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  1. resemble_to_hit_frequency_1001/README.md +172 -0
  2. resemble_to_hit_frequency_1001/all_results.json +16 -0
  3. resemble_to_hit_frequency_1001/checkpoint-100000/config.json +31 -0
  4. resemble_to_hit_frequency_1001/checkpoint-100000/generation_config.json +6 -0
  5. resemble_to_hit_frequency_1001/checkpoint-100000/merges.txt +0 -0
  6. resemble_to_hit_frequency_1001/checkpoint-100000/model.safetensors +3 -0
  7. resemble_to_hit_frequency_1001/checkpoint-100000/optimizer.pt +3 -0
  8. resemble_to_hit_frequency_1001/checkpoint-100000/rng_state.pth +3 -0
  9. resemble_to_hit_frequency_1001/checkpoint-100000/scaler.pt +3 -0
  10. resemble_to_hit_frequency_1001/checkpoint-100000/scheduler.pt +3 -0
  11. resemble_to_hit_frequency_1001/checkpoint-100000/special_tokens_map.json +5 -0
  12. resemble_to_hit_frequency_1001/checkpoint-100000/tokenizer.json +0 -0
  13. resemble_to_hit_frequency_1001/checkpoint-100000/tokenizer_config.json +20 -0
  14. resemble_to_hit_frequency_1001/checkpoint-100000/trainer_state.json +0 -0
  15. resemble_to_hit_frequency_1001/checkpoint-100000/training_args.bin +3 -0
  16. resemble_to_hit_frequency_1001/checkpoint-100000/vocab.json +0 -0
  17. resemble_to_hit_frequency_1001/checkpoint-40000/config.json +31 -0
  18. resemble_to_hit_frequency_1001/checkpoint-40000/generation_config.json +6 -0
  19. resemble_to_hit_frequency_1001/checkpoint-40000/merges.txt +0 -0
  20. resemble_to_hit_frequency_1001/checkpoint-40000/model.safetensors +3 -0
  21. resemble_to_hit_frequency_1001/checkpoint-40000/optimizer.pt +3 -0
  22. resemble_to_hit_frequency_1001/checkpoint-40000/rng_state.pth +3 -0
  23. resemble_to_hit_frequency_1001/checkpoint-40000/scaler.pt +3 -0
  24. resemble_to_hit_frequency_1001/checkpoint-40000/scheduler.pt +3 -0
  25. resemble_to_hit_frequency_1001/checkpoint-40000/special_tokens_map.json +5 -0
  26. resemble_to_hit_frequency_1001/checkpoint-40000/tokenizer.json +0 -0
  27. resemble_to_hit_frequency_1001/checkpoint-40000/tokenizer_config.json +20 -0
  28. resemble_to_hit_frequency_1001/checkpoint-40000/trainer_state.json +0 -0
  29. resemble_to_hit_frequency_1001/checkpoint-40000/training_args.bin +3 -0
  30. resemble_to_hit_frequency_1001/checkpoint-40000/vocab.json +0 -0
  31. resemble_to_hit_frequency_1001/checkpoint-70000/config.json +31 -0
  32. resemble_to_hit_frequency_1001/checkpoint-70000/generation_config.json +6 -0
  33. resemble_to_hit_frequency_1001/checkpoint-70000/merges.txt +0 -0
  34. resemble_to_hit_frequency_1001/checkpoint-70000/model.safetensors +3 -0
  35. resemble_to_hit_frequency_1001/checkpoint-70000/optimizer.pt +3 -0
  36. resemble_to_hit_frequency_1001/checkpoint-70000/rng_state.pth +3 -0
  37. resemble_to_hit_frequency_1001/checkpoint-70000/scaler.pt +3 -0
  38. resemble_to_hit_frequency_1001/checkpoint-70000/scheduler.pt +3 -0
  39. resemble_to_hit_frequency_1001/checkpoint-70000/special_tokens_map.json +5 -0
  40. resemble_to_hit_frequency_1001/checkpoint-70000/tokenizer.json +0 -0
  41. resemble_to_hit_frequency_1001/checkpoint-70000/tokenizer_config.json +20 -0
  42. resemble_to_hit_frequency_1001/checkpoint-70000/trainer_state.json +0 -0
  43. resemble_to_hit_frequency_1001/checkpoint-70000/training_args.bin +3 -0
  44. resemble_to_hit_frequency_1001/checkpoint-70000/vocab.json +0 -0
  45. resemble_to_hit_frequency_1001/checkpoint-80000/config.json +31 -0
  46. resemble_to_hit_frequency_1001/checkpoint-80000/generation_config.json +6 -0
  47. resemble_to_hit_frequency_1001/checkpoint-80000/merges.txt +0 -0
  48. resemble_to_hit_frequency_1001/checkpoint-80000/model.safetensors +3 -0
  49. resemble_to_hit_frequency_1001/checkpoint-80000/optimizer.pt +3 -0
  50. resemble_to_hit_frequency_1001/checkpoint-80000/rng_state.pth +3 -0
resemble_to_hit_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_resemble_to_hit_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/jcuxvn5d)
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+ # exceptions_exp2_resemble_to_hit_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: 3.5557
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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: 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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+ | 4.8439 | 0.2914 | 1000 | 0.2509 | 4.7752 |
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+ | 4.329 | 0.5828 | 2000 | 0.3000 | 4.2779 |
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+ | 4.1511 | 0.8741 | 3000 | 0.3167 | 4.0918 |
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+ | 3.9927 | 1.1655 | 4000 | 0.3258 | 3.9809 |
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+ | 3.9166 | 1.4569 | 5000 | 0.3327 | 3.9076 |
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+ | 3.8693 | 1.7483 | 6000 | 0.3379 | 3.8500 |
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+ | 3.7327 | 2.0396 | 7000 | 0.3422 | 3.8088 |
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+ | 3.7487 | 2.3310 | 8000 | 0.3450 | 3.7771 |
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+ | 3.7285 | 2.6224 | 9000 | 0.3478 | 3.7496 |
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+ | 3.7212 | 2.9138 | 10000 | 0.3504 | 3.7192 |
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+ | 3.6257 | 3.2051 | 11000 | 0.3525 | 3.7095 |
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+ | 3.6324 | 3.4965 | 12000 | 0.3538 | 3.6917 |
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+ | 3.6403 | 3.7879 | 13000 | 0.3554 | 3.6738 |
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+ | 3.5471 | 4.0793 | 14000 | 0.3564 | 3.6670 |
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+ | 3.5627 | 4.3706 | 15000 | 0.3577 | 3.6559 |
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+ | 3.5772 | 4.6620 | 16000 | 0.3592 | 3.6416 |
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+ | 3.5756 | 4.9534 | 17000 | 0.3605 | 3.6272 |
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+ | 3.4948 | 5.2448 | 18000 | 0.3604 | 3.6304 |
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+ | 3.5348 | 5.5361 | 19000 | 0.3613 | 3.6220 |
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+ | 3.5111 | 5.8275 | 20000 | 0.3627 | 3.6120 |
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+ | 3.4294 | 6.1189 | 21000 | 0.3626 | 3.6138 |
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+ | 3.468 | 6.4103 | 22000 | 0.3633 | 3.6076 |
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+ | 3.463 | 6.7016 | 23000 | 0.3641 | 3.5994 |
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+ | 3.4931 | 6.9930 | 24000 | 0.3651 | 3.5879 |
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+ | 3.4302 | 7.2844 | 25000 | 0.3649 | 3.5963 |
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+ | 3.4563 | 7.5758 | 26000 | 0.3654 | 3.5880 |
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+ | 3.4508 | 7.8671 | 27000 | 0.3665 | 3.5766 |
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+ | 3.3689 | 8.1585 | 28000 | 0.3662 | 3.5876 |
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+ | 3.409 | 8.4499 | 29000 | 0.3672 | 3.5788 |
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+ | 3.4213 | 8.7413 | 30000 | 0.3675 | 3.5736 |
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+ | 3.3257 | 9.0326 | 31000 | 0.3677 | 3.5775 |
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+ | 3.3722 | 9.3240 | 32000 | 0.3677 | 3.5775 |
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+ | 3.3982 | 9.6154 | 33000 | 0.3684 | 3.5674 |
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+ | 3.4083 | 9.9068 | 34000 | 0.3689 | 3.5608 |
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+ | 3.3294 | 10.1981 | 35000 | 0.3687 | 3.5735 |
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+ | 3.3591 | 10.4895 | 36000 | 0.3689 | 3.5666 |
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+ | 3.3894 | 10.7809 | 37000 | 0.3694 | 3.5561 |
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+ | 3.2944 | 11.0723 | 38000 | 0.3693 | 3.5667 |
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+ | 3.3381 | 11.3636 | 39000 | 0.3691 | 3.5636 |
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+ | 3.3591 | 11.6550 | 40000 | 0.3700 | 3.5557 |
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+ | 3.357 | 11.9464 | 41000 | 0.3706 | 3.5481 |
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+ | 3.3056 | 12.2378 | 42000 | 0.3699 | 3.5649 |
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+ | 3.3235 | 12.5291 | 43000 | 0.3705 | 3.5532 |
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+ | 3.3355 | 12.8205 | 44000 | 0.3705 | 3.5489 |
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+ | 3.2631 | 13.1119 | 45000 | 0.3701 | 3.5618 |
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+ | 3.3058 | 13.4033 | 46000 | 0.3707 | 3.5577 |
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+ | 3.3095 | 13.6946 | 47000 | 0.3713 | 3.5500 |
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+ | 3.3335 | 13.9860 | 48000 | 0.3718 | 3.5389 |
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+ | 3.2777 | 14.2774 | 49000 | 0.3712 | 3.5574 |
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+ | 3.313 | 14.5688 | 50000 | 0.3716 | 3.5501 |
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+ | 3.3186 | 14.8601 | 51000 | 0.3722 | 3.5429 |
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+ | 3.2468 | 15.1515 | 52000 | 0.3714 | 3.5522 |
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+ | 3.2767 | 15.4429 | 53000 | 0.3715 | 3.5495 |
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+ | 3.2932 | 15.7343 | 54000 | 0.3725 | 3.5390 |
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+ | 3.2057 | 16.0256 | 55000 | 0.3721 | 3.5518 |
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+ | 3.2652 | 16.3170 | 56000 | 0.3720 | 3.5508 |
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+ | 3.2886 | 16.6084 | 57000 | 0.3725 | 3.5458 |
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+ | 3.2946 | 16.8998 | 58000 | 0.3731 | 3.5339 |
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+ | 3.2236 | 17.1911 | 59000 | 0.3719 | 3.5545 |
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+ | 3.268 | 17.4825 | 60000 | 0.3725 | 3.5442 |
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+ | 3.2783 | 17.7739 | 61000 | 0.3730 | 3.5379 |
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+ | 3.1921 | 18.0653 | 62000 | 0.3721 | 3.5566 |
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+ | 3.2344 | 18.3566 | 63000 | 0.3727 | 3.5482 |
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+ | 3.2715 | 18.6480 | 64000 | 0.3732 | 3.5396 |
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+ | 3.2683 | 18.9394 | 65000 | 0.3736 | 3.5344 |
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+ | 3.2061 | 19.2308 | 66000 | 0.3728 | 3.5469 |
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+ | 3.2432 | 19.5221 | 67000 | 0.3731 | 3.5429 |
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+ | 3.2545 | 19.8135 | 68000 | 0.3736 | 3.5355 |
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+ | 3.1751 | 20.1049 | 69000 | 0.3732 | 3.5499 |
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+ | 3.2055 | 20.3963 | 70000 | 0.3729 | 3.5491 |
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+ | 3.2364 | 20.6876 | 71000 | 0.3736 | 3.5382 |
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+ | 3.2603 | 20.9790 | 72000 | 0.3741 | 3.5327 |
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+ | 3.1853 | 21.2704 | 73000 | 0.3733 | 3.5471 |
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+ | 3.2229 | 21.5618 | 74000 | 0.3736 | 3.5428 |
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+ | 3.2503 | 21.8531 | 75000 | 0.3743 | 3.5331 |
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+ | 3.1733 | 22.1445 | 76000 | 0.3730 | 3.5514 |
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+ | 3.1996 | 22.4359 | 77000 | 0.3737 | 3.5417 |
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+ | 3.2241 | 22.7273 | 78000 | 0.3742 | 3.5335 |
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+ | 3.1207 | 23.0186 | 79000 | 0.3738 | 3.5484 |
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+ | 3.1867 | 23.3100 | 80000 | 0.3737 | 3.5505 |
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+ | 3.1736 | 23.6014 | 81000 | 3.5509 | 0.3738 |
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+ | 3.1804 | 23.8928 | 82000 | 3.5459 | 0.3740 |
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+ | 3.166 | 24.1841 | 83000 | 3.5539 | 0.3734 |
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+ | 3.193 | 24.4755 | 84000 | 3.5468 | 0.3740 |
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+ | 3.2055 | 24.7669 | 85000 | 3.5372 | 0.3745 |
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+ | 3.125 | 25.0583 | 86000 | 3.5497 | 0.3741 |
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+ | 3.1831 | 25.3497 | 87000 | 3.5500 | 0.3737 |
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+ | 3.1967 | 25.6410 | 88000 | 3.5418 | 0.3745 |
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+ | 3.198 | 25.9324 | 89000 | 3.5323 | 0.3752 |
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+ | 3.1476 | 26.2238 | 90000 | 3.5518 | 0.3741 |
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+ | 3.1699 | 26.5152 | 91000 | 3.5434 | 0.3745 |
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+ | 3.1932 | 26.8065 | 92000 | 3.5361 | 0.3746 |
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+ | 3.129 | 27.0979 | 93000 | 3.5533 | 0.3737 |
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+ | 3.1585 | 27.3893 | 94000 | 3.5470 | 0.3741 |
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+ | 3.1692 | 27.6807 | 95000 | 3.5368 | 0.3751 |
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+ | 3.2099 | 27.9720 | 96000 | 3.5339 | 0.3755 |
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+ | 3.1312 | 28.2634 | 97000 | 3.5470 | 0.3748 |
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+ | 3.1501 | 28.5548 | 98000 | 3.5463 | 0.3748 |
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+ | 3.1644 | 28.8462 | 99000 | 3.5356 | 0.3749 |
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+ | 3.1114 | 29.1375 | 100000 | 3.5504 | 0.3742 |
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+ | 3.1421 | 29.4289 | 101000 | 3.5466 | 0.3746 |
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+ | 3.1544 | 29.7203 | 102000 | 3.5421 | 0.3751 |
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+ | 3.1002 | 30.0117 | 103000 | 3.5492 | 0.3748 |
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+ | 3.1165 | 30.3030 | 104000 | 3.5489 | 0.3747 |
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+ | 3.1392 | 30.5944 | 105000 | 3.5429 | 0.3749 |
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+ | 3.1409 | 30.8858 | 106000 | 3.5419 | 0.3754 |
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+ | 3.101 | 31.1772 | 107000 | 3.5554 | 0.3743 |
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+ | 3.1215 | 31.4685 | 108000 | 3.5474 | 0.3751 |
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+ | 3.1317 | 31.7599 | 109000 | 3.5389 | 0.3754 |
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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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