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UNetOscillatoryNeuron

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Safetensors
UNetOscillatoryNeuron
Generated from Trainer
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  1. README.md +61 -53
  2. model.safetensors +1 -1
README.md CHANGED
@@ -2,6 +2,9 @@
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  library_name: transformers
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  tags:
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  - generated_from_trainer
 
 
 
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  model-index:
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  - name: UNetOscillatoryNeuron
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  results: []
@@ -14,7 +17,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0257
 
 
 
 
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  ## Model description
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@@ -39,62 +46,63 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine
 
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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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- | 0.7184 | 1.0 | 27 | 0.2405 |
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- | 0.1433 | 2.0 | 54 | 0.1415 |
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- | 0.0714 | 3.0 | 81 | 0.0670 |
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- | 0.0523 | 4.0 | 108 | 0.0728 |
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- | 0.0421 | 5.0 | 135 | 0.0372 |
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- | 0.0388 | 6.0 | 162 | 0.0575 |
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- | 0.0336 | 7.0 | 189 | 0.0436 |
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- | 0.0303 | 8.0 | 216 | 0.0395 |
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- | 0.0287 | 9.0 | 243 | 0.0378 |
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- | 0.0264 | 10.0 | 270 | 0.0335 |
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- | 0.0252 | 11.0 | 297 | 0.0367 |
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- | 0.0241 | 12.0 | 324 | 0.0267 |
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- | 0.0247 | 13.0 | 351 | 0.0350 |
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- | 0.0241 | 14.0 | 378 | 0.0296 |
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- | 0.0238 | 15.0 | 405 | 0.0262 |
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- | 0.0217 | 16.0 | 432 | 0.0247 |
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- | 0.0225 | 17.0 | 459 | 0.0287 |
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- | 0.0201 | 18.0 | 486 | 0.0516 |
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- | 0.0193 | 19.0 | 513 | 0.0482 |
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- | 0.0186 | 20.0 | 540 | 0.0254 |
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- | 0.0193 | 21.0 | 567 | 0.0495 |
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- | 0.0179 | 22.0 | 594 | 0.0360 |
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- | 0.0173 | 23.0 | 621 | 0.0282 |
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- | 0.0168 | 24.0 | 648 | 0.0311 |
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- | 0.0162 | 25.0 | 675 | 0.0460 |
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- | 0.0163 | 26.0 | 702 | 0.0351 |
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- | 0.0158 | 27.0 | 729 | 0.0327 |
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- | 0.0153 | 28.0 | 756 | 0.0283 |
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- | 0.015 | 29.0 | 783 | 0.0319 |
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- | 0.0145 | 30.0 | 810 | 0.0343 |
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- | 0.0142 | 31.0 | 837 | 0.0404 |
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- | 0.014 | 32.0 | 864 | 0.0361 |
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- | 0.0139 | 33.0 | 891 | 0.0359 |
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- | 0.0139 | 34.0 | 918 | 0.0307 |
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- | 0.0135 | 35.0 | 945 | 0.0319 |
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- | 0.0131 | 36.0 | 972 | 0.0294 |
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- | 0.0129 | 37.0 | 999 | 0.0282 |
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- | 0.0127 | 38.0 | 1026 | 0.0291 |
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- | 0.0126 | 39.0 | 1053 | 0.0283 |
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- | 0.0124 | 40.0 | 1080 | 0.0296 |
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- | 0.0122 | 41.0 | 1107 | 0.0290 |
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- | 0.0122 | 42.0 | 1134 | 0.0266 |
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- | 0.0121 | 43.0 | 1161 | 0.0288 |
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- | 0.0119 | 44.0 | 1188 | 0.0262 |
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- | 0.0118 | 45.0 | 1215 | 0.0255 |
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- | 0.0118 | 46.0 | 1242 | 0.0253 |
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- | 0.0117 | 47.0 | 1269 | 0.0259 |
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- | 0.0117 | 48.0 | 1296 | 0.0252 |
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- | 0.0117 | 49.0 | 1323 | 0.0259 |
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- | 0.0116 | 50.0 | 1350 | 0.0257 |
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  ### Framework versions
 
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  library_name: transformers
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  tags:
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  - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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  model-index:
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  - name: UNetOscillatoryNeuron
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  results: []
 
17
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0221
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+ - Dice: 0.7035
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+ - Iou: 0.5515
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+ - Precision: 0.9921
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+ - Recall: 0.5538
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  ## Model description
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  - seed: 42
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.05
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  - num_epochs: 50
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Dice | Iou | Precision | Recall |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
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+ | 1.0549 | 1.0 | 27 | 1.3770 | 0.4525 | 0.2943 | 0.3000 | 0.9615 |
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+ | 0.4559 | 2.0 | 54 | 0.2323 | 0.2876 | 0.1730 | 0.9697 | 0.1739 |
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+ | 0.1153 | 3.0 | 81 | 0.0996 | 0.7487 | 0.6070 | 0.9158 | 0.6461 |
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+ | 0.0563 | 4.0 | 108 | 0.1447 | 0.7639 | 0.6262 | 0.8899 | 0.6814 |
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+ | 0.0436 | 5.0 | 135 | 0.0435 | 0.7086 | 0.5582 | 0.9768 | 0.5663 |
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+ | 0.0403 | 6.0 | 162 | 0.0817 | 0.7517 | 0.6101 | 0.9339 | 0.6371 |
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+ | 0.035 | 7.0 | 189 | 0.0623 | 0.7451 | 0.6023 | 0.9483 | 0.6228 |
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+ | 0.0315 | 8.0 | 216 | 0.0435 | 0.7371 | 0.5927 | 0.9679 | 0.6041 |
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+ | 0.031 | 9.0 | 243 | 0.0361 | 0.7202 | 0.5728 | 0.9788 | 0.5807 |
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+ | 0.0284 | 10.0 | 270 | 0.0285 | 0.7198 | 0.5714 | 0.9848 | 0.5763 |
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+ | 0.0262 | 11.0 | 297 | 0.0322 | 0.7256 | 0.5785 | 0.9794 | 0.5855 |
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+ | 0.0252 | 12.0 | 324 | 0.0286 | 0.7161 | 0.5666 | 0.9850 | 0.5713 |
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+ | 0.0247 | 13.0 | 351 | 0.0600 | 0.7440 | 0.6010 | 0.9533 | 0.6196 |
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+ | 0.0247 | 14.0 | 378 | 0.0412 | 0.7338 | 0.5883 | 0.9690 | 0.5996 |
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+ | 0.0258 | 15.0 | 405 | 0.0287 | 0.7198 | 0.5714 | 0.9825 | 0.5774 |
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+ | 0.0228 | 16.0 | 432 | 0.0278 | 0.7178 | 0.5686 | 0.9820 | 0.5749 |
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+ | 0.0226 | 17.0 | 459 | 0.0250 | 0.7166 | 0.5673 | 0.9847 | 0.5725 |
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+ | 0.0218 | 18.0 | 486 | 0.0436 | 0.7355 | 0.5905 | 0.9675 | 0.6027 |
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+ | 0.0204 | 19.0 | 513 | 0.0631 | 0.7476 | 0.6054 | 0.9512 | 0.6244 |
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+ | 0.0194 | 20.0 | 540 | 0.0268 | 0.7222 | 0.5736 | 0.9833 | 0.5788 |
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+ | 0.0203 | 21.0 | 567 | 0.0323 | 0.7275 | 0.5806 | 0.9768 | 0.5885 |
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+ | 0.0201 | 22.0 | 594 | 0.0337 | 0.7303 | 0.5839 | 0.9765 | 0.5920 |
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+ | 0.0188 | 23.0 | 621 | 0.0314 | 0.7282 | 0.5811 | 0.9790 | 0.5879 |
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+ | 0.0177 | 24.0 | 648 | 0.0263 | 0.7235 | 0.5756 | 0.9847 | 0.5802 |
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+ | 0.018 | 25.0 | 675 | 0.0265 | 0.7225 | 0.5742 | 0.9845 | 0.5788 |
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+ | 0.018 | 26.0 | 702 | 0.0238 | 0.7179 | 0.5690 | 0.9882 | 0.5726 |
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+ | 0.0174 | 27.0 | 729 | 0.0243 | 0.7175 | 0.5679 | 0.9873 | 0.5716 |
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+ | 0.0174 | 28.0 | 756 | 0.0214 | 0.7093 | 0.5590 | 0.9913 | 0.5617 |
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+ | 0.017 | 29.0 | 783 | 0.0220 | 0.7074 | 0.5558 | 0.9918 | 0.5581 |
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+ | 0.0162 | 30.0 | 810 | 0.0277 | 0.7237 | 0.5756 | 0.9833 | 0.5808 |
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+ | 0.0154 | 31.0 | 837 | 0.0303 | 0.7278 | 0.5806 | 0.9809 | 0.5866 |
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+ | 0.0152 | 32.0 | 864 | 0.0238 | 0.7160 | 0.5663 | 0.9875 | 0.5701 |
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+ | 0.015 | 33.0 | 891 | 0.0242 | 0.7174 | 0.5677 | 0.9873 | 0.5714 |
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+ | 0.0149 | 34.0 | 918 | 0.0253 | 0.7205 | 0.5718 | 0.9859 | 0.5761 |
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+ | 0.0146 | 35.0 | 945 | 0.0235 | 0.7154 | 0.5655 | 0.9879 | 0.5691 |
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+ | 0.0142 | 36.0 | 972 | 0.0225 | 0.7110 | 0.5601 | 0.9901 | 0.5629 |
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+ | 0.014 | 37.0 | 999 | 0.0222 | 0.7087 | 0.5575 | 0.9907 | 0.5602 |
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+ | 0.0137 | 38.0 | 1026 | 0.0232 | 0.7103 | 0.5594 | 0.9895 | 0.5626 |
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+ | 0.0137 | 39.0 | 1053 | 0.0227 | 0.7117 | 0.5611 | 0.9893 | 0.5643 |
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+ | 0.0134 | 40.0 | 1080 | 0.0220 | 0.7043 | 0.5524 | 0.9923 | 0.5546 |
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+ | 0.0133 | 41.0 | 1107 | 0.0226 | 0.7085 | 0.5574 | 0.9904 | 0.5602 |
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+ | 0.0132 | 42.0 | 1134 | 0.0229 | 0.7091 | 0.5582 | 0.9899 | 0.5612 |
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+ | 0.0132 | 43.0 | 1161 | 0.0220 | 0.7039 | 0.5520 | 0.9921 | 0.5542 |
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+ | 0.013 | 44.0 | 1188 | 0.0225 | 0.7046 | 0.5528 | 0.9916 | 0.5552 |
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+ | 0.0129 | 45.0 | 1215 | 0.0222 | 0.7058 | 0.5542 | 0.9915 | 0.5566 |
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+ | 0.0129 | 46.0 | 1242 | 0.0226 | 0.7036 | 0.5515 | 0.9913 | 0.5540 |
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+ | 0.0128 | 47.0 | 1269 | 0.0219 | 0.7031 | 0.5511 | 0.9924 | 0.5533 |
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+ | 0.0129 | 48.0 | 1296 | 0.0222 | 0.7035 | 0.5515 | 0.9922 | 0.5538 |
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+ | 0.0127 | 49.0 | 1323 | 0.0224 | 0.7048 | 0.5531 | 0.9912 | 0.5557 |
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+ | 0.0126 | 50.0 | 1350 | 0.0221 | 0.7035 | 0.5515 | 0.9921 | 0.5538 |
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  ### Framework versions
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