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  1. cost_to_carry_frequency_2128/README.md +163 -0
  2. cost_to_carry_frequency_2128/all_results.json +16 -0
  3. cost_to_carry_frequency_2128/checkpoint-100000/config.json +31 -0
  4. cost_to_carry_frequency_2128/checkpoint-100000/generation_config.json +6 -0
  5. cost_to_carry_frequency_2128/checkpoint-100000/merges.txt +0 -0
  6. cost_to_carry_frequency_2128/checkpoint-100000/model.safetensors +3 -0
  7. cost_to_carry_frequency_2128/checkpoint-100000/optimizer.pt +3 -0
  8. cost_to_carry_frequency_2128/checkpoint-100000/rng_state.pth +3 -0
  9. cost_to_carry_frequency_2128/checkpoint-100000/scaler.pt +3 -0
  10. cost_to_carry_frequency_2128/checkpoint-100000/scheduler.pt +3 -0
  11. cost_to_carry_frequency_2128/checkpoint-100000/special_tokens_map.json +5 -0
  12. cost_to_carry_frequency_2128/checkpoint-100000/tokenizer.json +0 -0
  13. cost_to_carry_frequency_2128/checkpoint-100000/tokenizer_config.json +20 -0
  14. cost_to_carry_frequency_2128/checkpoint-100000/trainer_state.json +0 -0
  15. cost_to_carry_frequency_2128/checkpoint-100000/training_args.bin +3 -0
  16. cost_to_carry_frequency_2128/checkpoint-100000/vocab.json +0 -0
  17. cost_to_carry_frequency_2128/checkpoint-40000/config.json +31 -0
  18. cost_to_carry_frequency_2128/checkpoint-40000/generation_config.json +6 -0
  19. cost_to_carry_frequency_2128/checkpoint-40000/merges.txt +0 -0
  20. cost_to_carry_frequency_2128/checkpoint-40000/model.safetensors +3 -0
  21. cost_to_carry_frequency_2128/checkpoint-40000/optimizer.pt +3 -0
  22. cost_to_carry_frequency_2128/checkpoint-40000/rng_state.pth +3 -0
  23. cost_to_carry_frequency_2128/checkpoint-40000/scaler.pt +3 -0
  24. cost_to_carry_frequency_2128/checkpoint-40000/scheduler.pt +3 -0
  25. cost_to_carry_frequency_2128/checkpoint-40000/special_tokens_map.json +5 -0
  26. cost_to_carry_frequency_2128/checkpoint-40000/tokenizer.json +0 -0
  27. cost_to_carry_frequency_2128/checkpoint-40000/tokenizer_config.json +20 -0
  28. cost_to_carry_frequency_2128/checkpoint-40000/trainer_state.json +0 -0
  29. cost_to_carry_frequency_2128/checkpoint-40000/training_args.bin +3 -0
  30. cost_to_carry_frequency_2128/checkpoint-40000/vocab.json +0 -0
  31. cost_to_carry_frequency_2128/checkpoint-70000/config.json +31 -0
  32. cost_to_carry_frequency_2128/checkpoint-70000/generation_config.json +6 -0
  33. cost_to_carry_frequency_2128/checkpoint-70000/merges.txt +0 -0
  34. cost_to_carry_frequency_2128/checkpoint-70000/model.safetensors +3 -0
  35. cost_to_carry_frequency_2128/checkpoint-70000/optimizer.pt +3 -0
  36. cost_to_carry_frequency_2128/checkpoint-70000/rng_state.pth +3 -0
  37. cost_to_carry_frequency_2128/checkpoint-70000/scaler.pt +3 -0
  38. cost_to_carry_frequency_2128/checkpoint-70000/scheduler.pt +3 -0
  39. cost_to_carry_frequency_2128/checkpoint-70000/special_tokens_map.json +5 -0
  40. cost_to_carry_frequency_2128/checkpoint-70000/tokenizer.json +0 -0
  41. cost_to_carry_frequency_2128/checkpoint-70000/tokenizer_config.json +20 -0
  42. cost_to_carry_frequency_2128/checkpoint-70000/trainer_state.json +0 -0
  43. cost_to_carry_frequency_2128/checkpoint-70000/training_args.bin +3 -0
  44. cost_to_carry_frequency_2128/checkpoint-70000/vocab.json +0 -0
  45. cost_to_carry_frequency_2128/checkpoint-80000/config.json +31 -0
  46. cost_to_carry_frequency_2128/checkpoint-80000/generation_config.json +6 -0
  47. cost_to_carry_frequency_2128/checkpoint-80000/merges.txt +0 -0
  48. cost_to_carry_frequency_2128/checkpoint-80000/model.safetensors +3 -0
  49. cost_to_carry_frequency_2128/checkpoint-80000/optimizer.pt +3 -0
  50. cost_to_carry_frequency_2128/checkpoint-80000/rng_state.pth +3 -0
cost_to_carry_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_cost_to_carry_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/9p6igllz)
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+ # exceptions_exp2_cost_to_carry_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: 3.5569
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+ - Accuracy: 0.3700
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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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+ | 4.8034 | 0.2913 | 1000 | 0.2554 | 4.7472 |
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+ | 4.3307 | 0.5826 | 2000 | 0.3005 | 4.2749 |
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+ | 4.133 | 0.8739 | 3000 | 0.3159 | 4.0936 |
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+ | 3.9994 | 1.1652 | 4000 | 0.3255 | 3.9870 |
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+ | 3.9189 | 1.4565 | 5000 | 0.3319 | 3.9137 |
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+ | 3.873 | 1.7478 | 6000 | 0.3377 | 3.8517 |
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+ | 3.7513 | 2.0390 | 7000 | 0.3415 | 3.8102 |
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+ | 3.7592 | 2.3303 | 8000 | 0.3450 | 3.7795 |
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+ | 3.7318 | 2.6216 | 9000 | 0.3474 | 3.7511 |
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+ | 3.7092 | 2.9130 | 10000 | 0.3502 | 3.7233 |
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+ | 3.6303 | 3.2042 | 11000 | 0.3518 | 3.7111 |
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+ | 3.634 | 3.4955 | 12000 | 0.3532 | 3.6934 |
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+ | 3.6417 | 3.7868 | 13000 | 0.3552 | 3.6750 |
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+ | 3.5387 | 4.0781 | 14000 | 0.3563 | 3.6710 |
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+ | 3.5645 | 4.3694 | 15000 | 0.3571 | 3.6592 |
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+ | 3.5712 | 4.6607 | 16000 | 0.3587 | 3.6471 |
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+ | 3.5678 | 4.9520 | 17000 | 0.3600 | 3.6317 |
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+ | 3.5042 | 5.2432 | 18000 | 0.3604 | 3.6396 |
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+ | 3.5238 | 5.5345 | 19000 | 0.3613 | 3.6238 |
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+ | 3.5195 | 5.8259 | 20000 | 0.3622 | 3.6152 |
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+ | 3.4431 | 6.1171 | 21000 | 0.3624 | 3.6179 |
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+ | 3.4638 | 6.4084 | 22000 | 0.3632 | 3.6109 |
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+ | 3.505 | 6.6997 | 23000 | 0.3639 | 3.6010 |
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+ | 3.4849 | 6.9910 | 24000 | 0.3649 | 3.5899 |
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+ | 3.4216 | 7.2823 | 25000 | 0.3647 | 3.5989 |
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+ | 3.4423 | 7.5736 | 26000 | 0.3656 | 3.5896 |
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+ | 3.4548 | 7.8649 | 27000 | 0.3662 | 3.5811 |
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+ | 3.3804 | 8.1561 | 28000 | 0.3658 | 3.5930 |
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+ | 3.4071 | 8.4474 | 29000 | 0.3665 | 3.5825 |
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+ | 3.4312 | 8.7388 | 30000 | 0.3673 | 3.5726 |
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+ | 3.3276 | 9.0300 | 31000 | 0.3677 | 3.5778 |
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+ | 3.3689 | 9.3213 | 32000 | 0.3675 | 3.5782 |
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+ | 3.3928 | 9.6126 | 33000 | 0.3680 | 3.5680 |
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+ | 3.4054 | 9.9039 | 34000 | 0.3687 | 3.5603 |
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+ | 3.3389 | 10.1952 | 35000 | 0.3685 | 3.5742 |
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+ | 3.3566 | 10.4865 | 36000 | 0.3686 | 3.5662 |
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+ | 3.3865 | 10.7778 | 37000 | 0.3694 | 3.5583 |
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+ | 3.3071 | 11.0690 | 38000 | 0.3690 | 3.5702 |
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+ | 3.3269 | 11.3603 | 39000 | 0.3692 | 3.5654 |
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+ | 3.3528 | 11.6517 | 40000 | 0.3701 | 3.5569 |
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+ | 3.372 | 11.9430 | 41000 | 0.3706 | 3.5482 |
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+ | 3.3063 | 12.2342 | 42000 | 0.3700 | 3.5630 |
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+ | 3.3309 | 12.5255 | 43000 | 0.3704 | 3.5568 |
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+ | 3.3442 | 12.8168 | 44000 | 0.3710 | 3.5484 |
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+ | 3.2636 | 13.1081 | 45000 | 0.3702 | 3.5620 |
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+ | 3.3113 | 13.3994 | 46000 | 0.3708 | 3.5552 |
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+ | 3.3403 | 13.6907 | 47000 | 0.3712 | 3.5487 |
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+ | 3.3308 | 13.9820 | 48000 | 0.3717 | 3.5424 |
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+ | 3.2723 | 14.2732 | 49000 | 0.3712 | 3.5563 |
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+ | 3.3099 | 14.5646 | 50000 | 0.3718 | 3.5470 |
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+ | 3.3159 | 14.8559 | 51000 | 0.3722 | 3.5394 |
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+ | 3.2313 | 15.1471 | 52000 | 0.3712 | 3.5569 |
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+ | 3.2791 | 15.4384 | 53000 | 0.3719 | 3.5488 |
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+ | 3.2936 | 15.7297 | 54000 | 0.3723 | 3.5409 |
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+ | 3.1967 | 16.0210 | 55000 | 0.3717 | 3.5522 |
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+ | 3.2523 | 16.3123 | 56000 | 0.3723 | 3.5495 |
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+ | 3.2784 | 16.6036 | 57000 | 0.3726 | 3.5425 |
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+ | 3.2943 | 16.8949 | 58000 | 0.3732 | 3.5336 |
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+ | 3.2154 | 17.1861 | 59000 | 0.3722 | 3.5533 |
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+ | 3.2344 | 17.4775 | 60000 | 0.3725 | 3.5473 |
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+ | 3.2703 | 17.7688 | 61000 | 0.3730 | 3.5380 |
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+ | 3.1844 | 18.0600 | 62000 | 0.3725 | 3.5507 |
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+ | 3.2328 | 18.3513 | 63000 | 0.3725 | 3.5483 |
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+ | 3.2432 | 18.6426 | 64000 | 0.3730 | 3.5404 |
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+ | 3.2529 | 18.9339 | 65000 | 0.3737 | 3.5312 |
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+ | 3.2102 | 19.2252 | 66000 | 0.3729 | 3.5524 |
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+ | 3.2376 | 19.5165 | 67000 | 0.3736 | 3.5410 |
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+ | 3.2518 | 19.8078 | 68000 | 0.3737 | 3.5361 |
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+ | 3.1679 | 20.0990 | 69000 | 0.3726 | 3.5535 |
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+ | 3.2017 | 20.3904 | 70000 | 0.3733 | 3.5443 |
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+ | 3.2243 | 20.6817 | 71000 | 0.3738 | 3.5388 |
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+ | 3.2591 | 20.9730 | 72000 | 0.3740 | 3.5341 |
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+ | 3.1907 | 21.2642 | 73000 | 0.3732 | 3.5509 |
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+ | 3.2165 | 21.5555 | 74000 | 0.3737 | 3.5430 |
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+ | 3.2326 | 21.8468 | 75000 | 0.3741 | 3.5349 |
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+ | 3.1574 | 22.1381 | 76000 | 0.3735 | 3.5511 |
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+ | 3.1852 | 22.4294 | 77000 | 0.3735 | 3.5454 |
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+ | 3.2004 | 22.7207 | 78000 | 0.3743 | 3.5348 |
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+ | 3.142 | 23.0119 | 79000 | 0.3739 | 3.5474 |
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+ | 3.1732 | 23.3033 | 80000 | 0.3733 | 3.5511 |
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+ | 3.1819 | 23.5946 | 81000 | 3.5574 | 0.3728 |
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+ | 3.1931 | 23.8859 | 82000 | 3.5438 | 0.3739 |
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+ | 3.1453 | 24.1774 | 83000 | 3.5560 | 0.3733 |
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+ | 3.1766 | 24.4687 | 84000 | 3.5511 | 0.3737 |
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+ | 3.2054 | 24.7600 | 85000 | 3.5386 | 0.3744 |
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+ | 3.1193 | 25.0513 | 86000 | 3.5483 | 0.3739 |
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+ | 3.1554 | 25.3426 | 87000 | 3.5489 | 0.3738 |
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+ | 3.1892 | 25.6339 | 88000 | 3.5394 | 0.3743 |
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+ | 3.1922 | 25.9252 | 89000 | 3.5372 | 0.3749 |
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+ | 3.1368 | 26.2164 | 90000 | 3.5518 | 0.3741 |
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+ | 3.1591 | 26.5077 | 91000 | 3.5447 | 0.3746 |
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+ | 3.1906 | 26.7991 | 92000 | 3.5366 | 0.3749 |
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+ | 3.1112 | 27.0903 | 93000 | 3.5538 | 0.3743 |
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+ | 3.1361 | 27.3816 | 94000 | 3.5490 | 0.3744 |
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+ | 3.1604 | 27.6729 | 95000 | 3.5376 | 0.3749 |
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+ | 3.1888 | 27.9642 | 96000 | 3.5316 | 0.3753 |
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+ | 3.1254 | 28.2555 | 97000 | 3.5546 | 0.3744 |
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+ | 3.138 | 28.5468 | 98000 | 3.5463 | 0.3746 |
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+ | 3.1704 | 28.8381 | 99000 | 3.5396 | 0.3751 |
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+ | 3.1003 | 29.1293 | 100000 | 3.5567 | 0.3740 |
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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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