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modelo_entrenado_02

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  1. README.md +101 -101
  2. model.safetensors +1 -1
  3. runs/May27_20-58-59_34ec97677d65/events.out.tfevents.1716843540.34ec97677d65.1835.2 +3 -0
  4. runs/May27_20-58-59_34ec97677d65/events.out.tfevents.1716843588.34ec97677d65.1835.3 +3 -0
  5. 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: 3.1244
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  ## Model description
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@@ -46,106 +46,106 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
49
- | No log | 1.0 | 2 | 2.7577 |
50
- | No log | 2.0 | 4 | 2.9781 |
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- | No log | 3.0 | 6 | 2.8632 |
52
- | No log | 4.0 | 8 | 2.8579 |
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- | No log | 5.0 | 10 | 3.0384 |
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- | No log | 6.0 | 12 | 2.7311 |
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- | No log | 7.0 | 14 | 3.2083 |
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- | No log | 8.0 | 16 | 2.7743 |
57
- | No log | 9.0 | 18 | 2.9103 |
58
- | No log | 10.0 | 20 | 2.9129 |
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- | No log | 11.0 | 22 | 2.8430 |
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- | No log | 12.0 | 24 | 3.0835 |
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- | No log | 13.0 | 26 | 2.3511 |
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- | No log | 14.0 | 28 | 2.7013 |
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- | No log | 15.0 | 30 | 3.1549 |
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- | No log | 16.0 | 32 | 2.6080 |
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- | No log | 17.0 | 34 | 2.8091 |
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- | No log | 18.0 | 36 | 2.9793 |
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- | No log | 19.0 | 38 | 3.0124 |
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- | No log | 20.0 | 40 | 3.3556 |
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- | No log | 21.0 | 42 | 3.0714 |
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- | No log | 22.0 | 44 | 2.7299 |
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- | No log | 23.0 | 46 | 3.0126 |
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- | No log | 24.0 | 48 | 2.8463 |
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- | No log | 25.0 | 50 | 2.7301 |
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- | No log | 26.0 | 52 | 3.0173 |
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- | No log | 27.0 | 54 | 2.7944 |
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- | No log | 28.0 | 56 | 2.9017 |
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- | No log | 29.0 | 58 | 2.8487 |
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- | No log | 30.0 | 60 | 2.6775 |
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- | No log | 31.0 | 62 | 2.8994 |
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- | No log | 32.0 | 64 | 2.9530 |
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- | No log | 33.0 | 66 | 2.9083 |
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- | No log | 34.0 | 68 | 3.0679 |
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- | No log | 35.0 | 70 | 3.2776 |
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- | No log | 36.0 | 72 | 3.1745 |
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- | No log | 37.0 | 74 | 3.1096 |
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- | No log | 38.0 | 76 | 2.9348 |
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- | No log | 39.0 | 78 | 2.8553 |
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- | No log | 40.0 | 80 | 2.8863 |
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- | No log | 41.0 | 82 | 3.4298 |
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- | No log | 42.0 | 84 | 2.6532 |
91
- | No log | 43.0 | 86 | 3.0342 |
92
- | No log | 44.0 | 88 | 2.9126 |
93
- | No log | 45.0 | 90 | 3.0540 |
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- | No log | 46.0 | 92 | 2.5645 |
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- | No log | 47.0 | 94 | 2.5397 |
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- | No log | 48.0 | 96 | 2.9576 |
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- | No log | 49.0 | 98 | 3.0156 |
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- | No log | 50.0 | 100 | 2.9392 |
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- | No log | 51.0 | 102 | 3.0397 |
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- | No log | 52.0 | 104 | 2.6477 |
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- | No log | 53.0 | 106 | 3.2235 |
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- | No log | 54.0 | 108 | 2.8603 |
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- | No log | 55.0 | 110 | 3.0346 |
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- | No log | 56.0 | 112 | 3.1096 |
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- | No log | 57.0 | 114 | 3.3671 |
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- | No log | 58.0 | 116 | 3.1535 |
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- | No log | 59.0 | 118 | 2.7483 |
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- | No log | 60.0 | 120 | 3.1617 |
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- | No log | 61.0 | 122 | 3.2076 |
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- | No log | 62.0 | 124 | 3.0277 |
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- | No log | 63.0 | 126 | 3.1467 |
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- | No log | 64.0 | 128 | 2.9233 |
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- | No log | 65.0 | 130 | 3.1549 |
114
- | No log | 66.0 | 132 | 3.0969 |
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- | No log | 67.0 | 134 | 3.0112 |
116
- | No log | 68.0 | 136 | 3.1946 |
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- | No log | 69.0 | 138 | 3.2482 |
118
- | No log | 70.0 | 140 | 3.0938 |
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- | No log | 71.0 | 142 | 3.2812 |
120
- | No log | 72.0 | 144 | 3.1010 |
121
- | No log | 73.0 | 146 | 2.9116 |
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- | No log | 74.0 | 148 | 2.9614 |
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- | No log | 75.0 | 150 | 2.8463 |
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- | No log | 76.0 | 152 | 3.0709 |
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- | No log | 77.0 | 154 | 2.9854 |
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- | No log | 78.0 | 156 | 2.8761 |
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- | No log | 79.0 | 158 | 3.5857 |
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- | No log | 80.0 | 160 | 3.1981 |
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- | No log | 81.0 | 162 | 3.0583 |
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- | No log | 82.0 | 164 | 2.9779 |
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- | No log | 83.0 | 166 | 3.3871 |
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- | No log | 84.0 | 168 | 3.2019 |
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- | No log | 85.0 | 170 | 2.9458 |
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- | No log | 86.0 | 172 | 2.9492 |
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- | No log | 87.0 | 174 | 3.5746 |
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- | No log | 88.0 | 176 | 3.2414 |
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- | No log | 89.0 | 178 | 3.1301 |
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- | No log | 90.0 | 180 | 3.0594 |
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- | No log | 91.0 | 182 | 3.1043 |
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- | No log | 92.0 | 184 | 3.3868 |
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- | No log | 93.0 | 186 | 3.0604 |
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- | No log | 94.0 | 188 | 2.9658 |
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- | No log | 95.0 | 190 | 3.2042 |
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- | No log | 96.0 | 192 | 3.2314 |
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- | No log | 97.0 | 194 | 3.2674 |
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- | No log | 98.0 | 196 | 3.1568 |
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- | No log | 99.0 | 198 | 3.2152 |
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- | No log | 100.0 | 200 | 3.1337 |
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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: 2.8905
19
 
20
  ## Model description
21
 
 
46
 
47
  | Training Loss | Epoch | Step | Validation Loss |
48
  |:-------------:|:-----:|:----:|:---------------:|
49
+ | No log | 1.0 | 2 | 2.9081 |
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+ | No log | 2.0 | 4 | 2.8473 |
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+ | No log | 3.0 | 6 | 2.7549 |
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+ | No log | 4.0 | 8 | 2.5578 |
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+ | No log | 5.0 | 10 | 3.0478 |
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+ | No log | 6.0 | 12 | 2.9787 |
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+ | No log | 7.0 | 14 | 2.7132 |
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+ | No log | 8.0 | 16 | 2.8544 |
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+ | No log | 9.0 | 18 | 3.1011 |
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+ | No log | 10.0 | 20 | 2.7973 |
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+ | No log | 11.0 | 22 | 2.6940 |
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+ | No log | 12.0 | 24 | 2.7098 |
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+ | No log | 13.0 | 26 | 2.5052 |
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+ | No log | 14.0 | 28 | 2.7524 |
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+ | No log | 15.0 | 30 | 2.7444 |
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+ | No log | 16.0 | 32 | 2.4916 |
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+ | No log | 17.0 | 34 | 3.0314 |
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+ | No log | 18.0 | 36 | 3.1077 |
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+ | No log | 19.0 | 38 | 3.0316 |
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+ | No log | 20.0 | 40 | 2.5164 |
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+ | No log | 21.0 | 42 | 2.5739 |
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+ | No log | 22.0 | 44 | 2.8081 |
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+ | No log | 23.0 | 46 | 3.1536 |
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+ | No log | 24.0 | 48 | 2.9811 |
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+ | No log | 25.0 | 50 | 3.1687 |
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+ | No log | 26.0 | 52 | 3.0435 |
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+ | No log | 27.0 | 54 | 2.6157 |
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+ | No log | 28.0 | 56 | 2.7175 |
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+ | No log | 29.0 | 58 | 2.9729 |
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+ | No log | 30.0 | 60 | 2.7586 |
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+ | No log | 31.0 | 62 | 2.8325 |
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+ | No log | 32.0 | 64 | 2.9456 |
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+ | No log | 33.0 | 66 | 2.6372 |
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+ | No log | 34.0 | 68 | 2.8440 |
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+ | No log | 35.0 | 70 | 2.5303 |
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+ | No log | 36.0 | 72 | 3.2033 |
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+ | No log | 37.0 | 74 | 3.0512 |
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+ | No log | 38.0 | 76 | 2.8986 |
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+ | No log | 39.0 | 78 | 2.8305 |
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+ | No log | 40.0 | 80 | 2.9271 |
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+ | No log | 41.0 | 82 | 3.2164 |
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+ | No log | 42.0 | 84 | 2.9009 |
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+ | No log | 43.0 | 86 | 2.9351 |
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+ | No log | 44.0 | 88 | 2.4776 |
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+ | No log | 45.0 | 90 | 2.7373 |
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+ | No log | 46.0 | 92 | 3.0420 |
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+ | No log | 47.0 | 94 | 2.4812 |
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+ | No log | 48.0 | 96 | 2.7218 |
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+ | No log | 49.0 | 98 | 2.6222 |
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+ | No log | 50.0 | 100 | 2.9145 |
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+ | No log | 51.0 | 102 | 2.8870 |
100
+ | No log | 52.0 | 104 | 2.6611 |
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+ | No log | 53.0 | 106 | 2.8064 |
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+ | No log | 54.0 | 108 | 2.6478 |
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+ | No log | 55.0 | 110 | 3.1717 |
104
+ | No log | 56.0 | 112 | 2.6571 |
105
+ | No log | 57.0 | 114 | 3.1680 |
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+ | No log | 58.0 | 116 | 2.4588 |
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+ | No log | 59.0 | 118 | 3.0059 |
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+ | No log | 60.0 | 120 | 2.6247 |
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+ | No log | 61.0 | 122 | 2.7143 |
110
+ | No log | 62.0 | 124 | 2.6768 |
111
+ | No log | 63.0 | 126 | 3.1071 |
112
+ | No log | 64.0 | 128 | 2.5967 |
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+ | No log | 65.0 | 130 | 2.3665 |
114
+ | No log | 66.0 | 132 | 2.8559 |
115
+ | No log | 67.0 | 134 | 3.0175 |
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+ | No log | 68.0 | 136 | 2.9276 |
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+ | No log | 69.0 | 138 | 2.7686 |
118
+ | No log | 70.0 | 140 | 2.9915 |
119
+ | No log | 71.0 | 142 | 2.9836 |
120
+ | No log | 72.0 | 144 | 3.1500 |
121
+ | No log | 73.0 | 146 | 2.8040 |
122
+ | No log | 74.0 | 148 | 2.7839 |
123
+ | No log | 75.0 | 150 | 2.6345 |
124
+ | No log | 76.0 | 152 | 2.6594 |
125
+ | No log | 77.0 | 154 | 2.6113 |
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+ | No log | 78.0 | 156 | 2.9125 |
127
+ | No log | 79.0 | 158 | 2.8474 |
128
+ | No log | 80.0 | 160 | 3.0196 |
129
+ | No log | 81.0 | 162 | 2.9233 |
130
+ | No log | 82.0 | 164 | 2.7557 |
131
+ | No log | 83.0 | 166 | 3.1694 |
132
+ | No log | 84.0 | 168 | 3.0473 |
133
+ | No log | 85.0 | 170 | 2.6834 |
134
+ | No log | 86.0 | 172 | 2.6499 |
135
+ | No log | 87.0 | 174 | 2.9598 |
136
+ | No log | 88.0 | 176 | 2.7535 |
137
+ | No log | 89.0 | 178 | 2.7801 |
138
+ | No log | 90.0 | 180 | 2.8178 |
139
+ | No log | 91.0 | 182 | 3.0580 |
140
+ | No log | 92.0 | 184 | 3.3762 |
141
+ | No log | 93.0 | 186 | 2.8592 |
142
+ | No log | 94.0 | 188 | 3.0757 |
143
+ | No log | 95.0 | 190 | 3.0482 |
144
+ | No log | 96.0 | 192 | 2.9775 |
145
+ | No log | 97.0 | 194 | 3.0622 |
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+ | No log | 98.0 | 196 | 3.0460 |
147
+ | No log | 99.0 | 198 | 2.9721 |
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+ | No log | 100.0 | 200 | 3.1753 |
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  ### Framework versions
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