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  1. README.md +461 -19
  2. config.json +7 -7
  3. model.safetensors +2 -2
  4. tokenizer.json +0 -0
  5. tokenizer_config.json +5 -5
  6. training_args.bin +2 -2
  7. vocab.txt +0 -0
README.md CHANGED
@@ -1,7 +1,7 @@
1
  ---
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  library_name: transformers
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- license: mit
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- base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
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  tags:
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  - generated_from_trainer
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  model-index:
@@ -14,9 +14,9 @@ should probably proofread and complete it, then remove this comment. -->
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  # tapt_base_LR-2e-05
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- This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6639
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21
  ## Model description
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@@ -36,28 +36,470 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 3407
 
 
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.06
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- - num_epochs: 10
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:-----:|:----:|:---------------:|
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- | 1.7916 | 1.0 | 609 | 1.6565 |
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- | 1.5865 | 2.0 | 1218 | 1.6524 |
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- | 1.4759 | 3.0 | 1827 | 1.5922 |
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- | 1.3938 | 4.0 | 2436 | 1.6847 |
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- | 1.3161 | 5.0 | 3045 | 1.6620 |
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- | 1.2795 | 6.0 | 3654 | 1.7196 |
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- | 1.2487 | 7.0 | 4263 | 1.7240 |
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- | 1.208 | 8.0 | 4872 | 1.6970 |
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- | 1.1789 | 9.0 | 5481 | 1.6785 |
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- | 1.1856 | 10.0 | 6090 | 1.6639 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  ---
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  library_name: transformers
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+ license: apache-2.0
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+ base_model: bioformers/bioformer-16L
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  tags:
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  - generated_from_trainer
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  model-index:
 
14
 
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  # tapt_base_LR-2e-05
16
 
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+ This model is a fine-tuned version of [bioformers/bioformer-16L](https://huggingface.co/bioformers/bioformer-16L) on an unknown dataset.
18
  It achieves the following results on the evaluation set:
19
+ - Loss: 1.9776
20
 
21
  ## Model description
22
 
 
36
 
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  The following hyperparameters were used during training:
38
  - learning_rate: 2e-05
39
+ - train_batch_size: 64
40
+ - eval_batch_size: 64
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  - seed: 3407
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 1024
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
45
  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.06
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+ - num_epochs: 50
48
 
49
  ### Training results
50
 
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+ | Training Loss | Epoch | Step | Validation Loss |
52
+ |:-------------:|:-------:|:----:|:---------------:|
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+ | No log | 0.1046 | 1 | 2.2216 |
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+ | No log | 0.2092 | 2 | 2.1888 |
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+ | No log | 0.3137 | 3 | 2.1733 |
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+ | No log | 0.4183 | 4 | 2.1297 |
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+ | No log | 0.5229 | 5 | 2.1922 |
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+ | No log | 0.6275 | 6 | 2.1468 |
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+ | No log | 0.7320 | 7 | 2.1433 |
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+ | No log | 0.8366 | 8 | 2.0927 |
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+ | No log | 0.9412 | 9 | 2.1243 |
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+ | 2.4847 | 1.1046 | 10 | 2.1267 |
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+ | 2.4847 | 1.2092 | 11 | 2.0820 |
64
+ | 2.4847 | 1.3137 | 12 | 2.0738 |
65
+ | 2.4847 | 1.4183 | 13 | 2.0427 |
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+ | 2.4847 | 1.5229 | 14 | 2.0568 |
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+ | 2.4847 | 1.6275 | 15 | 2.0835 |
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+ | 2.4847 | 1.7320 | 16 | 2.0789 |
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+ | 2.4847 | 1.8366 | 17 | 2.0674 |
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+ | 2.4847 | 1.9412 | 18 | 2.0401 |
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+ | 2.4101 | 2.1046 | 19 | 2.0421 |
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+ | 2.4101 | 2.2092 | 20 | 2.0762 |
73
+ | 2.4101 | 2.3137 | 21 | 2.0065 |
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+ | 2.4101 | 2.4183 | 22 | 2.0763 |
75
+ | 2.4101 | 2.5229 | 23 | 2.0424 |
76
+ | 2.4101 | 2.6275 | 24 | 2.0310 |
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+ | 2.4101 | 2.7320 | 25 | 2.0874 |
78
+ | 2.4101 | 2.8366 | 26 | 2.0235 |
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+ | 2.4101 | 2.9412 | 27 | 2.0597 |
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+ | 2.3677 | 3.1046 | 28 | 1.9865 |
81
+ | 2.3677 | 3.2092 | 29 | 2.0295 |
82
+ | 2.3677 | 3.3137 | 30 | 2.0296 |
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+ | 2.3677 | 3.4183 | 31 | 2.0019 |
84
+ | 2.3677 | 3.5229 | 32 | 1.9696 |
85
+ | 2.3677 | 3.6275 | 33 | 2.0265 |
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+ | 2.3677 | 3.7320 | 34 | 2.0107 |
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+ | 2.3677 | 3.8366 | 35 | 2.0344 |
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+ | 2.3677 | 3.9412 | 36 | 2.0281 |
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+ | 2.2639 | 4.1046 | 37 | 2.0171 |
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+ | 2.2639 | 4.2092 | 38 | 2.0344 |
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+ | 2.2639 | 4.3137 | 39 | 1.9914 |
92
+ | 2.2639 | 4.4183 | 40 | 1.9856 |
93
+ | 2.2639 | 4.5229 | 41 | 2.0357 |
94
+ | 2.2639 | 4.6275 | 42 | 2.0289 |
95
+ | 2.2639 | 4.7320 | 43 | 1.9714 |
96
+ | 2.2639 | 4.8366 | 44 | 1.9895 |
97
+ | 2.2639 | 4.9412 | 45 | 1.9905 |
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+ | 2.2037 | 5.1046 | 46 | 1.9589 |
99
+ | 2.2037 | 5.2092 | 47 | 1.9865 |
100
+ | 2.2037 | 5.3137 | 48 | 2.0114 |
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+ | 2.2037 | 5.4183 | 49 | 2.0008 |
102
+ | 2.2037 | 5.5229 | 50 | 1.9578 |
103
+ | 2.2037 | 5.6275 | 51 | 2.0294 |
104
+ | 2.2037 | 5.7320 | 52 | 1.9585 |
105
+ | 2.2037 | 5.8366 | 53 | 1.9783 |
106
+ | 2.2037 | 5.9412 | 54 | 1.9880 |
107
+ | 2.16 | 6.1046 | 55 | 2.0060 |
108
+ | 2.16 | 6.2092 | 56 | 1.9558 |
109
+ | 2.16 | 6.3137 | 57 | 1.9664 |
110
+ | 2.16 | 6.4183 | 58 | 1.9201 |
111
+ | 2.16 | 6.5229 | 59 | 1.9816 |
112
+ | 2.16 | 6.6275 | 60 | 1.9682 |
113
+ | 2.16 | 6.7320 | 61 | 1.9605 |
114
+ | 2.16 | 6.8366 | 62 | 1.9233 |
115
+ | 2.16 | 6.9412 | 63 | 1.9687 |
116
+ | 2.1108 | 7.1046 | 64 | 1.9987 |
117
+ | 2.1108 | 7.2092 | 65 | 2.0023 |
118
+ | 2.1108 | 7.3137 | 66 | 1.9627 |
119
+ | 2.1108 | 7.4183 | 67 | 2.0215 |
120
+ | 2.1108 | 7.5229 | 68 | 1.9613 |
121
+ | 2.1108 | 7.6275 | 69 | 2.0261 |
122
+ | 2.1108 | 7.7320 | 70 | 1.9626 |
123
+ | 2.1108 | 7.8366 | 71 | 2.0007 |
124
+ | 2.1108 | 7.9412 | 72 | 1.9404 |
125
+ | 2.0949 | 8.1046 | 73 | 1.9943 |
126
+ | 2.0949 | 8.2092 | 74 | 2.0443 |
127
+ | 2.0949 | 8.3137 | 75 | 1.9909 |
128
+ | 2.0949 | 8.4183 | 76 | 1.9790 |
129
+ | 2.0949 | 8.5229 | 77 | 1.9505 |
130
+ | 2.0949 | 8.6275 | 78 | 1.9477 |
131
+ | 2.0949 | 8.7320 | 79 | 2.0272 |
132
+ | 2.0949 | 8.8366 | 80 | 1.9549 |
133
+ | 2.0949 | 8.9412 | 81 | 1.9641 |
134
+ | 2.0617 | 9.1046 | 82 | 1.9859 |
135
+ | 2.0617 | 9.2092 | 83 | 1.9376 |
136
+ | 2.0617 | 9.3137 | 84 | 1.9699 |
137
+ | 2.0617 | 9.4183 | 85 | 1.9334 |
138
+ | 2.0617 | 9.5229 | 86 | 1.9708 |
139
+ | 2.0617 | 9.6275 | 87 | 1.9700 |
140
+ | 2.0617 | 9.7320 | 88 | 1.9634 |
141
+ | 2.0617 | 9.8366 | 89 | 1.9220 |
142
+ | 2.0617 | 9.9412 | 90 | 1.9669 |
143
+ | 2.0509 | 10.1046 | 91 | 1.9568 |
144
+ | 2.0509 | 10.2092 | 92 | 1.9699 |
145
+ | 2.0509 | 10.3137 | 93 | 2.0316 |
146
+ | 2.0509 | 10.4183 | 94 | 1.9130 |
147
+ | 2.0509 | 10.5229 | 95 | 1.9707 |
148
+ | 2.0509 | 10.6275 | 96 | 1.9624 |
149
+ | 2.0509 | 10.7320 | 97 | 1.9516 |
150
+ | 2.0509 | 10.8366 | 98 | 1.9508 |
151
+ | 2.0509 | 10.9412 | 99 | 1.9166 |
152
+ | 1.9835 | 11.1046 | 100 | 1.9469 |
153
+ | 1.9835 | 11.2092 | 101 | 1.9620 |
154
+ | 1.9835 | 11.3137 | 102 | 1.9470 |
155
+ | 1.9835 | 11.4183 | 103 | 1.9458 |
156
+ | 1.9835 | 11.5229 | 104 | 1.9585 |
157
+ | 1.9835 | 11.6275 | 105 | 1.9451 |
158
+ | 1.9835 | 11.7320 | 106 | 1.9203 |
159
+ | 1.9835 | 11.8366 | 107 | 1.9323 |
160
+ | 1.9835 | 11.9412 | 108 | 1.9641 |
161
+ | 1.9719 | 12.1046 | 109 | 1.9262 |
162
+ | 1.9719 | 12.2092 | 110 | 1.9800 |
163
+ | 1.9719 | 12.3137 | 111 | 1.9422 |
164
+ | 1.9719 | 12.4183 | 112 | 1.9286 |
165
+ | 1.9719 | 12.5229 | 113 | 1.9934 |
166
+ | 1.9719 | 12.6275 | 114 | 1.9704 |
167
+ | 1.9719 | 12.7320 | 115 | 1.9390 |
168
+ | 1.9719 | 12.8366 | 116 | 1.9161 |
169
+ | 1.9719 | 12.9412 | 117 | 1.9483 |
170
+ | 1.9663 | 13.1046 | 118 | 1.9584 |
171
+ | 1.9663 | 13.2092 | 119 | 1.9642 |
172
+ | 1.9663 | 13.3137 | 120 | 1.9447 |
173
+ | 1.9663 | 13.4183 | 121 | 2.0014 |
174
+ | 1.9663 | 13.5229 | 122 | 1.8806 |
175
+ | 1.9663 | 13.6275 | 123 | 1.9487 |
176
+ | 1.9663 | 13.7320 | 124 | 1.9181 |
177
+ | 1.9663 | 13.8366 | 125 | 1.9238 |
178
+ | 1.9663 | 13.9412 | 126 | 1.9514 |
179
+ | 1.9785 | 14.1046 | 127 | 1.9426 |
180
+ | 1.9785 | 14.2092 | 128 | 1.9766 |
181
+ | 1.9785 | 14.3137 | 129 | 1.9118 |
182
+ | 1.9785 | 14.4183 | 130 | 1.9367 |
183
+ | 1.9785 | 14.5229 | 131 | 1.9372 |
184
+ | 1.9785 | 14.6275 | 132 | 1.9232 |
185
+ | 1.9785 | 14.7320 | 133 | 1.9999 |
186
+ | 1.9785 | 14.8366 | 134 | 1.9355 |
187
+ | 1.9785 | 14.9412 | 135 | 1.9657 |
188
+ | 1.9329 | 15.1046 | 136 | 1.9451 |
189
+ | 1.9329 | 15.2092 | 137 | 1.9597 |
190
+ | 1.9329 | 15.3137 | 138 | 1.9180 |
191
+ | 1.9329 | 15.4183 | 139 | 1.9344 |
192
+ | 1.9329 | 15.5229 | 140 | 1.9772 |
193
+ | 1.9329 | 15.6275 | 141 | 1.9797 |
194
+ | 1.9329 | 15.7320 | 142 | 1.9061 |
195
+ | 1.9329 | 15.8366 | 143 | 1.8886 |
196
+ | 1.9329 | 15.9412 | 144 | 1.9685 |
197
+ | 1.9144 | 16.1046 | 145 | 1.9798 |
198
+ | 1.9144 | 16.2092 | 146 | 1.9588 |
199
+ | 1.9144 | 16.3137 | 147 | 1.9274 |
200
+ | 1.9144 | 16.4183 | 148 | 1.9590 |
201
+ | 1.9144 | 16.5229 | 149 | 1.9553 |
202
+ | 1.9144 | 16.6275 | 150 | 1.9143 |
203
+ | 1.9144 | 16.7320 | 151 | 1.9269 |
204
+ | 1.9144 | 16.8366 | 152 | 1.9654 |
205
+ | 1.9144 | 16.9412 | 153 | 1.9789 |
206
+ | 1.9103 | 17.1046 | 154 | 1.9569 |
207
+ | 1.9103 | 17.2092 | 155 | 1.9652 |
208
+ | 1.9103 | 17.3137 | 156 | 1.9810 |
209
+ | 1.9103 | 17.4183 | 157 | 1.9285 |
210
+ | 1.9103 | 17.5229 | 158 | 1.9378 |
211
+ | 1.9103 | 17.6275 | 159 | 1.9520 |
212
+ | 1.9103 | 17.7320 | 160 | 1.9782 |
213
+ | 1.9103 | 17.8366 | 161 | 1.9681 |
214
+ | 1.9103 | 17.9412 | 162 | 1.8926 |
215
+ | 1.887 | 18.1046 | 163 | 1.9334 |
216
+ | 1.887 | 18.2092 | 164 | 1.9252 |
217
+ | 1.887 | 18.3137 | 165 | 1.9399 |
218
+ | 1.887 | 18.4183 | 166 | 1.9518 |
219
+ | 1.887 | 18.5229 | 167 | 1.9924 |
220
+ | 1.887 | 18.6275 | 168 | 1.9054 |
221
+ | 1.887 | 18.7320 | 169 | 1.9480 |
222
+ | 1.887 | 18.8366 | 170 | 1.9308 |
223
+ | 1.887 | 18.9412 | 171 | 1.9343 |
224
+ | 1.8644 | 19.1046 | 172 | 1.9861 |
225
+ | 1.8644 | 19.2092 | 173 | 1.9453 |
226
+ | 1.8644 | 19.3137 | 174 | 1.8999 |
227
+ | 1.8644 | 19.4183 | 175 | 1.9309 |
228
+ | 1.8644 | 19.5229 | 176 | 1.9544 |
229
+ | 1.8644 | 19.6275 | 177 | 1.9436 |
230
+ | 1.8644 | 19.7320 | 178 | 1.9165 |
231
+ | 1.8644 | 19.8366 | 179 | 1.9696 |
232
+ | 1.8644 | 19.9412 | 180 | 1.9248 |
233
+ | 1.8687 | 20.1046 | 181 | 1.9517 |
234
+ | 1.8687 | 20.2092 | 182 | 1.9042 |
235
+ | 1.8687 | 20.3137 | 183 | 1.9925 |
236
+ | 1.8687 | 20.4183 | 184 | 1.8843 |
237
+ | 1.8687 | 20.5229 | 185 | 1.9794 |
238
+ | 1.8687 | 20.6275 | 186 | 1.9789 |
239
+ | 1.8687 | 20.7320 | 187 | 1.9192 |
240
+ | 1.8687 | 20.8366 | 188 | 1.9174 |
241
+ | 1.8687 | 20.9412 | 189 | 1.9568 |
242
+ | 1.8361 | 21.1046 | 190 | 1.9128 |
243
+ | 1.8361 | 21.2092 | 191 | 1.9429 |
244
+ | 1.8361 | 21.3137 | 192 | 1.9558 |
245
+ | 1.8361 | 21.4183 | 193 | 1.9128 |
246
+ | 1.8361 | 21.5229 | 194 | 1.9589 |
247
+ | 1.8361 | 21.6275 | 195 | 1.9745 |
248
+ | 1.8361 | 21.7320 | 196 | 1.9994 |
249
+ | 1.8361 | 21.8366 | 197 | 1.9594 |
250
+ | 1.8361 | 21.9412 | 198 | 1.9064 |
251
+ | 1.8461 | 22.1046 | 199 | 1.9475 |
252
+ | 1.8461 | 22.2092 | 200 | 1.9638 |
253
+ | 1.8461 | 22.3137 | 201 | 1.9351 |
254
+ | 1.8461 | 22.4183 | 202 | 1.9184 |
255
+ | 1.8461 | 22.5229 | 203 | 1.9657 |
256
+ | 1.8461 | 22.6275 | 204 | 1.9109 |
257
+ | 1.8461 | 22.7320 | 205 | 1.9320 |
258
+ | 1.8461 | 22.8366 | 206 | 1.9680 |
259
+ | 1.8461 | 22.9412 | 207 | 1.9629 |
260
+ | 1.8246 | 23.1046 | 208 | 1.9430 |
261
+ | 1.8246 | 23.2092 | 209 | 1.9262 |
262
+ | 1.8246 | 23.3137 | 210 | 1.9615 |
263
+ | 1.8246 | 23.4183 | 211 | 1.9560 |
264
+ | 1.8246 | 23.5229 | 212 | 1.9661 |
265
+ | 1.8246 | 23.6275 | 213 | 1.9781 |
266
+ | 1.8246 | 23.7320 | 214 | 1.9806 |
267
+ | 1.8246 | 23.8366 | 215 | 1.9735 |
268
+ | 1.8246 | 23.9412 | 216 | 1.9583 |
269
+ | 1.8181 | 24.1046 | 217 | 1.9555 |
270
+ | 1.8181 | 24.2092 | 218 | 1.9165 |
271
+ | 1.8181 | 24.3137 | 219 | 1.9638 |
272
+ | 1.8181 | 24.4183 | 220 | 2.0008 |
273
+ | 1.8181 | 24.5229 | 221 | 1.9247 |
274
+ | 1.8181 | 24.6275 | 222 | 1.9720 |
275
+ | 1.8181 | 24.7320 | 223 | 2.0084 |
276
+ | 1.8181 | 24.8366 | 224 | 1.9424 |
277
+ | 1.8181 | 24.9412 | 225 | 1.9111 |
278
+ | 1.797 | 25.1046 | 226 | 1.9787 |
279
+ | 1.797 | 25.2092 | 227 | 1.9613 |
280
+ | 1.797 | 25.3137 | 228 | 1.8806 |
281
+ | 1.797 | 25.4183 | 229 | 1.9231 |
282
+ | 1.797 | 25.5229 | 230 | 1.9022 |
283
+ | 1.797 | 25.6275 | 231 | 1.9683 |
284
+ | 1.797 | 25.7320 | 232 | 1.9825 |
285
+ | 1.797 | 25.8366 | 233 | 1.9629 |
286
+ | 1.797 | 25.9412 | 234 | 1.9116 |
287
+ | 1.7749 | 26.1046 | 235 | 1.9700 |
288
+ | 1.7749 | 26.2092 | 236 | 1.9812 |
289
+ | 1.7749 | 26.3137 | 237 | 1.9249 |
290
+ | 1.7749 | 26.4183 | 238 | 1.9684 |
291
+ | 1.7749 | 26.5229 | 239 | 1.9605 |
292
+ | 1.7749 | 26.6275 | 240 | 1.8918 |
293
+ | 1.7749 | 26.7320 | 241 | 1.9443 |
294
+ | 1.7749 | 26.8366 | 242 | 1.9148 |
295
+ | 1.7749 | 26.9412 | 243 | 1.8974 |
296
+ | 1.8022 | 27.1046 | 244 | 1.9712 |
297
+ | 1.8022 | 27.2092 | 245 | 1.9719 |
298
+ | 1.8022 | 27.3137 | 246 | 1.9540 |
299
+ | 1.8022 | 27.4183 | 247 | 1.8907 |
300
+ | 1.8022 | 27.5229 | 248 | 1.9908 |
301
+ | 1.8022 | 27.6275 | 249 | 1.9274 |
302
+ | 1.8022 | 27.7320 | 250 | 1.9234 |
303
+ | 1.8022 | 27.8366 | 251 | 1.9581 |
304
+ | 1.8022 | 27.9412 | 252 | 1.9409 |
305
+ | 1.7879 | 28.1046 | 253 | 1.8716 |
306
+ | 1.7879 | 28.2092 | 254 | 1.9945 |
307
+ | 1.7879 | 28.3137 | 255 | 1.8658 |
308
+ | 1.7879 | 28.4183 | 256 | 1.9468 |
309
+ | 1.7879 | 28.5229 | 257 | 1.9457 |
310
+ | 1.7879 | 28.6275 | 258 | 1.9555 |
311
+ | 1.7879 | 28.7320 | 259 | 1.9545 |
312
+ | 1.7879 | 28.8366 | 260 | 1.9226 |
313
+ | 1.7879 | 28.9412 | 261 | 1.9331 |
314
+ | 1.8019 | 29.1046 | 262 | 1.9786 |
315
+ | 1.8019 | 29.2092 | 263 | 1.9768 |
316
+ | 1.8019 | 29.3137 | 264 | 1.9601 |
317
+ | 1.8019 | 29.4183 | 265 | 1.9172 |
318
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505
  ### Framework versions
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