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  1. cost_to_push_frequency_5039/README.md +172 -0
  2. cost_to_push_frequency_5039/all_results.json +16 -0
  3. cost_to_push_frequency_5039/checkpoint-100000/config.json +31 -0
  4. cost_to_push_frequency_5039/checkpoint-100000/generation_config.json +6 -0
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  9. cost_to_push_frequency_5039/checkpoint-100000/scaler.pt +3 -0
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  14. cost_to_push_frequency_5039/checkpoint-100000/trainer_state.json +0 -0
  15. cost_to_push_frequency_5039/checkpoint-100000/training_args.bin +3 -0
  16. cost_to_push_frequency_5039/checkpoint-100000/vocab.json +0 -0
  17. cost_to_push_frequency_5039/checkpoint-30000/config.json +31 -0
  18. cost_to_push_frequency_5039/checkpoint-30000/generation_config.json +6 -0
  19. cost_to_push_frequency_5039/checkpoint-30000/merges.txt +0 -0
  20. cost_to_push_frequency_5039/checkpoint-30000/model.safetensors +3 -0
  21. cost_to_push_frequency_5039/checkpoint-30000/optimizer.pt +3 -0
  22. cost_to_push_frequency_5039/checkpoint-30000/rng_state.pth +3 -0
  23. cost_to_push_frequency_5039/checkpoint-30000/scaler.pt +3 -0
  24. cost_to_push_frequency_5039/checkpoint-30000/scheduler.pt +3 -0
  25. cost_to_push_frequency_5039/checkpoint-30000/special_tokens_map.json +5 -0
  26. cost_to_push_frequency_5039/checkpoint-30000/tokenizer.json +0 -0
  27. cost_to_push_frequency_5039/checkpoint-30000/tokenizer_config.json +20 -0
  28. cost_to_push_frequency_5039/checkpoint-30000/trainer_state.json +0 -0
  29. cost_to_push_frequency_5039/checkpoint-30000/training_args.bin +3 -0
  30. cost_to_push_frequency_5039/checkpoint-30000/vocab.json +0 -0
  31. cost_to_push_frequency_5039/checkpoint-70000/config.json +31 -0
  32. cost_to_push_frequency_5039/checkpoint-70000/generation_config.json +6 -0
  33. cost_to_push_frequency_5039/checkpoint-70000/merges.txt +0 -0
  34. cost_to_push_frequency_5039/checkpoint-70000/model.safetensors +3 -0
  35. cost_to_push_frequency_5039/checkpoint-70000/optimizer.pt +3 -0
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  37. cost_to_push_frequency_5039/checkpoint-70000/scaler.pt +3 -0
  38. cost_to_push_frequency_5039/checkpoint-70000/scheduler.pt +3 -0
  39. cost_to_push_frequency_5039/checkpoint-70000/special_tokens_map.json +5 -0
  40. cost_to_push_frequency_5039/checkpoint-70000/tokenizer.json +0 -0
  41. cost_to_push_frequency_5039/checkpoint-70000/tokenizer_config.json +20 -0
  42. cost_to_push_frequency_5039/checkpoint-70000/trainer_state.json +0 -0
  43. cost_to_push_frequency_5039/checkpoint-70000/training_args.bin +3 -0
  44. cost_to_push_frequency_5039/checkpoint-70000/vocab.json +0 -0
  45. cost_to_push_frequency_5039/checkpoint-80000/config.json +31 -0
  46. cost_to_push_frequency_5039/checkpoint-80000/generation_config.json +6 -0
  47. cost_to_push_frequency_5039/checkpoint-80000/merges.txt +0 -0
  48. cost_to_push_frequency_5039/checkpoint-80000/model.safetensors +3 -0
  49. cost_to_push_frequency_5039/checkpoint-80000/optimizer.pt +3 -0
  50. cost_to_push_frequency_5039/checkpoint-80000/rng_state.pth +3 -0
cost_to_push_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_push_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/4uqbszjn)
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+ # exceptions_exp2_cost_to_push_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: 3.5735
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+ - Accuracy: 0.3672
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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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+ | 4.8278 | 0.2912 | 1000 | 0.2568 | 4.7395 |
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+ | 4.3264 | 0.5824 | 2000 | 0.3001 | 4.2771 |
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+ | 4.1401 | 0.8737 | 3000 | 0.3152 | 4.0969 |
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+ | 3.9957 | 1.1648 | 4000 | 0.3252 | 3.9897 |
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+ | 3.9142 | 1.4561 | 5000 | 0.3318 | 3.9158 |
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+ | 3.8871 | 1.7473 | 6000 | 0.3367 | 3.8573 |
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+ | 3.7577 | 2.0384 | 7000 | 0.3412 | 3.8156 |
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+ | 3.754 | 2.3297 | 8000 | 0.3443 | 3.7844 |
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+ | 3.7424 | 2.6209 | 9000 | 0.3470 | 3.7540 |
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+ | 3.7116 | 2.9121 | 10000 | 0.3494 | 3.7274 |
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+ | 3.6438 | 3.2033 | 11000 | 0.3516 | 3.7147 |
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+ | 3.6323 | 3.4945 | 12000 | 0.3530 | 3.6957 |
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+ | 3.6429 | 3.7857 | 13000 | 0.3549 | 3.6801 |
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+ | 3.5448 | 4.0769 | 14000 | 0.3564 | 3.6697 |
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+ | 3.5583 | 4.3681 | 15000 | 0.3572 | 3.6608 |
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+ | 3.5833 | 4.6593 | 16000 | 0.3584 | 3.6470 |
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+ | 3.5773 | 4.9506 | 17000 | 0.3596 | 3.6331 |
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+ | 3.4997 | 5.2417 | 18000 | 0.3596 | 3.6378 |
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+ | 3.5261 | 5.5329 | 19000 | 0.3609 | 3.6254 |
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+ | 3.5262 | 5.8242 | 20000 | 0.3623 | 3.6148 |
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+ | 3.4388 | 6.1153 | 21000 | 0.3627 | 3.6167 |
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+ | 3.4634 | 6.4065 | 22000 | 0.3631 | 3.6098 |
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+ | 3.5019 | 6.6978 | 23000 | 0.3638 | 3.6009 |
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+ | 3.4874 | 6.9890 | 24000 | 0.3646 | 3.5911 |
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+ | 3.4222 | 7.2802 | 25000 | 0.3646 | 3.5986 |
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+ | 3.4584 | 7.5714 | 26000 | 0.3650 | 3.5894 |
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+ | 3.4485 | 7.8626 | 27000 | 0.3659 | 3.5809 |
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+ | 3.3673 | 8.1538 | 28000 | 0.3658 | 3.5875 |
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+ | 3.4158 | 8.4450 | 29000 | 0.3664 | 3.5817 |
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+ | 3.4307 | 8.7362 | 30000 | 0.3672 | 3.5735 |
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+ | 3.3191 | 9.0274 | 31000 | 0.3673 | 3.5792 |
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+ | 3.3673 | 9.3186 | 32000 | 0.3674 | 3.5772 |
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+ | 3.4042 | 9.6098 | 33000 | 0.3681 | 3.5702 |
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+ | 3.4059 | 9.9010 | 34000 | 0.3685 | 3.5634 |
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+ | 3.3375 | 10.1922 | 35000 | 0.3681 | 3.5722 |
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+ | 3.3636 | 10.4834 | 36000 | 0.3686 | 3.5675 |
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+ | 3.3783 | 10.7747 | 37000 | 0.3690 | 3.5586 |
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+ | 3.2792 | 11.0658 | 38000 | 0.3686 | 3.5728 |
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+ | 3.3318 | 11.3570 | 39000 | 0.3697 | 3.5641 |
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+ | 3.3586 | 11.6483 | 40000 | 0.3697 | 3.5586 |
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+ | 3.355 | 11.9395 | 41000 | 0.3705 | 3.5511 |
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+ | 3.3012 | 12.2306 | 42000 | 0.3702 | 3.5619 |
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+ | 3.3375 | 12.5219 | 43000 | 0.3701 | 3.5573 |
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+ | 3.3423 | 12.8131 | 44000 | 0.3708 | 3.5473 |
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+ | 3.258 | 13.1043 | 45000 | 0.3704 | 3.5602 |
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+ | 3.2948 | 13.3955 | 46000 | 0.3708 | 3.5569 |
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+ | 3.3168 | 13.6867 | 47000 | 0.3710 | 3.5502 |
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+ | 3.3278 | 13.9779 | 48000 | 0.3715 | 3.5404 |
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+ | 3.2799 | 14.2691 | 49000 | 0.3709 | 3.5580 |
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+ | 3.305 | 14.5603 | 50000 | 0.3713 | 3.5497 |
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+ | 3.3274 | 14.8515 | 51000 | 0.3719 | 3.5401 |
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+ | 3.2323 | 15.1427 | 52000 | 0.3711 | 3.5575 |
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+ | 3.2795 | 15.4339 | 53000 | 0.3716 | 3.5513 |
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+ | 3.3018 | 15.7251 | 54000 | 0.3722 | 3.5419 |
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+ | 3.2195 | 16.0163 | 55000 | 0.3716 | 3.5543 |
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+ | 3.253 | 16.3075 | 56000 | 0.3717 | 3.5524 |
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+ | 3.2781 | 16.5988 | 57000 | 0.3723 | 3.5433 |
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+ | 3.2999 | 16.8900 | 58000 | 0.3728 | 3.5354 |
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+ | 3.2191 | 17.1811 | 59000 | 0.3717 | 3.5553 |
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+ | 3.2596 | 17.4724 | 60000 | 0.3723 | 3.5483 |
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+ | 3.2635 | 17.7636 | 61000 | 0.3731 | 3.5364 |
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+ | 3.1872 | 18.0547 | 62000 | 0.3727 | 3.5483 |
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+ | 3.2398 | 18.3460 | 63000 | 0.3726 | 3.5478 |
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+ | 3.2587 | 18.6372 | 64000 | 0.3732 | 3.5419 |
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+ | 3.2748 | 18.9284 | 65000 | 0.3734 | 3.5315 |
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+ | 3.1828 | 19.2196 | 66000 | 0.3727 | 3.5500 |
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+ | 3.2364 | 19.5108 | 67000 | 0.3732 | 3.5449 |
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+ | 3.271 | 19.8020 | 68000 | 0.3734 | 3.5359 |
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+ | 3.1782 | 20.0932 | 69000 | 0.3731 | 3.5494 |
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+ | 3.227 | 20.3844 | 70000 | 0.3730 | 3.5466 |
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+ | 3.243 | 20.6756 | 71000 | 0.3735 | 3.5373 |
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+ | 3.2558 | 20.9669 | 72000 | 0.3740 | 3.5292 |
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+ | 3.2002 | 21.2580 | 73000 | 0.3731 | 3.5506 |
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+ | 3.2176 | 21.5492 | 74000 | 0.3737 | 3.5432 |
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+ | 3.2304 | 21.8405 | 75000 | 0.3741 | 3.5328 |
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+ | 3.1667 | 22.1316 | 76000 | 0.3735 | 3.5492 |
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+ | 3.1947 | 22.4229 | 77000 | 0.3737 | 3.5422 |
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+ | 3.2262 | 22.7141 | 78000 | 0.3738 | 3.5383 |
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+ | 3.1953 | 23.0052 | 79000 | 0.3738 | 3.5464 |
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+ | 3.1894 | 23.2965 | 80000 | 0.3738 | 3.5445 |
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+ | 3.1864 | 23.5877 | 81000 | 3.5497 | 0.3734 |
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+ | 3.2009 | 23.8789 | 82000 | 3.5438 | 0.3739 |
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+ | 3.1553 | 24.1704 | 83000 | 3.5531 | 0.3734 |
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+ | 3.1842 | 24.4616 | 84000 | 3.5492 | 0.3738 |
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+ | 3.2134 | 24.7528 | 85000 | 3.5347 | 0.3743 |
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+ | 3.1239 | 25.0440 | 86000 | 3.5490 | 0.3737 |
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+ | 3.1617 | 25.3352 | 87000 | 3.5456 | 0.3741 |
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+ | 3.1904 | 25.6264 | 88000 | 3.5372 | 0.3746 |
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+ | 3.1968 | 25.9176 | 89000 | 3.5289 | 0.3752 |
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+ | 3.1467 | 26.2088 | 90000 | 3.5531 | 0.3738 |
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+ | 3.1696 | 26.5000 | 91000 | 3.5432 | 0.3745 |
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+ | 3.1874 | 26.7913 | 92000 | 3.5348 | 0.3750 |
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+ | 3.1152 | 27.0824 | 93000 | 3.5507 | 0.3740 |
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+ | 3.1483 | 27.3736 | 94000 | 3.5439 | 0.3743 |
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+ | 3.1667 | 27.6649 | 95000 | 3.5362 | 0.3750 |
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+ | 3.1915 | 27.9561 | 96000 | 3.5300 | 0.3752 |
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+ | 3.1298 | 28.2472 | 97000 | 3.5514 | 0.3740 |
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+ | 3.1652 | 28.5385 | 98000 | 3.5401 | 0.3749 |
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+ | 3.169 | 28.8297 | 99000 | 3.5337 | 0.3752 |
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+ | 3.1089 | 29.1209 | 100000 | 3.5571 | 0.3743 |
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+ | 3.1378 | 29.4121 | 101000 | 3.5446 | 0.3746 |
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+ | 3.1503 | 29.7033 | 102000 | 3.5406 | 0.3751 |
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+ | 3.1713 | 29.9945 | 103000 | 3.5308 | 0.3755 |
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+ | 3.1197 | 30.2857 | 104000 | 3.5519 | 0.3744 |
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+ | 3.1251 | 30.5769 | 105000 | 3.5411 | 0.3755 |
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+ | 3.1654 | 30.8681 | 106000 | 3.5359 | 0.3755 |
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+ | 3.1073 | 31.1593 | 107000 | 3.5528 | 0.3747 |
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+ | 3.1266 | 31.4505 | 108000 | 3.5441 | 0.3749 |
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+ | 3.1428 | 31.7417 | 109000 | 3.5388 | 0.3755 |
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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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