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Demosthene-OR
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t5-small-finetuned-en-to-fr

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update model card README.md

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@@ -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 [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: 2.0063
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- - Bleu: 42.1181
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- - Gen Len: 8.6667
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  ## Model description
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@@ -43,32 +43,112 @@ 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: 20
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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 | 1 | 2.6488 | 21.9728 | 9.0 |
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- | No log | 2.0 | 2 | 2.5827 | 21.9728 | 9.0 |
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- | No log | 3.0 | 3 | 2.5204 | 21.9728 | 9.0 |
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- | No log | 4.0 | 4 | 2.4619 | 31.7783 | 9.0 |
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- | No log | 5.0 | 5 | 2.4063 | 31.7783 | 9.0 |
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- | No log | 6.0 | 6 | 2.3545 | 31.7783 | 9.0 |
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- | No log | 7.0 | 7 | 2.3044 | 32.857 | 9.0 |
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- | No log | 8.0 | 8 | 2.2592 | 32.857 | 9.0 |
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- | No log | 9.0 | 9 | 2.2182 | 32.857 | 9.0 |
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- | No log | 10.0 | 10 | 2.1816 | 32.857 | 9.0 |
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- | No log | 11.0 | 11 | 2.1476 | 32.857 | 9.0 |
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- | No log | 12.0 | 12 | 2.1175 | 32.857 | 9.0 |
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- | No log | 13.0 | 13 | 2.0914 | 32.857 | 9.0 |
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- | No log | 14.0 | 14 | 2.0696 | 32.857 | 9.0 |
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- | No log | 15.0 | 15 | 2.0510 | 44.7214 | 8.3333 |
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- | No log | 16.0 | 16 | 2.0357 | 44.7214 | 8.3333 |
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- | No log | 17.0 | 17 | 2.0238 | 44.7214 | 8.3333 |
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- | No log | 18.0 | 18 | 2.0150 | 44.7214 | 8.3333 |
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- | No log | 19.0 | 19 | 2.0092 | 44.7214 | 8.3333 |
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- | No log | 20.0 | 20 | 2.0063 | 42.1181 | 8.6667 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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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: 0.8160
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+ - Bleu: 52.5642
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+ - Gen Len: 6.6667
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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: 100
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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 | 1 | 2.6488 | 21.9728 | 9.0 |
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+ | No log | 2.0 | 2 | 2.5800 | 21.9728 | 9.0 |
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+ | No log | 3.0 | 3 | 2.5120 | 31.7783 | 9.0 |
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+ | No log | 4.0 | 4 | 2.4455 | 31.7783 | 9.0 |
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+ | No log | 5.0 | 5 | 2.3783 | 31.7783 | 9.0 |
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+ | No log | 6.0 | 6 | 2.3129 | 32.857 | 9.0 |
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+ | No log | 7.0 | 7 | 2.2477 | 32.857 | 9.0 |
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+ | No log | 8.0 | 8 | 2.1856 | 32.857 | 9.0 |
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+ | No log | 9.0 | 9 | 2.1239 | 32.857 | 9.0 |
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+ | No log | 10.0 | 10 | 2.0648 | 32.857 | 9.0 |
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+ | No log | 11.0 | 11 | 2.0086 | 42.1181 | 8.6667 |
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+ | No log | 12.0 | 12 | 1.9568 | 42.1181 | 8.6667 |
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+ | No log | 13.0 | 13 | 1.9103 | 42.1181 | 8.6667 |
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+ | No log | 14.0 | 14 | 1.8669 | 42.1181 | 8.6667 |
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+ | No log | 15.0 | 15 | 1.8262 | 50.8368 | 7.0 |
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+ | No log | 16.0 | 16 | 1.7884 | 50.8368 | 7.0 |
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+ | No log | 17.0 | 17 | 1.7525 | 50.8368 | 7.0 |
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+ | No log | 18.0 | 18 | 1.7177 | 50.8368 | 7.0 |
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+ | No log | 19.0 | 19 | 1.6839 | 50.8368 | 7.0 |
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+ | No log | 20.0 | 20 | 1.6512 | 50.8368 | 7.0 |
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+ | No log | 21.0 | 21 | 1.6205 | 50.8368 | 7.0 |
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+ | No log | 22.0 | 22 | 1.5914 | 50.8368 | 7.0 |
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+ | No log | 23.0 | 23 | 1.5629 | 50.8368 | 7.0 |
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+ | No log | 24.0 | 24 | 1.5351 | 50.8368 | 7.0 |
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+ | No log | 25.0 | 25 | 1.5085 | 50.8368 | 7.0 |
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+ | No log | 26.0 | 26 | 1.4834 | 50.8368 | 7.0 |
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+ | No log | 27.0 | 27 | 1.4596 | 50.8368 | 7.0 |
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+ | No log | 28.0 | 28 | 1.4364 | 50.8368 | 7.0 |
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+ | No log | 29.0 | 29 | 1.4138 | 50.8368 | 7.0 |
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+ | No log | 30.0 | 30 | 1.3922 | 50.8368 | 7.0 |
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+ | No log | 31.0 | 31 | 1.3717 | 50.8368 | 7.0 |
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+ | No log | 32.0 | 32 | 1.3520 | 50.8368 | 7.0 |
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+ | No log | 33.0 | 33 | 1.3329 | 50.8368 | 7.0 |
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+ | No log | 34.0 | 34 | 1.3143 | 50.8368 | 7.0 |
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+ | No log | 35.0 | 35 | 1.2964 | 52.5642 | 6.6667 |
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+ | No log | 36.0 | 36 | 1.2786 | 52.5642 | 6.6667 |
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+ | No log | 37.0 | 37 | 1.2611 | 52.5642 | 6.6667 |
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+ | No log | 38.0 | 38 | 1.2446 | 52.5642 | 6.6667 |
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+ | No log | 39.0 | 39 | 1.2285 | 52.5642 | 6.6667 |
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+ | No log | 40.0 | 40 | 1.2128 | 52.5642 | 6.6667 |
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+ | No log | 41.0 | 41 | 1.1977 | 52.5642 | 6.6667 |
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+ | No log | 42.0 | 42 | 1.1828 | 52.5642 | 6.6667 |
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+ | No log | 43.0 | 43 | 1.1679 | 52.5642 | 6.6667 |
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+ | No log | 44.0 | 44 | 1.1532 | 52.5642 | 6.6667 |
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+ | No log | 45.0 | 45 | 1.1392 | 52.5642 | 6.6667 |
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+ | No log | 46.0 | 46 | 1.1253 | 52.5642 | 6.6667 |
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+ | No log | 47.0 | 47 | 1.1119 | 52.5642 | 6.6667 |
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+ | No log | 48.0 | 48 | 1.0989 | 52.5642 | 6.6667 |
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+ | No log | 49.0 | 49 | 1.0867 | 52.5642 | 6.6667 |
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+ | No log | 50.0 | 50 | 1.0748 | 52.5642 | 6.6667 |
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+ | No log | 51.0 | 51 | 1.0636 | 52.5642 | 6.6667 |
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+ | No log | 52.0 | 52 | 1.0527 | 52.5642 | 6.6667 |
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+ | No log | 53.0 | 53 | 1.0421 | 52.5642 | 6.6667 |
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+ | No log | 54.0 | 54 | 1.0315 | 52.5642 | 6.6667 |
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+ | No log | 55.0 | 55 | 1.0213 | 52.5642 | 6.6667 |
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+ | No log | 56.0 | 56 | 1.0116 | 52.5642 | 6.6667 |
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+ | No log | 57.0 | 57 | 1.0018 | 52.5642 | 6.6667 |
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+ | No log | 58.0 | 58 | 0.9923 | 52.5642 | 6.6667 |
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+ | No log | 59.0 | 59 | 0.9832 | 52.5642 | 6.6667 |
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+ | No log | 60.0 | 60 | 0.9743 | 52.5642 | 6.6667 |
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+ | No log | 61.0 | 61 | 0.9659 | 52.5642 | 6.6667 |
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+ | No log | 62.0 | 62 | 0.9578 | 52.5642 | 6.6667 |
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+ | No log | 63.0 | 63 | 0.9496 | 52.5642 | 6.6667 |
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+ | No log | 64.0 | 64 | 0.9416 | 52.5642 | 6.6667 |
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+ | No log | 65.0 | 65 | 0.9341 | 52.5642 | 6.6667 |
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+ | No log | 66.0 | 66 | 0.9266 | 52.5642 | 6.6667 |
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+ | No log | 67.0 | 67 | 0.9195 | 52.5642 | 6.6667 |
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+ | No log | 68.0 | 68 | 0.9125 | 52.5642 | 6.6667 |
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+ | No log | 69.0 | 69 | 0.9062 | 52.5642 | 6.6667 |
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+ | No log | 70.0 | 70 | 0.9002 | 52.5642 | 6.6667 |
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+ | No log | 71.0 | 71 | 0.8947 | 52.5642 | 6.6667 |
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+ | No log | 72.0 | 72 | 0.8894 | 52.5642 | 6.6667 |
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+ | No log | 73.0 | 73 | 0.8843 | 52.5642 | 6.6667 |
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+ | No log | 74.0 | 74 | 0.8794 | 52.5642 | 6.6667 |
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+ | No log | 75.0 | 75 | 0.8745 | 52.5642 | 6.6667 |
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+ | No log | 76.0 | 76 | 0.8698 | 52.5642 | 6.6667 |
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+ | No log | 77.0 | 77 | 0.8651 | 52.5642 | 6.6667 |
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+ | No log | 78.0 | 78 | 0.8607 | 52.5642 | 6.6667 |
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+ | No log | 79.0 | 79 | 0.8564 | 52.5642 | 6.6667 |
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+ | No log | 80.0 | 80 | 0.8525 | 52.5642 | 6.6667 |
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+ | No log | 81.0 | 81 | 0.8486 | 52.5642 | 6.6667 |
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+ | No log | 82.0 | 82 | 0.8449 | 52.5642 | 6.6667 |
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+ | No log | 83.0 | 83 | 0.8416 | 52.5642 | 6.6667 |
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+ | No log | 84.0 | 84 | 0.8386 | 52.5642 | 6.6667 |
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+ | No log | 85.0 | 85 | 0.8359 | 52.5642 | 6.6667 |
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+ | No log | 86.0 | 86 | 0.8333 | 52.5642 | 6.6667 |
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+ | No log | 87.0 | 87 | 0.8310 | 52.5642 | 6.6667 |
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+ | No log | 88.0 | 88 | 0.8290 | 52.5642 | 6.6667 |
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+ | No log | 89.0 | 89 | 0.8270 | 52.5642 | 6.6667 |
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+ | No log | 90.0 | 90 | 0.8251 | 52.5642 | 6.6667 |
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+ | No log | 91.0 | 91 | 0.8234 | 52.5642 | 6.6667 |
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+ | No log | 92.0 | 92 | 0.8218 | 52.5642 | 6.6667 |
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+ | No log | 93.0 | 93 | 0.8205 | 52.5642 | 6.6667 |
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+ | No log | 94.0 | 94 | 0.8193 | 52.5642 | 6.6667 |
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+ | No log | 95.0 | 95 | 0.8183 | 52.5642 | 6.6667 |
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+ | No log | 96.0 | 96 | 0.8175 | 52.5642 | 6.6667 |
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+ | No log | 97.0 | 97 | 0.8169 | 52.5642 | 6.6667 |
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+ | No log | 98.0 | 98 | 0.8164 | 52.5642 | 6.6667 |
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+ | No log | 99.0 | 99 | 0.8161 | 52.5642 | 6.6667 |
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+ | No log | 100.0 | 100 | 0.8160 | 52.5642 | 6.6667 |
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  ### Framework versions