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--- |
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license: apache-2.0 |
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base_model: t5-small |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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model-index: |
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- name: my_awesome_opus_books_model |
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results: [] |
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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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# my_awesome_opus_books_model |
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This model is a fine-tuned version of [t5-small](https://huggingface.co./t5-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9121 |
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- Bleu: 0.0681 |
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- Gen Len: 19.0 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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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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- num_epochs: 100 |
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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 | Bleu | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:| |
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| No log | 1.0 | 15 | 3.8537 | 0.0406 | 19.0 | |
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| No log | 2.0 | 30 | 3.3215 | 0.0355 | 19.0 | |
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| No log | 3.0 | 45 | 3.0488 | 0.0322 | 19.0 | |
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| No log | 4.0 | 60 | 2.8891 | 0.0327 | 19.0 | |
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| No log | 5.0 | 75 | 2.7809 | 0.0451 | 19.0 | |
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| No log | 6.0 | 90 | 2.7010 | 0.0489 | 19.0 | |
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| No log | 7.0 | 105 | 2.6242 | 0.0416 | 19.0 | |
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| No log | 8.0 | 120 | 2.5600 | 0.053 | 19.0 | |
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| No log | 9.0 | 135 | 2.5093 | 0.0512 | 19.0 | |
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| No log | 10.0 | 150 | 2.4712 | 0.0526 | 19.0 | |
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| No log | 11.0 | 165 | 2.4346 | 0.0854 | 19.0 | |
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| No log | 12.0 | 180 | 2.3966 | 0.0892 | 19.0 | |
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| No log | 13.0 | 195 | 2.3590 | 0.1197 | 19.0 | |
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| No log | 14.0 | 210 | 2.3271 | 0.1243 | 19.0 | |
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| No log | 15.0 | 225 | 2.2995 | 0.1243 | 19.0 | |
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| No log | 16.0 | 240 | 2.2742 | 0.1004 | 19.0 | |
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| No log | 17.0 | 255 | 2.2569 | 0.1073 | 19.0 | |
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| No log | 18.0 | 270 | 2.2399 | 0.1305 | 19.0 | |
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| No log | 19.0 | 285 | 2.2236 | 0.1288 | 19.0 | |
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| No log | 20.0 | 300 | 2.2085 | 0.1248 | 19.0 | |
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| No log | 21.0 | 315 | 2.1936 | 0.1153 | 19.0 | |
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| No log | 22.0 | 330 | 2.1801 | 0.093 | 19.0 | |
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| No log | 23.0 | 345 | 2.1685 | 0.1079 | 19.0 | |
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| No log | 24.0 | 360 | 2.1568 | 0.1079 | 19.0 | |
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| No log | 25.0 | 375 | 2.1464 | 0.0881 | 19.0 | |
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| No log | 26.0 | 390 | 2.1365 | 0.0881 | 19.0 | |
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| No log | 27.0 | 405 | 2.1264 | 0.0876 | 19.0 | |
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| No log | 28.0 | 420 | 2.1166 | 0.0858 | 19.0 | |
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| No log | 29.0 | 435 | 2.1079 | 0.0858 | 19.0 | |
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| No log | 30.0 | 450 | 2.1001 | 0.0863 | 19.0 | |
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| No log | 31.0 | 465 | 2.0919 | 0.0871 | 19.0 | |
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| No log | 32.0 | 480 | 2.0853 | 0.0833 | 19.0 | |
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| No log | 33.0 | 495 | 2.0781 | 0.0833 | 19.0 | |
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| 2.7093 | 34.0 | 510 | 2.0698 | 0.0833 | 19.0 | |
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| 2.7093 | 35.0 | 525 | 2.0632 | 0.0833 | 19.0 | |
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| 2.7093 | 36.0 | 540 | 2.0562 | 0.0828 | 19.0 | |
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| 2.7093 | 37.0 | 555 | 2.0514 | 0.0799 | 19.0 | |
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| 2.7093 | 38.0 | 570 | 2.0458 | 0.0761 | 19.0 | |
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| 2.7093 | 39.0 | 585 | 2.0400 | 0.0761 | 19.0 | |
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| 2.7093 | 40.0 | 600 | 2.0352 | 0.0799 | 19.0 | |
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| 2.7093 | 41.0 | 615 | 2.0297 | 0.0761 | 19.0 | |
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| 2.7093 | 42.0 | 630 | 2.0244 | 0.0748 | 19.0 | |
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| 2.7093 | 43.0 | 645 | 2.0200 | 0.075 | 19.0 | |
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| 2.7093 | 44.0 | 660 | 2.0155 | 0.0748 | 19.0 | |
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| 2.7093 | 45.0 | 675 | 2.0104 | 0.0748 | 19.0 | |
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| 2.7093 | 46.0 | 690 | 2.0053 | 0.075 | 19.0 | |
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| 2.7093 | 47.0 | 705 | 2.0012 | 0.075 | 19.0 | |
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| 2.7093 | 48.0 | 720 | 1.9966 | 0.075 | 19.0 | |
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| 2.7093 | 49.0 | 735 | 1.9923 | 0.075 | 19.0 | |
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| 2.7093 | 50.0 | 750 | 1.9890 | 0.075 | 19.0 | |
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| 2.7093 | 51.0 | 765 | 1.9856 | 0.0747 | 19.0 | |
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| 2.7093 | 52.0 | 780 | 1.9820 | 0.0747 | 19.0 | |
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| 2.7093 | 53.0 | 795 | 1.9793 | 0.0752 | 19.0 | |
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| 2.7093 | 54.0 | 810 | 1.9763 | 0.0733 | 19.0 | |
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| 2.7093 | 55.0 | 825 | 1.9731 | 0.0733 | 19.0 | |
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| 2.7093 | 56.0 | 840 | 1.9695 | 0.0733 | 19.0 | |
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| 2.7093 | 57.0 | 855 | 1.9666 | 0.0733 | 19.0 | |
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| 2.7093 | 58.0 | 870 | 1.9643 | 0.0733 | 19.0 | |
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| 2.7093 | 59.0 | 885 | 1.9617 | 0.0627 | 19.0 | |
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| 2.7093 | 60.0 | 900 | 1.9590 | 0.0732 | 19.0 | |
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| 2.7093 | 61.0 | 915 | 1.9561 | 0.0626 | 19.0 | |
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| 2.7093 | 62.0 | 930 | 1.9532 | 0.0626 | 19.0 | |
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| 2.7093 | 63.0 | 945 | 1.9509 | 0.0626 | 19.0 | |
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| 2.7093 | 64.0 | 960 | 1.9487 | 0.0626 | 19.0 | |
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| 2.7093 | 65.0 | 975 | 1.9473 | 0.0608 | 19.0 | |
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| 2.7093 | 66.0 | 990 | 1.9454 | 0.0608 | 19.0 | |
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| 2.1497 | 67.0 | 1005 | 1.9430 | 0.0613 | 19.0 | |
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| 2.1497 | 68.0 | 1020 | 1.9407 | 0.0613 | 19.0 | |
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| 2.1497 | 69.0 | 1035 | 1.9389 | 0.0613 | 19.0 | |
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| 2.1497 | 70.0 | 1050 | 1.9371 | 0.0613 | 19.0 | |
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| 2.1497 | 71.0 | 1065 | 1.9356 | 0.0613 | 19.0 | |
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| 2.1497 | 72.0 | 1080 | 1.9341 | 0.0613 | 19.0 | |
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| 2.1497 | 73.0 | 1095 | 1.9320 | 0.0613 | 19.0 | |
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| 2.1497 | 74.0 | 1110 | 1.9304 | 0.0681 | 19.0 | |
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| 2.1497 | 75.0 | 1125 | 1.9290 | 0.0681 | 19.0 | |
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| 2.1497 | 76.0 | 1140 | 1.9276 | 0.0681 | 19.0 | |
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| 2.1497 | 77.0 | 1155 | 1.9260 | 0.0681 | 19.0 | |
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| 2.1497 | 78.0 | 1170 | 1.9248 | 0.0681 | 19.0 | |
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| 2.1497 | 79.0 | 1185 | 1.9235 | 0.0681 | 19.0 | |
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| 2.1497 | 80.0 | 1200 | 1.9223 | 0.0681 | 19.0 | |
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| 2.1497 | 81.0 | 1215 | 1.9213 | 0.0681 | 19.0 | |
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| 2.1497 | 82.0 | 1230 | 1.9204 | 0.0681 | 19.0 | |
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| 2.1497 | 83.0 | 1245 | 1.9197 | 0.0681 | 19.0 | |
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| 2.1497 | 84.0 | 1260 | 1.9190 | 0.0681 | 19.0 | |
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| 2.1497 | 85.0 | 1275 | 1.9181 | 0.069 | 19.0 | |
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| 2.1497 | 86.0 | 1290 | 1.9175 | 0.069 | 19.0 | |
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| 2.1497 | 87.0 | 1305 | 1.9167 | 0.069 | 19.0 | |
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| 2.1497 | 88.0 | 1320 | 1.9159 | 0.069 | 19.0 | |
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| 2.1497 | 89.0 | 1335 | 1.9152 | 0.069 | 19.0 | |
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| 2.1497 | 90.0 | 1350 | 1.9145 | 0.069 | 19.0 | |
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| 2.1497 | 91.0 | 1365 | 1.9140 | 0.069 | 19.0 | |
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| 2.1497 | 92.0 | 1380 | 1.9136 | 0.069 | 19.0 | |
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| 2.1497 | 93.0 | 1395 | 1.9132 | 0.0681 | 19.0 | |
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| 2.1497 | 94.0 | 1410 | 1.9130 | 0.0681 | 19.0 | |
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| 2.1497 | 95.0 | 1425 | 1.9127 | 0.0681 | 19.0 | |
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| 2.1497 | 96.0 | 1440 | 1.9125 | 0.0681 | 19.0 | |
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| 2.1497 | 97.0 | 1455 | 1.9123 | 0.069 | 19.0 | |
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| 2.1497 | 98.0 | 1470 | 1.9122 | 0.069 | 19.0 | |
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| 2.1497 | 99.0 | 1485 | 1.9121 | 0.0681 | 19.0 | |
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| 2.0375 | 100.0 | 1500 | 1.9121 | 0.0681 | 19.0 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.1.0 |
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- Tokenizers 0.15.2 |
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