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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- wikitext |
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metrics: |
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- accuracy |
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model-index: |
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- name: distilbert_sa_pre-training-complete |
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results: |
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- task: |
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name: Masked Language Modeling |
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type: fill-mask |
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dataset: |
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name: wikitext wikitext-103-raw-v1 |
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type: wikitext |
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config: wikitext-103-raw-v1 |
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split: validation |
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args: wikitext-103-raw-v1 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7119499337524314 |
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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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# distilbert_sa_pre-training-complete |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the wikitext wikitext-103-raw-v1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3367 |
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- Accuracy: 0.7119 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 10 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 300000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:------:|:---------------:|:--------:| |
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| 1.8819 | 1.0 | 1787 | 1.6350 | 0.6570 | |
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| 1.7699 | 2.0 | 3574 | 1.5847 | 0.6664 | |
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| 1.7308 | 3.0 | 5361 | 1.5857 | 0.6678 | |
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| 1.7062 | 4.0 | 7148 | 1.5679 | 0.6684 | |
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| 1.6858 | 5.0 | 8935 | 1.5573 | 0.6689 | |
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| 1.6684 | 6.0 | 10722 | 1.5591 | 0.6687 | |
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| 1.6545 | 7.0 | 12509 | 1.5253 | 0.6756 | |
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| 1.6438 | 8.0 | 14296 | 1.5304 | 0.6748 | |
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| 1.631 | 9.0 | 16083 | 1.4976 | 0.6805 | |
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| 1.6236 | 10.0 | 17870 | 1.5153 | 0.6773 | |
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| 1.613 | 11.0 | 19657 | 1.5010 | 0.6786 | |
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| 1.6046 | 12.0 | 21444 | 1.5069 | 0.6818 | |
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| 1.5963 | 13.0 | 23231 | 1.4796 | 0.6805 | |
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| 1.5906 | 14.0 | 25018 | 1.4858 | 0.6809 | |
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| 1.5833 | 15.0 | 26805 | 1.4962 | 0.6806 | |
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| 1.5771 | 16.0 | 28592 | 1.4749 | 0.6826 | |
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| 1.5703 | 17.0 | 30379 | 1.4724 | 0.6874 | |
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| 1.5663 | 18.0 | 32166 | 1.4946 | 0.6827 | |
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| 1.5614 | 19.0 | 33953 | 1.4934 | 0.6798 | |
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| 1.5558 | 20.0 | 35740 | 1.4512 | 0.6893 | |
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| 1.5508 | 21.0 | 37527 | 1.4417 | 0.6921 | |
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| 1.5466 | 22.0 | 39314 | 1.4744 | 0.6837 | |
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| 1.5427 | 23.0 | 41101 | 1.4530 | 0.6904 | |
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| 1.5382 | 24.0 | 42888 | 1.4378 | 0.6900 | |
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| 1.5342 | 25.0 | 44675 | 1.4732 | 0.6820 | |
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| 1.5293 | 26.0 | 46462 | 1.4609 | 0.6865 | |
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| 1.5259 | 27.0 | 48249 | 1.4400 | 0.6942 | |
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| 1.5223 | 28.0 | 50036 | 1.4586 | 0.6879 | |
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| 1.5197 | 29.0 | 51823 | 1.4371 | 0.6906 | |
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| 1.5161 | 30.0 | 53610 | 1.4335 | 0.6908 | |
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| 1.5126 | 31.0 | 55397 | 1.4159 | 0.6978 | |
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| 1.5087 | 32.0 | 57184 | 1.4412 | 0.6858 | |
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| 1.5061 | 33.0 | 58971 | 1.4181 | 0.6958 | |
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| 1.5035 | 34.0 | 60758 | 1.4357 | 0.6903 | |
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| 1.5011 | 35.0 | 62545 | 1.4147 | 0.6914 | |
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| 1.4967 | 36.0 | 64332 | 1.4251 | 0.6931 | |
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| 1.4954 | 37.0 | 66119 | 1.4366 | 0.6910 | |
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| 1.4925 | 38.0 | 67906 | 1.4488 | 0.6896 | |
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| 1.4889 | 39.0 | 69693 | 1.4336 | 0.6907 | |
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| 1.4866 | 40.0 | 71480 | 1.4226 | 0.6945 | |
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| 1.4838 | 41.0 | 73267 | 1.4210 | 0.6951 | |
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| 1.4821 | 42.0 | 75054 | 1.4081 | 0.6944 | |
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| 1.4792 | 43.0 | 76841 | 1.4496 | 0.6895 | |
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| 1.4778 | 44.0 | 78628 | 1.4263 | 0.6925 | |
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| 1.4754 | 45.0 | 80415 | 1.3995 | 0.6982 | |
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| 1.4736 | 46.0 | 82202 | 1.3958 | 0.6992 | |
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| 1.4702 | 47.0 | 83989 | 1.4073 | 0.6989 | |
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| 1.4683 | 48.0 | 85776 | 1.3917 | 0.6996 | |
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| 1.4663 | 49.0 | 87563 | 1.4109 | 0.6956 | |
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| 1.4648 | 50.0 | 89350 | 1.4003 | 0.6991 | |
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| 1.4619 | 51.0 | 91137 | 1.3847 | 0.7040 | |
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| 1.4599 | 52.0 | 92924 | 1.4323 | 0.6936 | |
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| 1.4596 | 53.0 | 94711 | 1.3935 | 0.6986 | |
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| 1.4567 | 54.0 | 96498 | 1.4122 | 0.6974 | |
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| 1.455 | 55.0 | 98285 | 1.3975 | 0.6977 | |
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| 1.4533 | 56.0 | 100072 | 1.3907 | 0.7004 | |
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| 1.4513 | 57.0 | 101859 | 1.3957 | 0.6997 | |
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| 1.45 | 58.0 | 103646 | 1.3907 | 0.7001 | |
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| 1.4466 | 59.0 | 105433 | 1.4063 | 0.6988 | |
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| 1.4455 | 60.0 | 107220 | 1.3600 | 0.7036 | |
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| 1.4439 | 61.0 | 109007 | 1.3941 | 0.7015 | |
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| 1.4432 | 62.0 | 110794 | 1.3854 | 0.7016 | |
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| 1.4404 | 63.0 | 112581 | 1.4080 | 0.6973 | |
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| 1.4397 | 64.0 | 114368 | 1.3924 | 0.7011 | |
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| 1.4366 | 65.0 | 116155 | 1.3872 | 0.7049 | |
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| 1.4358 | 66.0 | 117942 | 1.3924 | 0.7010 | |
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| 1.4339 | 67.0 | 119729 | 1.3895 | 0.6989 | |
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| 1.4329 | 68.0 | 121516 | 1.4007 | 0.7002 | |
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| 1.4319 | 69.0 | 123303 | 1.3672 | 0.7047 | |
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| 1.4287 | 70.0 | 125090 | 1.3892 | 0.7021 | |
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| 1.4284 | 71.0 | 126877 | 1.3674 | 0.7016 | |
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| 1.4265 | 72.0 | 128664 | 1.3983 | 0.6962 | |
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| 1.4254 | 73.0 | 130451 | 1.3665 | 0.7006 | |
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| 1.4231 | 74.0 | 132238 | 1.3852 | 0.7003 | |
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| 1.4228 | 75.0 | 134025 | 1.4328 | 0.6945 | |
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| 1.4217 | 76.0 | 135812 | 1.3831 | 0.7031 | |
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| 1.4198 | 77.0 | 137599 | 1.3897 | 0.7017 | |
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| 1.4183 | 78.0 | 139386 | 1.3790 | 0.7027 | |
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| 1.417 | 79.0 | 141173 | 1.3697 | 0.7063 | |
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| 1.4179 | 80.0 | 142960 | 1.3805 | 0.7008 | |
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| 1.414 | 81.0 | 144747 | 1.3579 | 0.7051 | |
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| 1.4132 | 82.0 | 146534 | 1.3727 | 0.7054 | |
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| 1.4112 | 83.0 | 148321 | 1.3763 | 0.7014 | |
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| 1.412 | 84.0 | 150108 | 1.3806 | 0.7051 | |
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| 1.4103 | 85.0 | 151895 | 1.3889 | 0.7022 | |
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| 1.4082 | 86.0 | 153682 | 1.3886 | 0.6993 | |
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| 1.4068 | 87.0 | 155469 | 1.3721 | 0.7025 | |
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| 1.4068 | 88.0 | 157256 | 1.3589 | 0.7050 | |
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| 1.4043 | 89.0 | 159043 | 1.3599 | 0.7043 | |
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| 1.4042 | 90.0 | 160830 | 1.3675 | 0.7055 | |
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| 1.4033 | 91.0 | 162617 | 1.3720 | 0.7031 | |
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| 1.402 | 92.0 | 164404 | 1.3506 | 0.7067 | |
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| 1.4004 | 93.0 | 166191 | 1.3833 | 0.7017 | |
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| 1.4001 | 94.0 | 167978 | 1.3734 | 0.7021 | |
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| 1.398 | 95.0 | 169765 | 1.3792 | 0.7037 | |
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| 1.3983 | 96.0 | 171552 | 1.3676 | 0.7050 | |
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| 1.3966 | 97.0 | 173339 | 1.3888 | 0.7027 | |
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| 1.3953 | 98.0 | 175126 | 1.3928 | 0.7004 | |
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| 1.3934 | 99.0 | 176913 | 1.3824 | 0.7011 | |
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| 1.3928 | 100.0 | 178700 | 1.3829 | 0.7040 | |
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| 1.3919 | 101.0 | 180487 | 1.3534 | 0.7046 | |
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| 1.3902 | 102.0 | 182274 | 1.3559 | 0.7048 | |
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| 1.3896 | 103.0 | 184061 | 1.3682 | 0.7045 | |
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| 1.3895 | 104.0 | 185848 | 1.3643 | 0.7053 | |
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| 1.3884 | 105.0 | 187635 | 1.3854 | 0.7018 | |
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| 1.3878 | 106.0 | 189422 | 1.3702 | 0.7038 | |
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| 1.3865 | 107.0 | 191209 | 1.3530 | 0.7056 | |
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| 1.3842 | 108.0 | 192996 | 1.3804 | 0.7008 | |
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| 1.3836 | 109.0 | 194783 | 1.3508 | 0.7073 | |
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| 1.3831 | 110.0 | 196570 | 1.3821 | 0.7002 | |
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| 1.3828 | 111.0 | 198357 | 1.3552 | 0.7063 | |
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| 1.382 | 112.0 | 200144 | 1.3567 | 0.7090 | |
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| 1.3806 | 113.0 | 201931 | 1.3915 | 0.7022 | |
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| 1.3802 | 114.0 | 203718 | 1.3661 | 0.7098 | |
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| 1.3789 | 115.0 | 205505 | 1.3586 | 0.7071 | |
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| 1.3789 | 116.0 | 207292 | 1.3643 | 0.7049 | |
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| 1.3782 | 117.0 | 209079 | 1.3716 | 0.7037 | |
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| 1.3763 | 118.0 | 210866 | 1.3476 | 0.7077 | |
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| 1.3762 | 119.0 | 212653 | 1.3519 | 0.7067 | |
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| 1.3741 | 120.0 | 214440 | 1.3736 | 0.7027 | |
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| 1.3741 | 121.0 | 216227 | 1.3395 | 0.7073 | |
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| 1.3732 | 122.0 | 218014 | 1.3724 | 0.7020 | |
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| 1.3724 | 123.0 | 219801 | 1.3724 | 0.7025 | |
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| 1.3715 | 124.0 | 221588 | 1.3572 | 0.7083 | |
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| 1.3713 | 125.0 | 223375 | 1.3430 | 0.7101 | |
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| 1.369 | 126.0 | 225162 | 1.3457 | 0.7103 | |
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| 1.3687 | 127.0 | 226949 | 1.3457 | 0.7112 | |
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| 1.3698 | 128.0 | 228736 | 1.3649 | 0.7024 | |
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| 1.3683 | 129.0 | 230523 | 1.3422 | 0.7105 | |
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| 1.3668 | 130.0 | 232310 | 1.3531 | 0.7058 | |
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| 1.3675 | 131.0 | 234097 | 1.3607 | 0.7059 | |
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| 1.3661 | 132.0 | 235884 | 1.3553 | 0.7063 | |
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| 1.3642 | 133.0 | 237671 | 1.3541 | 0.7054 | |
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| 1.364 | 134.0 | 239458 | 1.3564 | 0.7080 | |
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| 1.3635 | 135.0 | 241245 | 1.3634 | 0.7055 | |
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| 1.3621 | 136.0 | 243032 | 1.3689 | 0.7043 | |
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| 1.3623 | 137.0 | 244819 | 1.3668 | 0.7087 | |
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| 1.3614 | 138.0 | 246606 | 1.3535 | 0.7061 | |
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| 1.3614 | 139.0 | 248393 | 1.3588 | 0.7086 | |
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| 1.3588 | 140.0 | 250180 | 1.3472 | 0.7091 | |
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| 1.3598 | 141.0 | 251967 | 1.3425 | 0.7085 | |
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| 1.3601 | 142.0 | 253754 | 1.3533 | 0.7099 | |
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| 1.3585 | 143.0 | 255541 | 1.3298 | 0.7112 | |
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| 1.3586 | 144.0 | 257328 | 1.3583 | 0.7036 | |
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| 1.3583 | 145.0 | 259115 | 1.3455 | 0.7081 | |
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| 1.3567 | 146.0 | 260902 | 1.3674 | 0.7045 | |
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| 1.3561 | 147.0 | 262689 | 1.3705 | 0.7056 | |
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| 1.3552 | 148.0 | 264476 | 1.3506 | 0.7080 | |
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| 1.3547 | 149.0 | 266263 | 1.3457 | 0.7120 | |
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| 1.3538 | 150.0 | 268050 | 1.3245 | 0.7100 | |
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| 1.3543 | 151.0 | 269837 | 1.3278 | 0.7110 | |
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| 1.3549 | 152.0 | 271624 | 1.3345 | 0.7103 | |
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| 1.3528 | 153.0 | 273411 | 1.3336 | 0.7089 | |
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| 1.3528 | 154.0 | 275198 | 1.3620 | 0.7075 | |
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| 1.3531 | 155.0 | 276985 | 1.3383 | 0.7120 | |
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| 1.3525 | 156.0 | 278772 | 1.3377 | 0.7091 | |
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| 1.3509 | 157.0 | 280559 | 1.3639 | 0.7054 | |
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| 1.3502 | 158.0 | 282346 | 1.3456 | 0.7091 | |
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| 1.351 | 159.0 | 284133 | 1.3359 | 0.7110 | |
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| 1.3493 | 160.0 | 285920 | 1.3361 | 0.7129 | |
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| 1.3497 | 161.0 | 287707 | 1.3350 | 0.7091 | |
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| 1.3484 | 162.0 | 289494 | 1.3582 | 0.7075 | |
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| 1.35 | 163.0 | 291281 | 1.3441 | 0.7100 | |
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| 1.3485 | 164.0 | 293068 | 1.3227 | 0.7093 | |
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| 1.3485 | 165.0 | 294855 | 1.3386 | 0.7118 | |
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| 1.3483 | 166.0 | 296642 | 1.3470 | 0.7087 | |
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| 1.3481 | 167.0 | 298429 | 1.3405 | 0.7087 | |
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| 1.3465 | 167.88 | 300000 | 1.3382 | 0.7062 | |
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### Framework versions |
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- Transformers 4.26.0 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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