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  1. cost_to_carry_frequency_5039/README.md +163 -0
  2. cost_to_carry_frequency_5039/all_results.json +16 -0
  3. cost_to_carry_frequency_5039/checkpoint-100000/config.json +31 -0
  4. cost_to_carry_frequency_5039/checkpoint-100000/generation_config.json +6 -0
  5. cost_to_carry_frequency_5039/checkpoint-100000/merges.txt +0 -0
  6. cost_to_carry_frequency_5039/checkpoint-100000/model.safetensors +3 -0
  7. cost_to_carry_frequency_5039/checkpoint-100000/optimizer.pt +3 -0
  8. cost_to_carry_frequency_5039/checkpoint-100000/rng_state.pth +3 -0
  9. cost_to_carry_frequency_5039/checkpoint-100000/scaler.pt +3 -0
  10. cost_to_carry_frequency_5039/checkpoint-100000/scheduler.pt +3 -0
  11. cost_to_carry_frequency_5039/checkpoint-100000/special_tokens_map.json +5 -0
  12. cost_to_carry_frequency_5039/checkpoint-100000/tokenizer.json +0 -0
  13. cost_to_carry_frequency_5039/checkpoint-100000/tokenizer_config.json +20 -0
  14. cost_to_carry_frequency_5039/checkpoint-100000/trainer_state.json +0 -0
  15. cost_to_carry_frequency_5039/checkpoint-100000/training_args.bin +3 -0
  16. cost_to_carry_frequency_5039/checkpoint-100000/vocab.json +0 -0
  17. cost_to_carry_frequency_5039/checkpoint-40000/config.json +31 -0
  18. cost_to_carry_frequency_5039/checkpoint-40000/generation_config.json +6 -0
  19. cost_to_carry_frequency_5039/checkpoint-40000/merges.txt +0 -0
  20. cost_to_carry_frequency_5039/checkpoint-40000/model.safetensors +3 -0
  21. cost_to_carry_frequency_5039/checkpoint-40000/optimizer.pt +3 -0
  22. cost_to_carry_frequency_5039/checkpoint-40000/rng_state.pth +3 -0
  23. cost_to_carry_frequency_5039/checkpoint-40000/scaler.pt +3 -0
  24. cost_to_carry_frequency_5039/checkpoint-40000/scheduler.pt +3 -0
  25. cost_to_carry_frequency_5039/checkpoint-40000/special_tokens_map.json +5 -0
  26. cost_to_carry_frequency_5039/checkpoint-40000/tokenizer.json +0 -0
  27. cost_to_carry_frequency_5039/checkpoint-40000/tokenizer_config.json +20 -0
  28. cost_to_carry_frequency_5039/checkpoint-40000/trainer_state.json +0 -0
  29. cost_to_carry_frequency_5039/checkpoint-40000/training_args.bin +3 -0
  30. cost_to_carry_frequency_5039/checkpoint-40000/vocab.json +0 -0
  31. cost_to_carry_frequency_5039/checkpoint-70000/config.json +31 -0
  32. cost_to_carry_frequency_5039/checkpoint-70000/generation_config.json +6 -0
  33. cost_to_carry_frequency_5039/checkpoint-70000/merges.txt +0 -0
  34. cost_to_carry_frequency_5039/checkpoint-70000/model.safetensors +3 -0
  35. cost_to_carry_frequency_5039/checkpoint-70000/optimizer.pt +3 -0
  36. cost_to_carry_frequency_5039/checkpoint-70000/rng_state.pth +3 -0
  37. cost_to_carry_frequency_5039/checkpoint-70000/scaler.pt +3 -0
  38. cost_to_carry_frequency_5039/checkpoint-70000/scheduler.pt +3 -0
  39. cost_to_carry_frequency_5039/checkpoint-70000/special_tokens_map.json +5 -0
  40. cost_to_carry_frequency_5039/checkpoint-70000/tokenizer.json +0 -0
  41. cost_to_carry_frequency_5039/checkpoint-70000/tokenizer_config.json +20 -0
  42. cost_to_carry_frequency_5039/checkpoint-70000/trainer_state.json +0 -0
  43. cost_to_carry_frequency_5039/checkpoint-70000/training_args.bin +3 -0
  44. cost_to_carry_frequency_5039/checkpoint-70000/vocab.json +0 -0
  45. cost_to_carry_frequency_5039/checkpoint-80000/config.json +31 -0
  46. cost_to_carry_frequency_5039/checkpoint-80000/generation_config.json +6 -0
  47. cost_to_carry_frequency_5039/checkpoint-80000/merges.txt +0 -0
  48. cost_to_carry_frequency_5039/checkpoint-80000/model.safetensors +3 -0
  49. cost_to_carry_frequency_5039/checkpoint-80000/optimizer.pt +3 -0
  50. cost_to_carry_frequency_5039/checkpoint-80000/rng_state.pth +3 -0
cost_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_cost_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/4fku4nxn)
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+ # exceptions_exp2_cost_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: 3.5551
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+ - Accuracy: 0.3699
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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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+ | 4.8031 | 0.2913 | 1000 | 0.2572 | 4.7371 |
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+ | 4.3318 | 0.5826 | 2000 | 0.3002 | 4.2790 |
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+ | 4.1345 | 0.8739 | 3000 | 0.3153 | 4.0969 |
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+ | 3.9889 | 1.1652 | 4000 | 0.3256 | 3.9892 |
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+ | 3.9416 | 1.4565 | 5000 | 0.3317 | 3.9164 |
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+ | 3.8766 | 1.7478 | 6000 | 0.3373 | 3.8531 |
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+ | 3.7531 | 2.0390 | 7000 | 0.3410 | 3.8140 |
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+ | 3.751 | 2.3303 | 8000 | 0.3444 | 3.7841 |
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+ | 3.7407 | 2.6216 | 9000 | 0.3471 | 3.7547 |
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+ | 3.7165 | 2.9130 | 10000 | 0.3496 | 3.7270 |
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+ | 3.6418 | 3.2042 | 11000 | 0.3515 | 3.7162 |
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+ | 3.6474 | 3.4955 | 12000 | 0.3528 | 3.6974 |
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+ | 3.6488 | 3.7868 | 13000 | 0.3547 | 3.6798 |
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+ | 3.5269 | 4.0781 | 14000 | 0.3558 | 3.6726 |
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+ | 3.5677 | 4.3694 | 15000 | 0.3570 | 3.6612 |
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+ | 3.5762 | 4.6607 | 16000 | 0.3585 | 3.6477 |
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+ | 3.5804 | 4.9520 | 17000 | 0.3595 | 3.6359 |
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+ | 3.4961 | 5.2432 | 18000 | 0.3599 | 3.6374 |
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+ | 3.5296 | 5.5345 | 19000 | 0.3610 | 3.6253 |
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+ | 3.5294 | 5.8259 | 20000 | 0.3620 | 3.6128 |
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+ | 3.4389 | 6.1171 | 21000 | 0.3623 | 3.6182 |
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+ | 3.4645 | 6.4084 | 22000 | 0.3629 | 3.6137 |
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+ | 3.4927 | 6.6997 | 23000 | 0.3633 | 3.6027 |
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+ | 3.4957 | 6.9910 | 24000 | 0.3644 | 3.5913 |
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+ | 3.4221 | 7.2823 | 25000 | 0.3644 | 3.6035 |
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+ | 3.4506 | 7.5736 | 26000 | 0.3649 | 3.5928 |
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+ | 3.463 | 7.8649 | 27000 | 0.3661 | 3.5816 |
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+ | 3.3836 | 8.1561 | 28000 | 0.3655 | 3.5931 |
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+ | 3.4157 | 8.4474 | 29000 | 0.3662 | 3.5836 |
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+ | 3.4279 | 8.7388 | 30000 | 0.3668 | 3.5736 |
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+ | 3.3251 | 9.0300 | 31000 | 0.3668 | 3.5834 |
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+ | 3.3876 | 9.3213 | 32000 | 0.3674 | 3.5795 |
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+ | 3.3896 | 9.6126 | 33000 | 0.3680 | 3.5700 |
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+ | 3.4105 | 9.9039 | 34000 | 0.3684 | 3.5614 |
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+ | 3.3541 | 10.1952 | 35000 | 0.3680 | 3.5770 |
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+ | 3.3641 | 10.4865 | 36000 | 0.3684 | 3.5685 |
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+ | 3.3848 | 10.7778 | 37000 | 0.3691 | 3.5592 |
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+ | 3.2978 | 11.0690 | 38000 | 0.3688 | 3.5681 |
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+ | 3.3493 | 11.3603 | 39000 | 0.3693 | 3.5685 |
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+ | 3.3711 | 11.6517 | 40000 | 0.3699 | 3.5551 |
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+ | 3.3672 | 11.9430 | 41000 | 0.3705 | 3.5509 |
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+ | 3.2958 | 12.2342 | 42000 | 0.3692 | 3.5678 |
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+ | 3.3399 | 12.5255 | 43000 | 0.3698 | 3.5578 |
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+ | 3.3493 | 12.8168 | 44000 | 0.3704 | 3.5509 |
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+ | 3.2654 | 13.1081 | 45000 | 0.3699 | 3.5675 |
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+ | 3.3085 | 13.3994 | 46000 | 0.3708 | 3.5567 |
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+ | 3.3214 | 13.6907 | 47000 | 0.3708 | 3.5490 |
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+ | 3.3432 | 13.9820 | 48000 | 0.3713 | 3.5423 |
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+ | 3.2757 | 14.2732 | 49000 | 0.3709 | 3.5556 |
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+ | 3.3139 | 14.5646 | 50000 | 0.3714 | 3.5503 |
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+ | 3.3253 | 14.8559 | 51000 | 0.3716 | 3.5436 |
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+ | 3.2513 | 15.1471 | 52000 | 0.3711 | 3.5588 |
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+ | 3.2882 | 15.4384 | 53000 | 0.3719 | 3.5489 |
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+ | 3.2945 | 15.7297 | 54000 | 0.3722 | 3.5417 |
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+ | 3.2078 | 16.0210 | 55000 | 0.3716 | 3.5534 |
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+ | 3.2496 | 16.3123 | 56000 | 0.3716 | 3.5539 |
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+ | 3.2868 | 16.6036 | 57000 | 0.3720 | 3.5444 |
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+ | 3.2986 | 16.8949 | 58000 | 0.3727 | 3.5382 |
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+ | 3.2382 | 17.1861 | 59000 | 0.3720 | 3.5537 |
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+ | 3.2572 | 17.4775 | 60000 | 0.3726 | 3.5462 |
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+ | 3.282 | 17.7688 | 61000 | 0.3727 | 3.5398 |
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+ | 3.1919 | 18.0600 | 62000 | 0.3721 | 3.5542 |
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+ | 3.2239 | 18.3513 | 63000 | 0.3723 | 3.5496 |
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+ | 3.2574 | 18.6426 | 64000 | 0.3729 | 3.5422 |
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+ | 3.2834 | 18.9339 | 65000 | 0.3735 | 3.5335 |
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+ | 3.2133 | 19.2252 | 66000 | 0.3724 | 3.5556 |
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+ | 3.2538 | 19.5165 | 67000 | 0.3729 | 3.5449 |
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+ | 3.2508 | 19.8078 | 68000 | 0.3739 | 3.5333 |
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+ | 3.1748 | 20.0990 | 69000 | 0.3729 | 3.5534 |
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+ | 3.2258 | 20.3904 | 70000 | 0.3732 | 3.5467 |
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+ | 3.2398 | 20.6817 | 71000 | 0.3735 | 3.5410 |
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+ | 3.2553 | 20.9730 | 72000 | 0.3741 | 3.5301 |
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+ | 3.1987 | 21.2642 | 73000 | 0.3732 | 3.5475 |
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+ | 3.2248 | 21.5555 | 74000 | 0.3734 | 3.5428 |
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+ | 3.2481 | 21.8468 | 75000 | 0.3737 | 3.5383 |
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+ | 3.1684 | 22.1381 | 76000 | 0.3730 | 3.5516 |
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+ | 3.2101 | 22.4294 | 77000 | 0.3739 | 3.5445 |
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+ | 3.2193 | 22.7207 | 78000 | 0.3738 | 3.5405 |
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+ | 3.1443 | 23.0119 | 79000 | 0.3738 | 3.5448 |
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+ | 3.1687 | 23.3033 | 80000 | 0.3736 | 3.5482 |
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+ | 3.1859 | 23.5946 | 81000 | 3.5496 | 0.3738 |
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+ | 3.2137 | 23.8859 | 82000 | 3.5423 | 0.3744 |
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+ | 3.1593 | 24.1774 | 83000 | 3.5556 | 0.3734 |
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+ | 3.1826 | 24.4687 | 84000 | 3.5452 | 0.3740 |
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+ | 3.2171 | 24.7600 | 85000 | 3.5401 | 0.3741 |
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+ | 3.1104 | 25.0513 | 86000 | 3.5506 | 0.3738 |
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+ | 3.1669 | 25.3426 | 87000 | 3.5499 | 0.3738 |
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+ | 3.1768 | 25.6339 | 88000 | 3.5437 | 0.3743 |
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+ | 3.2097 | 25.9252 | 89000 | 3.5322 | 0.3750 |
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+ | 3.1445 | 26.2164 | 90000 | 3.5474 | 0.3743 |
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+ | 3.1753 | 26.5077 | 91000 | 3.5461 | 0.3744 |
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+ | 3.1956 | 26.7991 | 92000 | 3.5343 | 0.3749 |
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+ | 3.1145 | 27.0903 | 93000 | 3.5568 | 0.3739 |
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+ | 3.1459 | 27.3816 | 94000 | 3.5481 | 0.3742 |
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+ | 3.1753 | 27.6729 | 95000 | 3.5389 | 0.3751 |
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+ | 3.1863 | 27.9642 | 96000 | 3.5336 | 0.3752 |
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+ | 3.1369 | 28.2555 | 97000 | 3.5486 | 0.3743 |
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+ | 3.1615 | 28.5468 | 98000 | 3.5426 | 0.3746 |
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+ | 3.1766 | 28.8381 | 99000 | 3.5358 | 0.3752 |
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+ | 3.0968 | 29.1293 | 100000 | 3.5533 | 0.3744 |
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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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