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  1. last_to_push_frequency_40817/README.md +163 -0
  2. last_to_push_frequency_40817/all_results.json +16 -0
  3. last_to_push_frequency_40817/checkpoint-100000/config.json +31 -0
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  16. last_to_push_frequency_40817/checkpoint-100000/vocab.json +0 -0
  17. last_to_push_frequency_40817/checkpoint-40000/config.json +31 -0
  18. last_to_push_frequency_40817/checkpoint-40000/generation_config.json +6 -0
  19. last_to_push_frequency_40817/checkpoint-40000/merges.txt +0 -0
  20. last_to_push_frequency_40817/checkpoint-40000/model.safetensors +3 -0
  21. last_to_push_frequency_40817/checkpoint-40000/optimizer.pt +3 -0
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  28. last_to_push_frequency_40817/checkpoint-40000/trainer_state.json +0 -0
  29. last_to_push_frequency_40817/checkpoint-40000/training_args.bin +3 -0
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  31. last_to_push_frequency_40817/checkpoint-70000/config.json +31 -0
  32. last_to_push_frequency_40817/checkpoint-70000/generation_config.json +6 -0
  33. last_to_push_frequency_40817/checkpoint-70000/merges.txt +0 -0
  34. last_to_push_frequency_40817/checkpoint-70000/model.safetensors +3 -0
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  41. last_to_push_frequency_40817/checkpoint-70000/tokenizer_config.json +20 -0
  42. last_to_push_frequency_40817/checkpoint-70000/trainer_state.json +0 -0
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  44. last_to_push_frequency_40817/checkpoint-70000/vocab.json +0 -0
  45. last_to_push_frequency_40817/checkpoint-80000/config.json +31 -0
  46. last_to_push_frequency_40817/checkpoint-80000/generation_config.json +6 -0
  47. last_to_push_frequency_40817/checkpoint-80000/merges.txt +0 -0
  48. last_to_push_frequency_40817/checkpoint-80000/model.safetensors +3 -0
  49. last_to_push_frequency_40817/checkpoint-80000/optimizer.pt +3 -0
  50. last_to_push_frequency_40817/checkpoint-80000/rng_state.pth +3 -0
last_to_push_frequency_40817/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_push_frequency_40817
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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/7xy0f54p)
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+ # exceptions_exp2_last_to_push_frequency_40817
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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: 3.5566
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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: 40817
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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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+ | 4.8226 | 0.2912 | 1000 | 0.2548 | 4.7595 |
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+ | 4.3377 | 0.5824 | 2000 | 0.2989 | 4.2932 |
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+ | 4.1529 | 0.8737 | 3000 | 0.3155 | 4.0958 |
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+ | 3.9874 | 1.1648 | 4000 | 0.3251 | 3.9857 |
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+ | 3.918 | 1.4561 | 5000 | 0.3322 | 3.9150 |
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+ | 3.8691 | 1.7473 | 6000 | 0.3375 | 3.8541 |
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+ | 3.7395 | 2.0384 | 7000 | 0.3417 | 3.8098 |
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+ | 3.75 | 2.3297 | 8000 | 0.3447 | 3.7835 |
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+ | 3.7328 | 2.6209 | 9000 | 0.3474 | 3.7519 |
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+ | 3.7218 | 2.9121 | 10000 | 0.3499 | 3.7271 |
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+ | 3.6198 | 3.2033 | 11000 | 0.3519 | 3.7125 |
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+ | 3.6521 | 3.4945 | 12000 | 0.3538 | 3.6945 |
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+ | 3.6425 | 3.7857 | 13000 | 0.3554 | 3.6775 |
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+ | 3.5318 | 4.0769 | 14000 | 0.3566 | 3.6691 |
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+ | 3.5609 | 4.3681 | 15000 | 0.3576 | 3.6563 |
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+ | 3.5807 | 4.6593 | 16000 | 0.3586 | 3.6454 |
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+ | 3.5623 | 4.9506 | 17000 | 0.3599 | 3.6315 |
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+ | 3.4969 | 5.2417 | 18000 | 0.3605 | 3.6372 |
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+ | 3.515 | 5.5329 | 19000 | 0.3612 | 3.6257 |
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+ | 3.5407 | 5.8242 | 20000 | 0.3623 | 3.6118 |
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+ | 3.4379 | 6.1153 | 21000 | 0.3627 | 3.6162 |
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+ | 3.4808 | 6.4065 | 22000 | 0.3631 | 3.6114 |
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+ | 3.4801 | 6.6978 | 23000 | 0.3639 | 3.6001 |
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+ | 3.5032 | 6.9890 | 24000 | 0.3650 | 3.5888 |
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+ | 3.4223 | 7.2802 | 25000 | 0.3644 | 3.5988 |
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+ | 3.4484 | 7.5714 | 26000 | 0.3656 | 3.5903 |
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+ | 3.4644 | 7.8626 | 27000 | 0.3663 | 3.5784 |
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+ | 3.3616 | 8.1538 | 28000 | 0.3662 | 3.5913 |
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+ | 3.4078 | 8.4450 | 29000 | 0.3665 | 3.5818 |
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+ | 3.4191 | 8.7362 | 30000 | 0.3672 | 3.5741 |
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+ | 3.3218 | 9.0274 | 31000 | 0.3671 | 3.5782 |
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+ | 3.3814 | 9.3186 | 32000 | 0.3672 | 3.5793 |
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+ | 3.3876 | 9.6098 | 33000 | 0.3680 | 3.5690 |
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+ | 3.4114 | 9.9010 | 34000 | 0.3689 | 3.5615 |
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+ | 3.3468 | 10.1922 | 35000 | 0.3682 | 3.5728 |
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+ | 3.3582 | 10.4834 | 36000 | 0.3688 | 3.5659 |
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+ | 3.3759 | 10.7747 | 37000 | 0.3691 | 3.5594 |
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+ | 3.2953 | 11.0658 | 38000 | 0.3690 | 3.5687 |
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+ | 3.32 | 11.3570 | 39000 | 0.3697 | 3.5641 |
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+ | 3.3552 | 11.6483 | 40000 | 0.3699 | 3.5566 |
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+ | 3.3642 | 11.9395 | 41000 | 0.3705 | 3.5502 |
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+ | 3.3008 | 12.2306 | 42000 | 0.3700 | 3.5611 |
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+ | 3.3318 | 12.5219 | 43000 | 0.3704 | 3.5559 |
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+ | 3.3508 | 12.8131 | 44000 | 0.3708 | 3.5485 |
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+ | 3.2646 | 13.1043 | 45000 | 0.3705 | 3.5609 |
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+ | 3.3065 | 13.3955 | 46000 | 0.3705 | 3.5541 |
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+ | 3.333 | 13.6867 | 47000 | 0.3712 | 3.5471 |
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+ | 3.3475 | 13.9779 | 48000 | 0.3716 | 3.5394 |
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+ | 3.2779 | 14.2691 | 49000 | 0.3710 | 3.5555 |
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+ | 3.2964 | 14.5603 | 50000 | 0.3715 | 3.5499 |
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+ | 3.3015 | 14.8515 | 51000 | 0.3717 | 3.5408 |
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+ | 3.2465 | 15.1427 | 52000 | 0.3710 | 3.5548 |
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+ | 3.2841 | 15.4339 | 53000 | 0.3715 | 3.5491 |
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+ | 3.2881 | 15.7251 | 54000 | 0.3720 | 3.5432 |
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+ | 3.1978 | 16.0163 | 55000 | 0.3723 | 3.5493 |
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+ | 3.259 | 16.3075 | 56000 | 0.3721 | 3.5498 |
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+ | 3.2834 | 16.5988 | 57000 | 0.3722 | 3.5432 |
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+ | 3.2864 | 16.8900 | 58000 | 0.3729 | 3.5378 |
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+ | 3.2375 | 17.1811 | 59000 | 0.3720 | 3.5509 |
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+ | 3.2556 | 17.4724 | 60000 | 0.3723 | 3.5462 |
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+ | 3.2668 | 17.7636 | 61000 | 0.3731 | 3.5369 |
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+ | 3.1791 | 18.0547 | 62000 | 0.3726 | 3.5498 |
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+ | 3.2225 | 18.3460 | 63000 | 0.3729 | 3.5450 |
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+ | 3.2548 | 18.6372 | 64000 | 0.3733 | 3.5395 |
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+ | 3.2761 | 18.9284 | 65000 | 0.3737 | 3.5303 |
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+ | 3.1968 | 19.2196 | 66000 | 0.3729 | 3.5495 |
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+ | 3.2385 | 19.5108 | 67000 | 0.3734 | 3.5390 |
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+ | 3.2498 | 19.8020 | 68000 | 0.3739 | 3.5317 |
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+ | 3.1671 | 20.0932 | 69000 | 0.3730 | 3.5486 |
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+ | 3.221 | 20.3844 | 70000 | 0.3734 | 3.5450 |
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+ | 3.2279 | 20.6756 | 71000 | 0.3738 | 3.5397 |
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+ | 3.2567 | 20.9669 | 72000 | 0.3744 | 3.5256 |
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+ | 3.1976 | 21.2580 | 73000 | 0.3736 | 3.5462 |
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+ | 3.2191 | 21.5492 | 74000 | 0.3737 | 3.5422 |
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+ | 3.237 | 21.8405 | 75000 | 0.3742 | 3.5333 |
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+ | 3.1506 | 22.1316 | 76000 | 0.3734 | 3.5470 |
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+ | 3.2 | 22.4229 | 77000 | 0.3737 | 3.5437 |
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+ | 3.2196 | 22.7141 | 78000 | 0.3744 | 3.5352 |
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+ | 3.1812 | 23.0052 | 79000 | 0.3737 | 3.5444 |
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+ | 3.1755 | 23.2965 | 80000 | 0.3743 | 3.5429 |
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+ | 3.1678 | 23.5877 | 81000 | 3.5462 | 0.3735 |
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+ | 3.1976 | 23.8789 | 82000 | 3.5400 | 0.3741 |
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+ | 3.1531 | 24.1704 | 83000 | 3.5527 | 0.3736 |
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+ | 3.1952 | 24.4616 | 84000 | 3.5442 | 0.3741 |
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+ | 3.1897 | 24.7528 | 85000 | 3.5352 | 0.3748 |
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+ | 3.1156 | 25.0440 | 86000 | 3.5469 | 0.3742 |
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+ | 3.1616 | 25.3352 | 87000 | 3.5476 | 0.3742 |
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+ | 3.1868 | 25.6264 | 88000 | 3.5388 | 0.3746 |
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+ | 3.1926 | 25.9176 | 89000 | 3.5338 | 0.3751 |
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+ | 3.14 | 26.2088 | 90000 | 3.5470 | 0.3746 |
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+ | 3.1625 | 26.5000 | 91000 | 3.5408 | 0.3748 |
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+ | 3.1847 | 26.7913 | 92000 | 3.5317 | 0.3751 |
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+ | 3.1093 | 27.0824 | 93000 | 3.5485 | 0.3745 |
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+ | 3.1523 | 27.3736 | 94000 | 3.5423 | 0.3747 |
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+ | 3.1734 | 27.6649 | 95000 | 3.5385 | 0.3748 |
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+ | 3.1821 | 27.9561 | 96000 | 3.5296 | 0.3756 |
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+ | 3.1248 | 28.2472 | 97000 | 3.5502 | 0.3746 |
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+ | 3.1562 | 28.5385 | 98000 | 3.5430 | 0.3749 |
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+ | 3.1632 | 28.8297 | 99000 | 3.5369 | 0.3753 |
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+ | 3.0985 | 29.1209 | 100000 | 3.5492 | 0.3746 |
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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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