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bart-large-cnn-prompt_generation

Text2Text Generation
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End of training

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  1. README.md +59 -57
  2. model.safetensors +1 -1
  3. runs/Nov25_18-00-53_28f3f5ce4d66/events.out.tfevents.1700935261.28f3f5ce4d66.281.0 +2 -2
  4. runs/Nov25_18-00-53_28f3f5ce4d66/events.out.tfevents.1700938408.28f3f5ce4d66.281.1 +3 -0
README.md CHANGED
@@ -3,6 +3,8 @@ license: mit
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  base_model: facebook/bart-large-cnn
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: bart-large-cnn-prompt_generation
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  results: []
@@ -16,11 +18,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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  - Loss: 2.6454
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- - Actual score: 0.8766
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- - Predction score: 0.3383
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- - Score difference: 0.5383
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- - Map: 0.675
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- - Ndcg@10: 0.7065
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  ## Model description
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@@ -50,58 +52,58 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Actual score | Predction score | Score difference | Map | Ndcg@10 |
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- |:-------------:|:-----:|:----:|:---------------:|:------------:|:---------------:|:----------------:|:------:|:-------:|
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- | No log | 1.0 | 15 | 3.6562 | 0.8766 | -0.0289 | 0.9055 | 0.519 | 0.5699 |
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- | No log | 2.0 | 30 | 3.5539 | 0.8766 | 0.1581 | 0.7185 | 0.5457 | 0.5999 |
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- | No log | 3.0 | 45 | 3.3930 | 0.8766 | -0.0469 | 0.9235 | 0.654 | 0.7112 |
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- | No log | 4.0 | 60 | 3.2928 | 0.8766 | -0.1568 | 1.0334 | 0.5673 | 0.6259 |
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- | No log | 5.0 | 75 | 3.1723 | 0.8766 | -0.1002 | 0.9768 | 0.6457 | 0.6947 |
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- | No log | 6.0 | 90 | 3.0813 | 0.8766 | -0.1568 | 1.0334 | 0.589 | 0.6425 |
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- | No log | 7.0 | 105 | 3.0169 | 0.8766 | -0.6039 | 1.4805 | 0.659 | 0.7152 |
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- | No log | 8.0 | 120 | 2.9700 | 0.8766 | -0.7584 | 1.6350 | 0.6607 | 0.7159 |
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- | No log | 9.0 | 135 | 2.9340 | 0.8766 | -0.4008 | 1.2774 | 0.569 | 0.6225 |
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- | No log | 10.0 | 150 | 2.9044 | 0.8766 | -0.6995 | 1.5761 | 0.5923 | 0.6452 |
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- | No log | 11.0 | 165 | 2.8795 | 0.8766 | -0.4866 | 1.3632 | 0.5933 | 0.6460 |
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- | No log | 12.0 | 180 | 2.8558 | 0.8766 | -0.5519 | 1.4285 | 0.654 | 0.7112 |
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- | No log | 13.0 | 195 | 2.8351 | 0.8766 | -0.7601 | 1.6367 | 0.6940 | 0.7512 |
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- | No log | 14.0 | 210 | 2.8170 | 0.8766 | -0.7849 | 1.6616 | 0.6907 | 0.7538 |
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- | No log | 15.0 | 225 | 2.8016 | 0.8766 | -0.5879 | 1.4645 | 0.7140 | 0.7659 |
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- | No log | 16.0 | 240 | 2.7867 | 0.8766 | -0.6487 | 1.5254 | 0.7073 | 0.7659 |
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- | No log | 17.0 | 255 | 2.7737 | 0.8766 | -0.3421 | 1.2187 | 0.6923 | 0.7493 |
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- | No log | 18.0 | 270 | 2.7617 | 0.8766 | -0.1162 | 0.9928 | 0.6623 | 0.7219 |
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- | No log | 19.0 | 285 | 2.7502 | 0.8766 | -0.2738 | 1.1504 | 0.6023 | 0.6567 |
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- | No log | 20.0 | 300 | 2.7402 | 0.8766 | -0.5541 | 1.4307 | 0.6273 | 0.6859 |
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- | No log | 21.0 | 315 | 2.7312 | 0.8766 | -0.3386 | 1.2152 | 0.674 | 0.7259 |
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- | No log | 22.0 | 330 | 2.7228 | 0.8766 | -0.5500 | 1.4266 | 0.6940 | 0.7512 |
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- | No log | 23.0 | 345 | 2.7148 | 0.8766 | -0.2210 | 1.0976 | 0.6773 | 0.7338 |
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- | No log | 24.0 | 360 | 2.7074 | 0.8766 | -0.0863 | 0.9630 | 0.6773 | 0.7438 |
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- | No log | 25.0 | 375 | 2.7012 | 0.8766 | -0.1210 | 0.9976 | 0.6373 | 0.7038 |
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- | No log | 26.0 | 390 | 2.6955 | 0.8766 | -0.2872 | 1.1638 | 0.7217 | 0.7722 |
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- | No log | 27.0 | 405 | 2.6905 | 0.8766 | -0.1040 | 0.9806 | 0.7167 | 0.7682 |
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- | No log | 28.0 | 420 | 2.6859 | 0.8766 | -0.1951 | 1.0717 | 0.69 | 0.7329 |
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- | No log | 29.0 | 435 | 2.6815 | 0.8766 | -0.0243 | 0.9009 | 0.7133 | 0.7556 |
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- | No log | 30.0 | 450 | 2.6774 | 0.8766 | -0.1058 | 0.9824 | 0.6933 | 0.7356 |
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- | No log | 31.0 | 465 | 2.6732 | 0.8766 | -0.1431 | 1.0197 | 0.74 | 0.7803 |
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- | No log | 32.0 | 480 | 2.6697 | 0.8766 | -0.1289 | 1.0055 | 0.7 | 0.7403 |
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- | No log | 33.0 | 495 | 2.6668 | 0.8766 | -0.1033 | 0.9800 | 0.7367 | 0.7829 |
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- | 2.6871 | 34.0 | 510 | 2.6638 | 0.8766 | 0.0345 | 0.8422 | 0.7267 | 0.7756 |
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- | 2.6871 | 35.0 | 525 | 2.6613 | 0.8766 | 0.0778 | 0.7988 | 0.7557 | 0.8021 |
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- | 2.6871 | 36.0 | 540 | 2.6593 | 0.8766 | 0.0817 | 0.7950 | 0.7817 | 0.8269 |
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- | 2.6871 | 37.0 | 555 | 2.6572 | 0.8766 | 0.0656 | 0.8110 | 0.7517 | 0.7996 |
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- | 2.6871 | 38.0 | 570 | 2.6551 | 0.8766 | 0.1775 | 0.6991 | 0.7617 | 0.8069 |
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- | 2.6871 | 39.0 | 585 | 2.6535 | 0.8766 | 0.0677 | 0.8090 | 0.775 | 0.8169 |
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- | 2.6871 | 40.0 | 600 | 2.6520 | 0.8766 | 0.1447 | 0.7319 | 0.765 | 0.8043 |
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- | 2.6871 | 41.0 | 615 | 2.6508 | 0.8766 | 0.1812 | 0.6954 | 0.7017 | 0.7417 |
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- | 2.6871 | 42.0 | 630 | 2.6496 | 0.8766 | 0.2167 | 0.6600 | 0.6867 | 0.7303 |
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- | 2.6871 | 43.0 | 645 | 2.6488 | 0.8766 | 0.2700 | 0.6066 | 0.7267 | 0.7703 |
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- | 2.6871 | 44.0 | 660 | 2.6478 | 0.8766 | 0.3052 | 0.5714 | 0.6967 | 0.7377 |
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- | 2.6871 | 45.0 | 675 | 2.6472 | 0.8766 | 0.2416 | 0.6350 | 0.685 | 0.7191 |
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- | 2.6871 | 46.0 | 690 | 2.6466 | 0.8766 | 0.2533 | 0.6234 | 0.685 | 0.7191 |
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- | 2.6871 | 47.0 | 705 | 2.6461 | 0.8766 | 0.3144 | 0.5623 | 0.665 | 0.6991 |
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- | 2.6871 | 48.0 | 720 | 2.6458 | 0.8766 | 0.2416 | 0.6350 | 0.675 | 0.7065 |
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- | 2.6871 | 49.0 | 735 | 2.6455 | 0.8766 | 0.2159 | 0.6608 | 0.685 | 0.7191 |
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- | 2.6871 | 50.0 | 750 | 2.6454 | 0.8766 | 0.3383 | 0.5383 | 0.675 | 0.7065 |
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  ### Framework versions
 
3
  base_model: facebook/bart-large-cnn
4
  tags:
5
  - generated_from_trainer
6
+ metrics:
7
+ - rouge
8
  model-index:
9
  - name: bart-large-cnn-prompt_generation
10
  results: []
 
18
  This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on an unknown dataset.
19
  It achieves the following results on the evaluation set:
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  - Loss: 2.6454
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+ - Rouge1: 40.6908
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+ - Rouge2: 16.1706
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+ - Rougel: 25.6927
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+ - Rougelsum: 25.6588
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+ - Gen Len: 77.2
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
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+ | No log | 1.0 | 15 | 3.6562 | 25.0903 | 5.3158 | 16.4265 | 16.3853 | 67.42 |
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+ | No log | 2.0 | 30 | 3.5539 | 24.9011 | 4.9854 | 16.5812 | 16.5697 | 65.28 |
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+ | No log | 3.0 | 45 | 3.3930 | 24.9983 | 5.2373 | 17.0342 | 16.993 | 65.8 |
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+ | No log | 4.0 | 60 | 3.2928 | 24.8418 | 4.7159 | 16.929 | 16.907 | 66.0 |
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+ | No log | 5.0 | 75 | 3.1723 | 26.012 | 5.5696 | 17.4002 | 17.4621 | 66.84 |
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+ | No log | 6.0 | 90 | 3.0813 | 26.9443 | 5.8262 | 17.8297 | 17.8673 | 67.52 |
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+ | No log | 7.0 | 105 | 3.0169 | 27.7155 | 6.4297 | 18.4479 | 18.4913 | 66.78 |
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+ | No log | 8.0 | 120 | 2.9700 | 27.2858 | 6.5437 | 18.5185 | 18.4731 | 67.78 |
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+ | No log | 9.0 | 135 | 2.9340 | 28.0747 | 7.3049 | 18.7045 | 18.718 | 67.34 |
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+ | No log | 10.0 | 150 | 2.9044 | 28.4417 | 7.34 | 18.7805 | 18.8377 | 66.44 |
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+ | No log | 11.0 | 165 | 2.8795 | 28.8704 | 7.4119 | 18.7748 | 18.849 | 67.02 |
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+ | No log | 12.0 | 180 | 2.8558 | 28.5338 | 7.1929 | 18.7993 | 18.859 | 67.02 |
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+ | No log | 13.0 | 195 | 2.8351 | 30.3984 | 8.3546 | 19.8864 | 19.918 | 68.18 |
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+ | No log | 14.0 | 210 | 2.8170 | 30.934 | 8.8637 | 20.6051 | 20.6574 | 67.74 |
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+ | No log | 15.0 | 225 | 2.8016 | 33.611 | 10.3334 | 22.0692 | 22.11 | 67.94 |
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+ | No log | 16.0 | 240 | 2.7867 | 34.4518 | 11.2186 | 22.5517 | 22.5979 | 67.36 |
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+ | No log | 17.0 | 255 | 2.7737 | 33.8745 | 10.9904 | 22.0985 | 22.1333 | 68.98 |
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+ | No log | 18.0 | 270 | 2.7617 | 35.1795 | 11.6458 | 22.3628 | 22.3954 | 68.1 |
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+ | No log | 19.0 | 285 | 2.7502 | 35.3137 | 11.7688 | 22.7397 | 22.7986 | 67.24 |
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+ | No log | 20.0 | 300 | 2.7402 | 35.8673 | 12.3602 | 23.4671 | 23.481 | 67.32 |
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+ | No log | 21.0 | 315 | 2.7312 | 37.2112 | 13.6711 | 24.0348 | 24.0426 | 68.58 |
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+ | No log | 22.0 | 330 | 2.7228 | 37.521 | 14.1801 | 24.1826 | 24.2038 | 68.46 |
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+ | No log | 23.0 | 345 | 2.7148 | 37.4877 | 13.7803 | 24.2369 | 24.189 | 70.18 |
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+ | No log | 24.0 | 360 | 2.7074 | 38.2158 | 14.3195 | 24.4562 | 24.4262 | 69.56 |
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+ | No log | 25.0 | 375 | 2.7012 | 38.0379 | 14.2362 | 24.5273 | 24.4723 | 70.7 |
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+ | No log | 26.0 | 390 | 2.6955 | 37.4245 | 13.8152 | 24.4203 | 24.4188 | 69.52 |
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+ | No log | 27.0 | 405 | 2.6905 | 37.4296 | 13.4741 | 24.569 | 24.5797 | 70.7 |
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+ | No log | 28.0 | 420 | 2.6859 | 38.7617 | 14.3506 | 25.0565 | 25.0256 | 71.56 |
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+ | No log | 29.0 | 435 | 2.6815 | 39.3441 | 15.2271 | 25.4611 | 25.4251 | 73.38 |
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+ | No log | 30.0 | 450 | 2.6774 | 38.6753 | 14.4202 | 24.7802 | 24.8057 | 72.94 |
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+ | No log | 31.0 | 465 | 2.6732 | 39.7278 | 15.0554 | 25.4741 | 25.4578 | 74.02 |
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+ | No log | 32.0 | 480 | 2.6697 | 39.9498 | 15.0412 | 25.4949 | 25.5039 | 74.2 |
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+ | No log | 33.0 | 495 | 2.6668 | 40.0256 | 15.1986 | 25.4401 | 25.436 | 75.14 |
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+ | 2.6871 | 34.0 | 510 | 2.6638 | 39.8616 | 15.249 | 25.4639 | 25.4979 | 75.54 |
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+ | 2.6871 | 35.0 | 525 | 2.6613 | 39.9678 | 15.1735 | 25.7189 | 25.719 | 75.8 |
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+ | 2.6871 | 36.0 | 540 | 2.6593 | 40.3261 | 15.4175 | 25.6158 | 25.6426 | 75.0 |
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+ | 2.6871 | 37.0 | 555 | 2.6572 | 40.6307 | 15.3666 | 25.6045 | 25.6245 | 76.06 |
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+ | 2.6871 | 38.0 | 570 | 2.6551 | 41.2257 | 15.55 | 26.0762 | 26.0547 | 75.74 |
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+ | 2.6871 | 39.0 | 585 | 2.6535 | 41.2164 | 15.981 | 26.068 | 26.0566 | 76.16 |
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+ | 2.6871 | 40.0 | 600 | 2.6520 | 41.3161 | 15.9648 | 26.0276 | 26.0199 | 76.14 |
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+ | 2.6871 | 41.0 | 615 | 2.6508 | 41.1103 | 15.7775 | 25.2761 | 25.237 | 77.28 |
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+ | 2.6871 | 42.0 | 630 | 2.6496 | 41.4765 | 16.2494 | 26.021 | 26.0026 | 76.68 |
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+ | 2.6871 | 43.0 | 645 | 2.6488 | 41.725 | 16.3547 | 26.1039 | 26.067 | 75.88 |
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+ | 2.6871 | 44.0 | 660 | 2.6478 | 41.3649 | 16.3576 | 26.0133 | 25.9943 | 76.08 |
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+ | 2.6871 | 45.0 | 675 | 2.6472 | 41.1901 | 16.4955 | 26.0594 | 26.0468 | 76.34 |
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+ | 2.6871 | 46.0 | 690 | 2.6466 | 41.0942 | 16.2436 | 25.8578 | 25.853 | 75.92 |
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+ | 2.6871 | 47.0 | 705 | 2.6461 | 40.6232 | 16.1631 | 25.6709 | 25.6473 | 76.46 |
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+ | 2.6871 | 48.0 | 720 | 2.6458 | 41.1453 | 16.3914 | 25.946 | 25.9199 | 76.1 |
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+ | 2.6871 | 49.0 | 735 | 2.6455 | 41.0364 | 16.3432 | 25.8202 | 25.7964 | 76.18 |
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+ | 2.6871 | 50.0 | 750 | 2.6454 | 40.6908 | 16.1706 | 25.6927 | 25.6588 | 77.2 |
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  ### Framework versions
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