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  1. cost_to_push_frequency_40817/README.md +163 -0
  2. cost_to_push_frequency_40817/all_results.json +16 -0
  3. cost_to_push_frequency_40817/checkpoint-100000/config.json +31 -0
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  16. cost_to_push_frequency_40817/checkpoint-100000/vocab.json +0 -0
  17. cost_to_push_frequency_40817/checkpoint-40000/config.json +31 -0
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  29. cost_to_push_frequency_40817/checkpoint-40000/training_args.bin +3 -0
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  31. cost_to_push_frequency_40817/checkpoint-70000/config.json +31 -0
  32. cost_to_push_frequency_40817/checkpoint-70000/generation_config.json +6 -0
  33. cost_to_push_frequency_40817/checkpoint-70000/merges.txt +0 -0
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  41. cost_to_push_frequency_40817/checkpoint-70000/tokenizer_config.json +20 -0
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  45. cost_to_push_frequency_40817/checkpoint-80000/config.json +31 -0
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  48. cost_to_push_frequency_40817/checkpoint-80000/model.safetensors +3 -0
  49. cost_to_push_frequency_40817/checkpoint-80000/optimizer.pt +3 -0
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cost_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_cost_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/w8fx0r0m)
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+ # exceptions_exp2_cost_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: 3.5598
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+ - Accuracy: 0.3697
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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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+ | 4.8127 | 0.2912 | 1000 | 0.2567 | 4.7381 |
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+ | 4.3335 | 0.5824 | 2000 | 0.2996 | 4.2858 |
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+ | 4.1534 | 0.8737 | 3000 | 0.3156 | 4.0959 |
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+ | 3.9897 | 1.1648 | 4000 | 0.3250 | 3.9880 |
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+ | 3.9207 | 1.4561 | 5000 | 0.3320 | 3.9177 |
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+ | 3.873 | 1.7473 | 6000 | 0.3373 | 3.8572 |
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+ | 3.7433 | 2.0384 | 7000 | 0.3414 | 3.8152 |
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+ | 3.7535 | 2.3297 | 8000 | 0.3447 | 3.7854 |
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+ | 3.7376 | 2.6209 | 9000 | 0.3469 | 3.7569 |
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+ | 3.7252 | 2.9121 | 10000 | 0.3495 | 3.7304 |
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+ | 3.6234 | 3.2033 | 11000 | 0.3517 | 3.7156 |
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+ | 3.6557 | 3.4945 | 12000 | 0.3533 | 3.6976 |
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+ | 3.6457 | 3.7857 | 13000 | 0.3549 | 3.6785 |
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+ | 3.5349 | 4.0769 | 14000 | 0.3563 | 3.6728 |
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+ | 3.5641 | 4.3681 | 15000 | 0.3572 | 3.6605 |
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+ | 3.5836 | 4.6593 | 16000 | 0.3581 | 3.6491 |
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+ | 3.5664 | 4.9506 | 17000 | 0.3594 | 3.6349 |
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+ | 3.5001 | 5.2417 | 18000 | 0.3602 | 3.6395 |
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+ | 3.517 | 5.5329 | 19000 | 0.3608 | 3.6293 |
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+ | 3.5431 | 5.8242 | 20000 | 0.3619 | 3.6172 |
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+ | 3.4399 | 6.1153 | 21000 | 0.3624 | 3.6206 |
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+ | 3.4835 | 6.4065 | 22000 | 0.3628 | 3.6148 |
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+ | 3.4843 | 6.6978 | 23000 | 0.3637 | 3.6034 |
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+ | 3.5065 | 6.9890 | 24000 | 0.3644 | 3.5931 |
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+ | 3.4255 | 7.2802 | 25000 | 0.3643 | 3.5995 |
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+ | 3.4515 | 7.5714 | 26000 | 0.3653 | 3.5941 |
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+ | 3.4696 | 7.8626 | 27000 | 0.3659 | 3.5824 |
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+ | 3.3641 | 8.1538 | 28000 | 0.3659 | 3.5928 |
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+ | 3.4108 | 8.4450 | 29000 | 0.3662 | 3.5870 |
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+ | 3.4221 | 8.7362 | 30000 | 0.3668 | 3.5794 |
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+ | 3.3236 | 9.0274 | 31000 | 0.3667 | 3.5818 |
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+ | 3.3853 | 9.3186 | 32000 | 0.3668 | 3.5826 |
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+ | 3.3915 | 9.6098 | 33000 | 0.3678 | 3.5712 |
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+ | 3.4141 | 9.9010 | 34000 | 0.3684 | 3.5661 |
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+ | 3.3509 | 10.1922 | 35000 | 0.3678 | 3.5768 |
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+ | 3.362 | 10.4834 | 36000 | 0.3685 | 3.5677 |
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+ | 3.3798 | 10.7747 | 37000 | 0.3688 | 3.5631 |
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+ | 3.2987 | 11.0658 | 38000 | 0.3687 | 3.5727 |
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+ | 3.3238 | 11.3570 | 39000 | 0.3692 | 3.5684 |
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+ | 3.3598 | 11.6483 | 40000 | 0.3697 | 3.5598 |
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+ | 3.369 | 11.9395 | 41000 | 0.3703 | 3.5531 |
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+ | 3.3039 | 12.2306 | 42000 | 0.3693 | 3.5701 |
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+ | 3.3343 | 12.5219 | 43000 | 0.3698 | 3.5604 |
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+ | 3.3544 | 12.8131 | 44000 | 0.3704 | 3.5530 |
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+ | 3.2674 | 13.1043 | 45000 | 0.3702 | 3.5654 |
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+ | 3.3115 | 13.3955 | 46000 | 0.3702 | 3.5570 |
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+ | 3.3372 | 13.6867 | 47000 | 0.3709 | 3.5515 |
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+ | 3.3515 | 13.9779 | 48000 | 0.3715 | 3.5427 |
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+ | 3.2806 | 14.2691 | 49000 | 0.3707 | 3.5594 |
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+ | 3.2986 | 14.5603 | 50000 | 0.3711 | 3.5534 |
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+ | 3.3052 | 14.8515 | 51000 | 0.3715 | 3.5445 |
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+ | 3.2483 | 15.1427 | 52000 | 0.3708 | 3.5598 |
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+ | 3.2875 | 15.4339 | 53000 | 0.3711 | 3.5542 |
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+ | 3.2915 | 15.7251 | 54000 | 0.3718 | 3.5452 |
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+ | 3.2 | 16.0163 | 55000 | 0.3718 | 3.5551 |
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+ | 3.2613 | 16.3075 | 56000 | 0.3715 | 3.5532 |
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+ | 3.2859 | 16.5988 | 57000 | 0.3720 | 3.5457 |
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+ | 3.2906 | 16.8900 | 58000 | 0.3724 | 3.5421 |
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+ | 3.2407 | 17.1811 | 59000 | 0.3717 | 3.5552 |
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+ | 3.2587 | 17.4724 | 60000 | 0.3721 | 3.5497 |
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+ | 3.2695 | 17.7636 | 61000 | 0.3728 | 3.5404 |
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+ | 3.1818 | 18.0547 | 62000 | 0.3724 | 3.5517 |
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+ | 3.2254 | 18.3460 | 63000 | 0.3725 | 3.5471 |
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+ | 3.2572 | 18.6372 | 64000 | 0.3730 | 3.5421 |
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+ | 3.2777 | 18.9284 | 65000 | 0.3733 | 3.5330 |
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+ | 3.1986 | 19.2196 | 66000 | 0.3725 | 3.5531 |
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+ | 3.241 | 19.5108 | 67000 | 0.3730 | 3.5428 |
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+ | 3.2523 | 19.8020 | 68000 | 0.3734 | 3.5360 |
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+ | 3.1685 | 20.0932 | 69000 | 0.3726 | 3.5519 |
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+ | 3.2243 | 20.3844 | 70000 | 0.3731 | 3.5470 |
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+ | 3.2304 | 20.6756 | 71000 | 0.3736 | 3.5405 |
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+ | 3.2591 | 20.9669 | 72000 | 0.3739 | 3.5315 |
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+ | 3.1987 | 21.2580 | 73000 | 0.3731 | 3.5516 |
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+ | 3.2221 | 21.5492 | 74000 | 0.3734 | 3.5445 |
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+ | 3.2369 | 21.8405 | 75000 | 0.3740 | 3.5345 |
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+ | 3.1531 | 22.1316 | 76000 | 0.3731 | 3.5519 |
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+ | 3.2025 | 22.4229 | 77000 | 0.3734 | 3.5477 |
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+ | 3.2233 | 22.7141 | 78000 | 0.3741 | 3.5381 |
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+ | 3.1824 | 23.0052 | 79000 | 0.3734 | 3.5487 |
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+ | 3.1764 | 23.2965 | 80000 | 0.3738 | 3.5481 |
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+ | 3.1692 | 23.5877 | 81000 | 3.5507 | 0.3731 |
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+ | 3.2001 | 23.8789 | 82000 | 3.5438 | 0.3738 |
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+ | 3.1553 | 24.1704 | 83000 | 3.5570 | 0.3731 |
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+ | 3.1972 | 24.4616 | 84000 | 3.5480 | 0.3738 |
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+ | 3.1915 | 24.7528 | 85000 | 3.5381 | 0.3744 |
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+ | 3.1181 | 25.0440 | 86000 | 3.5499 | 0.3738 |
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+ | 3.1646 | 25.3352 | 87000 | 3.5475 | 0.3738 |
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+ | 3.1891 | 25.6264 | 88000 | 3.5407 | 0.3744 |
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+ | 3.1944 | 25.9176 | 89000 | 3.5363 | 0.3748 |
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+ | 3.1404 | 26.2088 | 90000 | 3.5520 | 0.3740 |
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+ | 3.1642 | 26.5000 | 91000 | 3.5457 | 0.3742 |
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+ | 3.1863 | 26.7913 | 92000 | 3.5325 | 0.3748 |
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+ | 3.112 | 27.0824 | 93000 | 3.5509 | 0.3740 |
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+ | 3.1551 | 27.3736 | 94000 | 3.5456 | 0.3744 |
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+ | 3.1736 | 27.6649 | 95000 | 3.5409 | 0.3746 |
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+ | 3.1848 | 27.9561 | 96000 | 3.5325 | 0.3755 |
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+ | 3.1264 | 28.2472 | 97000 | 3.5508 | 0.3742 |
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+ | 3.1589 | 28.5385 | 98000 | 3.5432 | 0.3748 |
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+ | 3.1664 | 28.8297 | 99000 | 3.5382 | 0.3750 |
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+ | 3.1008 | 29.1209 | 100000 | 3.5525 | 0.3742 |
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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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