21.8468 | 75000 | 0.3740 | 3.5349 |
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+ | 3.1451 | 22.1381 | 76000 | 0.3727 | 3.5534 |
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+ | 3.1956 | 22.4294 | 77000 | 0.3735 | 3.5484 |
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+ | 3.2134 | 22.7207 | 78000 | 0.3735 | 3.5387 |
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+ | 3.1542 | 23.0119 | 79000 | 0.3731 | 3.5543 |
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+ | 3.1608 | 23.3032 | 80000 | 0.3732 | 3.5508 |
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+ | 3.1725 | 23.5945 | 81000 | 3.5530 | 0.3732 |
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+ | 3.1946 | 23.8858 | 82000 | 3.5443 | 0.3738 |
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+ | 3.1572 | 24.1771 | 83000 | 3.5598 | 0.3730 |
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+ | 3.1841 | 24.4684 | 84000 | 3.5440 | 0.3736 |
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+ | 3.2113 | 24.7597 | 85000 | 3.5388 | 0.3743 |
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+ | 3.121 | 25.0510 | 86000 | 3.5537 | 0.3734 |
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+ | 3.1624 | 25.3423 | 87000 | 3.5482 | 0.3738 |
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+ | 3.1908 | 25.6336 | 88000 | 3.5439 | 0.3741 |
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+ | 3.1936 | 25.9248 | 89000 | 3.5319 | 0.3748 |
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+ | 3.1478 | 26.2161 | 90000 | 3.5510 | 0.3737 |
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+ | 3.1713 | 26.5074 | 91000 | 3.5444 | 0.3740 |
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+ | 3.1895 | 26.7987 | 92000 | 3.5355 | 0.3744 |
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+ | 3.1082 | 27.0900 | 93000 | 3.5560 | 0.3739 |
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+ | 3.1543 | 27.3813 | 94000 | 3.5485 | 0.3740 |
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+ | 3.1656 | 27.6726 | 95000 | 3.5379 | 0.3746 |
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+ | 3.1859 | 27.9639 | 96000 | 3.5337 | 0.3751 |
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+ | 3.1304 | 28.2552 | 97000 | 3.5524 | 0.3741 |
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+ | 3.1453 | 28.5465 | 98000 | 3.5447 | 0.3743 |
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+ | 3.1717 | 28.8378 | 99000 | 3.5363 | 0.3750 |
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+ | 3.0999 | 29.1290 | 100000 | 3.5560 | 0.3740 |
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+ | 3.1412 | 29.4203 | 101000 | 3.5490 | 0.3743 |
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+ | 3.1638 | 29.7116 | 102000 | 3.5413 | 0.3749 |
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+ | 3.1551 | 30.0029 | 103000 | 3.5489 | 0.3747 |
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+ | 3.1229 | 30.2942 | 104000 | 3.5493 | 0.3744 |
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+ | 3.1301 | 31.4594 | 108000 | 3.5488 | 0.3748 |
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+ | 3.1514 | 31.7507 | 109000 | 3.5407 | 0.3754 |
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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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