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End of training

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  1. README.md +69 -44
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -16,9 +16,9 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/mpnet-base](https://huggingface.co/microsoft/mpnet-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2478
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- - F1: 0.8938
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- - Roc Auc: 0.6465
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  ## Model description
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@@ -43,52 +43,77 @@ The following hyperparameters were used during training:
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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: 40
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
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- | No log | 1.0 | 57 | 0.3726 | 0.8319 | 0.5 |
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- | No log | 2.0 | 114 | 0.3361 | 0.8319 | 0.5 |
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- | No log | 3.0 | 171 | 0.3303 | 0.8319 | 0.5 |
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- | No log | 4.0 | 228 | 0.3249 | 0.8319 | 0.5 |
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- | No log | 5.0 | 285 | 0.3188 | 0.8319 | 0.5 |
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- | No log | 6.0 | 342 | 0.3141 | 0.8319 | 0.5 |
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- | No log | 7.0 | 399 | 0.3089 | 0.8319 | 0.5 |
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- | No log | 8.0 | 456 | 0.3042 | 0.8319 | 0.5 |
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- | 0.3595 | 9.0 | 513 | 0.2997 | 0.8319 | 0.5 |
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- | 0.3595 | 10.0 | 570 | 0.2940 | 0.8319 | 0.5 |
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- | 0.3595 | 11.0 | 627 | 0.2898 | 0.8319 | 0.5 |
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- | 0.3595 | 12.0 | 684 | 0.2856 | 0.8463 | 0.5032 |
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- | 0.3595 | 13.0 | 741 | 0.2819 | 0.8593 | 0.5096 |
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- | 0.3595 | 14.0 | 798 | 0.2789 | 0.8600 | 0.5128 |
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- | 0.3595 | 15.0 | 855 | 0.2757 | 0.8701 | 0.5220 |
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- | 0.3595 | 16.0 | 912 | 0.2723 | 0.8733 | 0.5312 |
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- | 0.3595 | 17.0 | 969 | 0.2698 | 0.8733 | 0.5312 |
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- | 0.2983 | 18.0 | 1026 | 0.2670 | 0.8808 | 0.5629 |
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- | 0.2983 | 19.0 | 1083 | 0.2652 | 0.8814 | 0.5661 |
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- | 0.2983 | 20.0 | 1140 | 0.2630 | 0.8786 | 0.5744 |
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- | 0.2983 | 21.0 | 1197 | 0.2612 | 0.8807 | 0.5840 |
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- | 0.2983 | 22.0 | 1254 | 0.2596 | 0.8818 | 0.5900 |
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- | 0.2983 | 23.0 | 1311 | 0.2580 | 0.8841 | 0.6024 |
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- | 0.2983 | 24.0 | 1368 | 0.2562 | 0.8878 | 0.6153 |
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- | 0.2983 | 25.0 | 1425 | 0.2555 | 0.8851 | 0.6056 |
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- | 0.2983 | 26.0 | 1482 | 0.2544 | 0.8860 | 0.6088 |
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- | 0.2747 | 27.0 | 1539 | 0.2535 | 0.8868 | 0.6148 |
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- | 0.2747 | 28.0 | 1596 | 0.2527 | 0.8878 | 0.6153 |
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- | 0.2747 | 29.0 | 1653 | 0.2519 | 0.8869 | 0.6121 |
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- | 0.2747 | 30.0 | 1710 | 0.2512 | 0.8875 | 0.6180 |
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- | 0.2747 | 31.0 | 1767 | 0.2501 | 0.8900 | 0.6277 |
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- | 0.2747 | 32.0 | 1824 | 0.2495 | 0.8923 | 0.6401 |
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- | 0.2747 | 33.0 | 1881 | 0.2492 | 0.8907 | 0.6337 |
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- | 0.2747 | 34.0 | 1938 | 0.2488 | 0.8922 | 0.6401 |
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- | 0.2747 | 35.0 | 1995 | 0.2485 | 0.8915 | 0.6369 |
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- | 0.2633 | 36.0 | 2052 | 0.2480 | 0.8922 | 0.6401 |
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- | 0.2633 | 37.0 | 2109 | 0.2478 | 0.8938 | 0.6465 |
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- | 0.2633 | 38.0 | 2166 | 0.2477 | 0.8930 | 0.6433 |
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- | 0.2633 | 39.0 | 2223 | 0.2476 | 0.8938 | 0.6465 |
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- | 0.2633 | 40.0 | 2280 | 0.2476 | 0.8938 | 0.6465 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/mpnet-base](https://huggingface.co/microsoft/mpnet-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2601
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+ - F1: 0.8921
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+ - Roc Auc: 0.6253
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  ## Model description
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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: 65
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
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+ | No log | 1.0 | 57 | 0.3852 | 0.8161 | 0.5 |
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+ | No log | 2.0 | 114 | 0.3612 | 0.8161 | 0.5 |
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+ | No log | 3.0 | 171 | 0.3569 | 0.8161 | 0.5 |
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+ | No log | 4.0 | 228 | 0.3515 | 0.8161 | 0.5 |
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+ | No log | 5.0 | 285 | 0.3453 | 0.8161 | 0.5 |
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+ | No log | 6.0 | 342 | 0.3403 | 0.8161 | 0.5 |
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+ | No log | 7.0 | 399 | 0.3345 | 0.8161 | 0.5 |
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+ | No log | 8.0 | 456 | 0.3292 | 0.8161 | 0.5 |
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+ | 0.3585 | 9.0 | 513 | 0.3252 | 0.8161 | 0.5 |
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+ | 0.3585 | 10.0 | 570 | 0.3175 | 0.8161 | 0.5 |
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+ | 0.3585 | 11.0 | 627 | 0.3129 | 0.8161 | 0.5 |
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+ | 0.3585 | 12.0 | 684 | 0.3076 | 0.8351 | 0.5029 |
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+ | 0.3585 | 13.0 | 741 | 0.3024 | 0.8425 | 0.5109 |
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+ | 0.3585 | 14.0 | 798 | 0.2995 | 0.8516 | 0.5163 |
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+ | 0.3585 | 15.0 | 855 | 0.2953 | 0.8528 | 0.5221 |
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+ | 0.3585 | 16.0 | 912 | 0.2904 | 0.8744 | 0.5426 |
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+ | 0.3585 | 17.0 | 969 | 0.2875 | 0.8738 | 0.5451 |
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+ | 0.2943 | 18.0 | 1026 | 0.2835 | 0.8833 | 0.5798 |
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+ | 0.2943 | 19.0 | 1083 | 0.2811 | 0.8799 | 0.5710 |
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+ | 0.2943 | 20.0 | 1140 | 0.2786 | 0.8815 | 0.5873 |
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+ | 0.2943 | 21.0 | 1197 | 0.2761 | 0.8815 | 0.5873 |
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+ | 0.2943 | 22.0 | 1254 | 0.2750 | 0.8838 | 0.5906 |
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+ | 0.2943 | 23.0 | 1311 | 0.2705 | 0.8905 | 0.6194 |
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+ | 0.2943 | 24.0 | 1368 | 0.2687 | 0.8911 | 0.6224 |
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+ | 0.2943 | 25.0 | 1425 | 0.2674 | 0.8895 | 0.6165 |
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+ | 0.2943 | 26.0 | 1482 | 0.2652 | 0.8911 | 0.6224 |
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+ | 0.2666 | 27.0 | 1539 | 0.2642 | 0.8911 | 0.6224 |
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+ | 0.2666 | 28.0 | 1596 | 0.2634 | 0.8903 | 0.6194 |
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+ | 0.2666 | 29.0 | 1653 | 0.2612 | 0.8903 | 0.6194 |
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+ | 0.2666 | 30.0 | 1710 | 0.2601 | 0.8921 | 0.6253 |
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+ | 0.2666 | 31.0 | 1767 | 0.2583 | 0.8913 | 0.6328 |
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+ | 0.2666 | 32.0 | 1824 | 0.2568 | 0.8864 | 0.6319 |
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+ | 0.2666 | 33.0 | 1881 | 0.2563 | 0.8861 | 0.6319 |
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+ | 0.2666 | 34.0 | 1938 | 0.2552 | 0.8869 | 0.6349 |
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+ | 0.2666 | 35.0 | 1995 | 0.2544 | 0.8884 | 0.6378 |
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+ | 0.2516 | 36.0 | 2052 | 0.2530 | 0.8875 | 0.6374 |
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+ | 0.2516 | 37.0 | 2109 | 0.2523 | 0.8876 | 0.6374 |
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+ | 0.2516 | 38.0 | 2166 | 0.2514 | 0.8889 | 0.6432 |
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+ | 0.2516 | 39.0 | 2223 | 0.2504 | 0.8874 | 0.6453 |
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+ | 0.2516 | 40.0 | 2280 | 0.2502 | 0.8892 | 0.6432 |
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+ | 0.2516 | 41.0 | 2337 | 0.2495 | 0.8862 | 0.6419 |
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+ | 0.2516 | 42.0 | 2394 | 0.2490 | 0.8867 | 0.6445 |
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+ | 0.2516 | 43.0 | 2451 | 0.2491 | 0.8859 | 0.6365 |
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+ | 0.2442 | 44.0 | 2508 | 0.2480 | 0.8906 | 0.6511 |
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+ | 0.2442 | 45.0 | 2565 | 0.2476 | 0.8894 | 0.6457 |
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+ | 0.2442 | 46.0 | 2622 | 0.2476 | 0.8888 | 0.6478 |
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+ | 0.2442 | 47.0 | 2679 | 0.2474 | 0.8906 | 0.6511 |
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+ | 0.2442 | 48.0 | 2736 | 0.2462 | 0.8890 | 0.6507 |
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+ | 0.2442 | 49.0 | 2793 | 0.2461 | 0.8920 | 0.6545 |
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+ | 0.2442 | 50.0 | 2850 | 0.2455 | 0.8894 | 0.6532 |
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+ | 0.2442 | 51.0 | 2907 | 0.2457 | 0.8897 | 0.6507 |
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+ | 0.2442 | 52.0 | 2964 | 0.2452 | 0.8894 | 0.6532 |
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+ | 0.238 | 53.0 | 3021 | 0.2449 | 0.8903 | 0.6536 |
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+ | 0.238 | 54.0 | 3078 | 0.2447 | 0.8894 | 0.6532 |
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+ | 0.238 | 55.0 | 3135 | 0.2446 | 0.8894 | 0.6532 |
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+ | 0.238 | 56.0 | 3192 | 0.2446 | 0.8904 | 0.6536 |
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+ | 0.238 | 57.0 | 3249 | 0.2443 | 0.8894 | 0.6532 |
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+ | 0.238 | 58.0 | 3306 | 0.2441 | 0.8894 | 0.6532 |
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+ | 0.238 | 59.0 | 3363 | 0.2440 | 0.8911 | 0.6566 |
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+ | 0.238 | 60.0 | 3420 | 0.2440 | 0.8911 | 0.6566 |
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+ | 0.238 | 61.0 | 3477 | 0.2439 | 0.8903 | 0.6536 |
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+ | 0.2353 | 62.0 | 3534 | 0.2437 | 0.8911 | 0.6566 |
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+ | 0.2353 | 63.0 | 3591 | 0.2438 | 0.8911 | 0.6566 |
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+ | 0.2353 | 64.0 | 3648 | 0.2437 | 0.8911 | 0.6566 |
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+ | 0.2353 | 65.0 | 3705 | 0.2437 | 0.8911 | 0.6566 |
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  ### Framework versions
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