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  1. cost_to_carry_frequency_1001/README.md +172 -0
  2. cost_to_carry_frequency_1001/all_results.json +16 -0
  3. cost_to_carry_frequency_1001/checkpoint-100000/config.json +31 -0
  4. cost_to_carry_frequency_1001/checkpoint-100000/generation_config.json +6 -0
  5. cost_to_carry_frequency_1001/checkpoint-100000/merges.txt +0 -0
  6. cost_to_carry_frequency_1001/checkpoint-100000/model.safetensors +3 -0
  7. cost_to_carry_frequency_1001/checkpoint-100000/optimizer.pt +3 -0
  8. cost_to_carry_frequency_1001/checkpoint-100000/rng_state.pth +3 -0
  9. cost_to_carry_frequency_1001/checkpoint-100000/scaler.pt +3 -0
  10. cost_to_carry_frequency_1001/checkpoint-100000/scheduler.pt +3 -0
  11. cost_to_carry_frequency_1001/checkpoint-100000/special_tokens_map.json +5 -0
  12. cost_to_carry_frequency_1001/checkpoint-100000/tokenizer.json +0 -0
  13. cost_to_carry_frequency_1001/checkpoint-100000/tokenizer_config.json +20 -0
  14. cost_to_carry_frequency_1001/checkpoint-100000/trainer_state.json +0 -0
  15. cost_to_carry_frequency_1001/checkpoint-100000/training_args.bin +3 -0
  16. cost_to_carry_frequency_1001/checkpoint-100000/vocab.json +0 -0
  17. cost_to_carry_frequency_1001/checkpoint-40000/config.json +31 -0
  18. cost_to_carry_frequency_1001/checkpoint-40000/generation_config.json +6 -0
  19. cost_to_carry_frequency_1001/checkpoint-40000/merges.txt +0 -0
  20. cost_to_carry_frequency_1001/checkpoint-40000/model.safetensors +3 -0
  21. cost_to_carry_frequency_1001/checkpoint-40000/optimizer.pt +3 -0
  22. cost_to_carry_frequency_1001/checkpoint-40000/rng_state.pth +3 -0
  23. cost_to_carry_frequency_1001/checkpoint-40000/scaler.pt +3 -0
  24. cost_to_carry_frequency_1001/checkpoint-40000/scheduler.pt +3 -0
  25. cost_to_carry_frequency_1001/checkpoint-40000/special_tokens_map.json +5 -0
  26. cost_to_carry_frequency_1001/checkpoint-40000/tokenizer.json +0 -0
  27. cost_to_carry_frequency_1001/checkpoint-40000/tokenizer_config.json +20 -0
  28. cost_to_carry_frequency_1001/checkpoint-40000/trainer_state.json +0 -0
  29. cost_to_carry_frequency_1001/checkpoint-40000/training_args.bin +3 -0
  30. cost_to_carry_frequency_1001/checkpoint-40000/vocab.json +0 -0
  31. cost_to_carry_frequency_1001/checkpoint-70000/config.json +31 -0
  32. cost_to_carry_frequency_1001/checkpoint-70000/generation_config.json +6 -0
  33. cost_to_carry_frequency_1001/checkpoint-70000/merges.txt +0 -0
  34. cost_to_carry_frequency_1001/checkpoint-70000/model.safetensors +3 -0
  35. cost_to_carry_frequency_1001/checkpoint-70000/optimizer.pt +3 -0
  36. cost_to_carry_frequency_1001/checkpoint-70000/rng_state.pth +3 -0
  37. cost_to_carry_frequency_1001/checkpoint-70000/scaler.pt +3 -0
  38. cost_to_carry_frequency_1001/checkpoint-70000/scheduler.pt +3 -0
  39. cost_to_carry_frequency_1001/checkpoint-70000/special_tokens_map.json +5 -0
  40. cost_to_carry_frequency_1001/checkpoint-70000/tokenizer.json +0 -0
  41. cost_to_carry_frequency_1001/checkpoint-70000/tokenizer_config.json +20 -0
  42. cost_to_carry_frequency_1001/checkpoint-70000/trainer_state.json +0 -0
  43. cost_to_carry_frequency_1001/checkpoint-70000/training_args.bin +3 -0
  44. cost_to_carry_frequency_1001/checkpoint-70000/vocab.json +0 -0
  45. cost_to_carry_frequency_1001/checkpoint-80000/config.json +31 -0
  46. cost_to_carry_frequency_1001/checkpoint-80000/generation_config.json +6 -0
  47. cost_to_carry_frequency_1001/checkpoint-80000/merges.txt +0 -0
  48. cost_to_carry_frequency_1001/checkpoint-80000/model.safetensors +3 -0
  49. cost_to_carry_frequency_1001/checkpoint-80000/optimizer.pt +3 -0
  50. cost_to_carry_frequency_1001/checkpoint-80000/rng_state.pth +3 -0
cost_to_carry_frequency_1001/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_cost_to_carry_frequency_1001
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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/8zrhwait)
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+ # exceptions_exp2_cost_to_carry_frequency_1001
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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: 3.5568
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+ - Accuracy: 0.3698
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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: 1001
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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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+ | 4.8349 | 0.2913 | 1000 | 0.2546 | 4.7532 |
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+ | 4.3363 | 0.5826 | 2000 | 0.2986 | 4.2907 |
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+ | 4.1568 | 0.8739 | 3000 | 0.3155 | 4.0980 |
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+ | 3.9878 | 1.1652 | 4000 | 0.3255 | 3.9938 |
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+ | 3.9343 | 1.4565 | 5000 | 0.3317 | 3.9163 |
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+ | 3.8895 | 1.7478 | 6000 | 0.3368 | 3.8571 |
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+ | 3.7541 | 2.0390 | 7000 | 0.3412 | 3.8186 |
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+ | 3.7621 | 2.3303 | 8000 | 0.3437 | 3.7863 |
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+ | 3.7407 | 2.6216 | 9000 | 0.3468 | 3.7544 |
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+ | 3.7164 | 2.9130 | 10000 | 0.3496 | 3.7293 |
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+ | 3.6345 | 3.2042 | 11000 | 0.3515 | 3.7179 |
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+ | 3.6454 | 3.4955 | 12000 | 0.3534 | 3.6975 |
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+ | 3.6355 | 3.7868 | 13000 | 0.3547 | 3.6775 |
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+ | 3.5475 | 4.0781 | 14000 | 0.3562 | 3.6730 |
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+ | 3.5685 | 4.3694 | 15000 | 0.3569 | 3.6620 |
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+ | 3.5778 | 4.6607 | 16000 | 0.3582 | 3.6479 |
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+ | 3.5844 | 4.9520 | 17000 | 0.3595 | 3.6320 |
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+ | 3.5025 | 5.2432 | 18000 | 0.3599 | 3.6374 |
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+ | 3.5089 | 5.5345 | 19000 | 0.3610 | 3.6249 |
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+ | 3.5334 | 5.8259 | 20000 | 0.3620 | 3.6139 |
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+ | 3.4438 | 6.1171 | 21000 | 0.3620 | 3.6201 |
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+ | 3.4704 | 6.4084 | 22000 | 0.3629 | 3.6089 |
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+ | 3.4899 | 6.6997 | 23000 | 0.3638 | 3.6004 |
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+ | 3.4974 | 6.9910 | 24000 | 0.3647 | 3.5901 |
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+ | 3.4278 | 7.2823 | 25000 | 0.3648 | 3.5997 |
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+ | 3.444 | 7.5736 | 26000 | 0.3654 | 3.5886 |
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+ | 3.4694 | 7.8649 | 27000 | 0.3658 | 3.5817 |
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+ | 3.3704 | 8.1561 | 28000 | 0.3659 | 3.5886 |
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+ | 3.4165 | 8.4474 | 29000 | 0.3665 | 3.5834 |
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+ | 3.4266 | 8.7388 | 30000 | 0.3671 | 3.5733 |
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+ | 3.3195 | 9.0300 | 31000 | 0.3672 | 3.5814 |
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+ | 3.3913 | 9.3213 | 32000 | 0.3673 | 3.5770 |
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+ | 3.4035 | 9.6126 | 33000 | 0.3679 | 3.5706 |
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+ | 3.4133 | 9.9039 | 34000 | 0.3683 | 3.5632 |
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+ | 3.3355 | 10.1952 | 35000 | 0.3680 | 3.5764 |
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+ | 3.3782 | 10.4865 | 36000 | 0.3686 | 3.5681 |
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+ | 3.3796 | 10.7778 | 37000 | 0.3691 | 3.5603 |
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+ | 3.2878 | 11.0690 | 38000 | 0.3689 | 3.5698 |
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+ | 3.3437 | 11.3603 | 39000 | 0.3691 | 3.5676 |
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+ | 3.3602 | 11.6517 | 40000 | 0.3698 | 3.5568 |
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+ | 3.3774 | 11.9430 | 41000 | 0.3702 | 3.5490 |
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+ | 3.3016 | 12.2342 | 42000 | 0.3695 | 3.5640 |
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+ | 3.3469 | 12.5255 | 43000 | 0.3703 | 3.5561 |
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+ | 3.3608 | 12.8168 | 44000 | 0.3708 | 3.5487 |
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+ | 3.2594 | 13.1081 | 45000 | 0.3704 | 3.5596 |
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+ | 3.2975 | 13.3994 | 46000 | 0.3705 | 3.5558 |
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+ | 3.3248 | 13.6907 | 47000 | 0.3709 | 3.5499 |
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+ | 3.3497 | 13.9820 | 48000 | 0.3718 | 3.5397 |
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+ | 3.2825 | 14.2732 | 49000 | 0.3710 | 3.5577 |
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+ | 3.2991 | 14.5646 | 50000 | 0.3709 | 3.5529 |
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+ | 3.312 | 14.8559 | 51000 | 0.3721 | 3.5414 |
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+ | 3.2651 | 15.1471 | 52000 | 0.3711 | 3.5577 |
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+ | 3.2765 | 15.4384 | 53000 | 0.3716 | 3.5510 |
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+ | 3.3027 | 15.7297 | 54000 | 0.3722 | 3.5434 |
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+ | 3.2035 | 16.0210 | 55000 | 0.3715 | 3.5553 |
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+ | 3.2571 | 16.3123 | 56000 | 0.3720 | 3.5523 |
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+ | 3.2808 | 16.6036 | 57000 | 0.3721 | 3.5462 |
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+ | 3.2875 | 16.8949 | 58000 | 0.3726 | 3.5378 |
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+ | 3.2199 | 17.1861 | 59000 | 0.3721 | 3.5521 |
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+ | 3.2427 | 17.4775 | 60000 | 0.3728 | 3.5461 |
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+ | 3.2725 | 17.7688 | 61000 | 0.3729 | 3.5392 |
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+ | 3.1907 | 18.0600 | 62000 | 0.3723 | 3.5532 |
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+ | 3.2403 | 18.3513 | 63000 | 0.3725 | 3.5507 |
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+ | 3.2635 | 18.6426 | 64000 | 0.3728 | 3.5408 |
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+ | 3.2826 | 18.9339 | 65000 | 0.3732 | 3.5314 |
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+ | 3.2112 | 19.2252 | 66000 | 0.3726 | 3.5499 |
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+ | 3.2371 | 19.5165 | 67000 | 0.3729 | 3.5425 |
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+ | 3.2569 | 19.8078 | 68000 | 0.3738 | 3.5353 |
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+ | 3.1833 | 20.0990 | 69000 | 0.3728 | 3.5502 |
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+ | 3.2127 | 20.3904 | 70000 | 0.3732 | 3.5441 |
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+ | 3.2389 | 20.6817 | 71000 | 0.3735 | 3.5391 |
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+ | 3.2485 | 20.9730 | 72000 | 0.3740 | 3.5297 |
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+ | 3.1872 | 21.2642 | 73000 | 0.3731 | 3.5496 |
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+ | 3.2282 | 21.5555 | 74000 | 0.3737 | 3.5427 |
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+ | 3.2416 | 21.8468 | 75000 | 0.3743 | 3.5323 |
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+ | 3.1625 | 22.1381 | 76000 | 0.3732 | 3.5518 |
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+ | 3.2022 | 22.4294 | 77000 | 0.3736 | 3.5422 |
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+ | 3.2332 | 22.7207 | 78000 | 0.3743 | 3.5360 |
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+ | 3.154 | 23.0119 | 79000 | 0.3739 | 3.5455 |
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+ | 3.17 | 23.3033 | 80000 | 0.3736 | 3.5483 |
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+ | 3.1777 | 23.5946 | 81000 | 3.5508 | 0.3735 |
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+ | 3.1857 | 23.8859 | 82000 | 3.5428 | 0.3739 |
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+ | 3.154 | 24.1774 | 83000 | 3.5539 | 0.3734 |
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+ | 3.2043 | 24.4687 | 84000 | 3.5451 | 0.3737 |
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+ | 3.2072 | 24.7600 | 85000 | 3.5331 | 0.3746 |
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+ | 3.126 | 25.0513 | 86000 | 3.5491 | 0.3739 |
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+ | 3.1699 | 25.3426 | 87000 | 3.5480 | 0.3740 |
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+ | 3.193 | 25.6339 | 88000 | 3.5393 | 0.3743 |
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+ | 3.2127 | 25.9252 | 89000 | 3.5282 | 0.3751 |
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+ | 3.149 | 26.2164 | 90000 | 3.5491 | 0.3742 |
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+ | 3.1732 | 26.5077 | 91000 | 3.5452 | 0.3744 |
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+ | 3.1891 | 26.7991 | 92000 | 3.5350 | 0.3748 |
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+ | 3.1126 | 27.0903 | 93000 | 3.5532 | 0.3742 |
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+ | 3.1489 | 27.3816 | 94000 | 3.5459 | 0.3741 |
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+ | 3.1777 | 27.6729 | 95000 | 3.5390 | 0.3749 |
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+ | 3.1906 | 27.9642 | 96000 | 3.5350 | 0.3750 |
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+ | 3.1367 | 28.2555 | 97000 | 3.5522 | 0.3744 |
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+ | 3.1598 | 28.5468 | 98000 | 3.5442 | 0.3747 |
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+ | 3.1649 | 28.8381 | 99000 | 3.5347 | 0.3751 |
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+ | 3.1082 | 29.1293 | 100000 | 3.5540 | 0.3741 |
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+ | 3.1409 | 29.4206 | 101000 | 3.5481 | 0.3747 |
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+ | 3.1688 | 29.7120 | 102000 | 3.5373 | 0.3749 |
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+ | 3.1564 | 30.0032 | 103000 | 3.5466 | 0.3746 |
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+ | 3.1222 | 30.2945 | 104000 | 3.5510 | 0.3745 |
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+ | 3.1444 | 30.5858 | 105000 | 3.5422 | 0.3751 |
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+ | 3.1575 | 30.8771 | 106000 | 3.5330 | 0.3759 |
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+ | 3.0957 | 31.1684 | 107000 | 3.5511 | 0.3745 |
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+ | 3.1194 | 31.4597 | 108000 | 3.5446 | 0.3749 |
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+ | 3.134 | 31.7510 | 109000 | 3.5384 | 0.3753 |
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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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