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modelo_entrenado_02

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  1. README.md +102 -52
  2. model.safetensors +1 -1
  3. runs/May24_18-03-21_2a37799bfdb0/events.out.tfevents.1716573802.2a37799bfdb0.1942.0 +3 -0
  4. runs/May24_18-03-43_2a37799bfdb0/events.out.tfevents.1716573824.2a37799bfdb0.1942.1 +3 -0
  5. runs/May24_18-03-43_2a37799bfdb0/events.out.tfevents.1716573875.2a37799bfdb0.1942.2 +3 -0
  6. training_args.bin +1 -1
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.9396
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  ## Model description
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@@ -40,62 +40,112 @@ 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: 50
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | No log | 1.0 | 2 | 2.4935 |
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- | No log | 2.0 | 4 | 2.8214 |
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- | No log | 3.0 | 6 | 2.7883 |
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- | No log | 4.0 | 8 | 2.8334 |
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- | No log | 5.0 | 10 | 2.7451 |
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- | No log | 6.0 | 12 | 2.4568 |
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- | No log | 7.0 | 14 | 2.4742 |
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- | No log | 8.0 | 16 | 2.6113 |
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- | No log | 9.0 | 18 | 2.8200 |
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- | No log | 10.0 | 20 | 2.8160 |
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- | No log | 11.0 | 22 | 2.4983 |
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- | No log | 12.0 | 24 | 2.5141 |
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- | No log | 13.0 | 26 | 2.4966 |
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- | No log | 14.0 | 28 | 2.3954 |
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- | No log | 15.0 | 30 | 2.8277 |
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- | No log | 16.0 | 32 | 2.7597 |
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- | No log | 17.0 | 34 | 2.4643 |
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- | No log | 18.0 | 36 | 2.8983 |
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- | No log | 19.0 | 38 | 2.9526 |
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- | No log | 20.0 | 40 | 2.5481 |
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- | No log | 21.0 | 42 | 2.5330 |
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- | No log | 22.0 | 44 | 3.0032 |
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- | No log | 23.0 | 46 | 2.8084 |
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- | No log | 24.0 | 48 | 2.7706 |
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- | No log | 25.0 | 50 | 2.9537 |
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- | No log | 26.0 | 52 | 2.6999 |
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- | No log | 27.0 | 54 | 2.8320 |
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- | No log | 28.0 | 56 | 2.8468 |
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- | No log | 29.0 | 58 | 2.6420 |
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- | No log | 30.0 | 60 | 2.7281 |
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- | No log | 31.0 | 62 | 2.9489 |
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- | No log | 32.0 | 64 | 2.5408 |
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- | No log | 33.0 | 66 | 2.8423 |
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- | No log | 34.0 | 68 | 3.0089 |
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- | No log | 35.0 | 70 | 2.9187 |
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- | No log | 36.0 | 72 | 2.7514 |
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- | No log | 37.0 | 74 | 3.0102 |
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- | No log | 38.0 | 76 | 2.7669 |
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- | No log | 39.0 | 78 | 2.9588 |
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- | No log | 40.0 | 80 | 2.6657 |
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- | No log | 41.0 | 82 | 2.9423 |
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- | No log | 42.0 | 84 | 2.8133 |
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- | No log | 43.0 | 86 | 2.9580 |
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- | No log | 44.0 | 88 | 2.7164 |
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- | No log | 45.0 | 90 | 2.8963 |
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- | No log | 46.0 | 92 | 2.4701 |
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- | No log | 47.0 | 94 | 2.9313 |
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- | No log | 48.0 | 96 | 2.8447 |
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- | No log | 49.0 | 98 | 2.8477 |
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- | No log | 50.0 | 100 | 2.8419 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
15
 
16
  This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the None dataset.
17
  It achieves the following results on the evaluation set:
18
+ - Loss: 2.9377
19
 
20
  ## Model description
21
 
 
40
  - seed: 42
41
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
42
  - lr_scheduler_type: linear
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+ - num_epochs: 100
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45
  ### Training results
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47
  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | No log | 1.0 | 2 | 2.4285 |
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+ | No log | 2.0 | 4 | 2.5700 |
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+ | No log | 3.0 | 6 | 2.3661 |
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+ | No log | 4.0 | 8 | 2.7635 |
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+ | No log | 5.0 | 10 | 2.6494 |
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+ | No log | 6.0 | 12 | 2.5599 |
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+ | No log | 7.0 | 14 | 2.8686 |
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+ | No log | 8.0 | 16 | 2.9705 |
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+ | No log | 9.0 | 18 | 2.6723 |
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+ | No log | 10.0 | 20 | 2.5567 |
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+ | No log | 11.0 | 22 | 2.4658 |
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+ | No log | 12.0 | 24 | 2.5316 |
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+ | No log | 13.0 | 26 | 2.6476 |
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+ | No log | 14.0 | 28 | 2.4711 |
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+ | No log | 15.0 | 30 | 2.7310 |
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+ | No log | 16.0 | 32 | 2.8316 |
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+ | No log | 17.0 | 34 | 2.7867 |
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+ | No log | 18.0 | 36 | 2.3467 |
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+ | No log | 19.0 | 38 | 3.1519 |
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+ | No log | 20.0 | 40 | 2.9244 |
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+ | No log | 21.0 | 42 | 2.7193 |
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+ | No log | 22.0 | 44 | 2.8540 |
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+ | No log | 23.0 | 46 | 2.7119 |
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+ | No log | 24.0 | 48 | 2.9885 |
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+ | No log | 25.0 | 50 | 2.7189 |
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+ | No log | 26.0 | 52 | 2.7430 |
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+ | No log | 27.0 | 54 | 2.8829 |
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+ | No log | 28.0 | 56 | 2.7182 |
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+ | No log | 29.0 | 58 | 2.9149 |
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+ | No log | 30.0 | 60 | 2.7041 |
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+ | No log | 31.0 | 62 | 2.8468 |
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+ | No log | 32.0 | 64 | 2.9701 |
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+ | No log | 33.0 | 66 | 2.5975 |
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+ | No log | 34.0 | 68 | 2.9569 |
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+ | No log | 35.0 | 70 | 2.8847 |
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+ | No log | 36.0 | 72 | 3.2673 |
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+ | No log | 37.0 | 74 | 3.0552 |
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+ | No log | 38.0 | 76 | 2.8077 |
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+ | No log | 39.0 | 78 | 2.9599 |
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+ | No log | 40.0 | 80 | 2.9013 |
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+ | No log | 41.0 | 82 | 3.0198 |
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+ | No log | 42.0 | 84 | 2.6469 |
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+ | No log | 43.0 | 86 | 3.1038 |
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+ | No log | 44.0 | 88 | 2.8045 |
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+ | No log | 45.0 | 90 | 2.8941 |
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+ | No log | 46.0 | 92 | 2.6583 |
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+ | No log | 47.0 | 94 | 2.5010 |
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+ | No log | 48.0 | 96 | 2.8845 |
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+ | No log | 49.0 | 98 | 2.8941 |
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+ | No log | 50.0 | 100 | 2.9485 |
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+ | No log | 51.0 | 102 | 2.6861 |
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+ | No log | 52.0 | 104 | 2.8158 |
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+ | No log | 53.0 | 106 | 2.7242 |
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+ | No log | 54.0 | 108 | 2.8971 |
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+ | No log | 55.0 | 110 | 2.7668 |
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+ | No log | 56.0 | 112 | 2.8346 |
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+ | No log | 57.0 | 114 | 2.8979 |
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+ | No log | 58.0 | 116 | 2.6177 |
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+ | No log | 59.0 | 118 | 2.7576 |
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+ | No log | 60.0 | 120 | 2.6442 |
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+ | No log | 61.0 | 122 | 2.9222 |
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+ | No log | 62.0 | 124 | 2.6028 |
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+ | No log | 63.0 | 126 | 3.3076 |
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+ | No log | 64.0 | 128 | 2.6238 |
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+ | No log | 65.0 | 130 | 2.8379 |
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+ | No log | 66.0 | 132 | 2.7671 |
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+ | No log | 67.0 | 134 | 2.9184 |
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+ | No log | 68.0 | 136 | 2.8382 |
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+ | No log | 69.0 | 138 | 2.7783 |
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+ | No log | 70.0 | 140 | 2.9365 |
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+ | No log | 71.0 | 142 | 2.9453 |
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+ | No log | 72.0 | 144 | 2.6354 |
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+ | No log | 73.0 | 146 | 2.6368 |
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+ | No log | 74.0 | 148 | 2.9489 |
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+ | No log | 75.0 | 150 | 2.6480 |
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+ | No log | 76.0 | 152 | 3.0972 |
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+ | No log | 77.0 | 154 | 2.9844 |
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+ | No log | 78.0 | 156 | 2.7689 |
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+ | No log | 79.0 | 158 | 2.8069 |
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+ | No log | 80.0 | 160 | 2.7575 |
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+ | No log | 81.0 | 162 | 2.6872 |
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+ | No log | 82.0 | 164 | 3.0615 |
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+ | No log | 83.0 | 166 | 3.0133 |
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+ | No log | 84.0 | 168 | 2.8961 |
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+ | No log | 85.0 | 170 | 2.9905 |
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+ | No log | 86.0 | 172 | 2.9221 |
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+ | No log | 87.0 | 174 | 2.9477 |
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+ | No log | 88.0 | 176 | 3.1695 |
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+ | No log | 89.0 | 178 | 2.9689 |
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+ | No log | 90.0 | 180 | 2.8121 |
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+ | No log | 91.0 | 182 | 2.9417 |
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+ | No log | 92.0 | 184 | 3.2368 |
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+ | No log | 93.0 | 186 | 3.1631 |
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+ | No log | 94.0 | 188 | 2.8032 |
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+ | No log | 95.0 | 190 | 2.8622 |
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+ | No log | 96.0 | 192 | 2.9860 |
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+ | No log | 97.0 | 194 | 2.9899 |
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+ | No log | 98.0 | 196 | 3.0396 |
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+ | No log | 99.0 | 198 | 2.8936 |
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+ | No log | 100.0 | 200 | 2.9383 |
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  ### Framework versions
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