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camembert_ccnet_classification_tools_classifier-only_fr-p0.2

Text Classification
Transformers
PyTorch
camembert
Generated from Trainer
Inference Endpoints
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  1. README.md +62 -62
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -16,8 +16,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [camembert/camembert-base-ccnet](https://huggingface.co/camembert/camembert-base-ccnet) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1673
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- - Accuracy: 0.95
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  - Learning Rate: 0.0
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  ## Model description
@@ -49,66 +49,66 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Rate |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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- | No log | 1.0 | 7 | 0.4658 | 0.825 | 0.0010 |
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- | No log | 2.0 | 14 | 0.3444 | 0.95 | 0.0010 |
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- | No log | 3.0 | 21 | 0.2803 | 0.925 | 0.0009 |
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- | No log | 4.0 | 28 | 0.3995 | 0.825 | 0.0009 |
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- | No log | 5.0 | 35 | 0.2299 | 0.95 | 0.0009 |
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- | No log | 6.0 | 42 | 0.3046 | 0.925 | 0.0009 |
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- | No log | 7.0 | 49 | 0.4598 | 0.8 | 0.0009 |
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- | No log | 8.0 | 56 | 0.2019 | 0.95 | 0.0009 |
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- | No log | 9.0 | 63 | 0.2067 | 0.925 | 0.0008 |
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- | No log | 10.0 | 70 | 0.3652 | 0.9 | 0.0008 |
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- | No log | 11.0 | 77 | 0.2074 | 0.925 | 0.0008 |
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- | No log | 12.0 | 84 | 0.3108 | 0.875 | 0.0008 |
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- | No log | 13.0 | 91 | 0.2461 | 0.975 | 0.0008 |
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- | No log | 14.0 | 98 | 0.2046 | 0.975 | 0.0008 |
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- | No log | 15.0 | 105 | 0.3392 | 0.85 | 0.0008 |
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- | No log | 16.0 | 112 | 0.2231 | 0.95 | 0.0007 |
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- | No log | 17.0 | 119 | 0.3282 | 0.9 | 0.0007 |
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- | No log | 18.0 | 126 | 0.2064 | 0.975 | 0.0007 |
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- | No log | 19.0 | 133 | 0.2215 | 0.925 | 0.0007 |
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- | No log | 20.0 | 140 | 0.2380 | 0.9 | 0.0007 |
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- | No log | 21.0 | 147 | 0.1949 | 0.975 | 0.0007 |
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- | No log | 22.0 | 154 | 0.1659 | 0.95 | 0.0006 |
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- | No log | 23.0 | 161 | 0.2391 | 0.9 | 0.0006 |
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- | No log | 24.0 | 168 | 0.2423 | 0.95 | 0.0006 |
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- | No log | 25.0 | 175 | 0.2612 | 0.9 | 0.0006 |
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- | No log | 26.0 | 182 | 0.2852 | 0.875 | 0.0006 |
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- | No log | 27.0 | 189 | 0.2253 | 0.95 | 0.0006 |
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- | No log | 28.0 | 196 | 0.2657 | 0.9 | 0.0005 |
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- | No log | 29.0 | 203 | 0.1879 | 0.95 | 0.0005 |
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- | No log | 30.0 | 210 | 0.1927 | 0.95 | 0.0005 |
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- | No log | 31.0 | 217 | 0.2760 | 0.9 | 0.0005 |
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- | No log | 32.0 | 224 | 0.2340 | 0.975 | 0.0005 |
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- | No log | 33.0 | 231 | 0.1929 | 0.95 | 0.0005 |
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- | No log | 34.0 | 238 | 0.1898 | 0.925 | 0.0004 |
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- | No log | 35.0 | 245 | 0.1868 | 0.975 | 0.0004 |
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- | No log | 36.0 | 252 | 0.1988 | 0.95 | 0.0004 |
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- | No log | 37.0 | 259 | 0.2276 | 0.9 | 0.0004 |
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- | No log | 38.0 | 266 | 0.1873 | 0.925 | 0.0004 |
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- | No log | 39.0 | 273 | 0.1512 | 0.975 | 0.0003 |
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- | No log | 40.0 | 280 | 0.1580 | 0.975 | 0.0003 |
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- | No log | 41.0 | 287 | 0.1751 | 0.95 | 0.0003 |
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- | No log | 42.0 | 294 | 0.2039 | 0.925 | 0.0003 |
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- | No log | 43.0 | 301 | 0.2150 | 0.9 | 0.0003 |
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- | No log | 44.0 | 308 | 0.1601 | 0.975 | 0.0003 |
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- | No log | 45.0 | 315 | 0.1538 | 0.975 | 0.0003 |
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- | No log | 46.0 | 322 | 0.1678 | 0.975 | 0.0002 |
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- | No log | 47.0 | 329 | 0.1763 | 0.95 | 0.0002 |
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- | No log | 48.0 | 336 | 0.1952 | 0.95 | 0.0002 |
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- | No log | 49.0 | 343 | 0.1751 | 0.95 | 0.0002 |
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- | No log | 50.0 | 350 | 0.1659 | 0.975 | 0.0002 |
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- | No log | 51.0 | 357 | 0.1716 | 0.975 | 0.0001 |
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- | No log | 52.0 | 364 | 0.1912 | 0.975 | 0.0001 |
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- | No log | 53.0 | 371 | 0.1950 | 0.95 | 0.0001 |
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- | No log | 54.0 | 378 | 0.2143 | 0.925 | 0.0001 |
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- | No log | 55.0 | 385 | 0.2027 | 0.925 | 0.0001 |
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- | No log | 56.0 | 392 | 0.1877 | 0.925 | 0.0001 |
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- | No log | 57.0 | 399 | 0.1811 | 0.95 | 5e-05 |
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- | No log | 58.0 | 406 | 0.1748 | 0.95 | 0.0000 |
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- | No log | 59.0 | 413 | 0.1677 | 0.95 | 0.0000 |
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- | No log | 60.0 | 420 | 0.1673 | 0.95 | 0.0 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [camembert/camembert-base-ccnet](https://huggingface.co/camembert/camembert-base-ccnet) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2525
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+ - Accuracy: 0.975
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  - Learning Rate: 0.0
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  ## Model description
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Rate |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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+ | No log | 1.0 | 7 | 1.8405 | 0.3 | 0.0010 |
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+ | No log | 2.0 | 14 | 1.5880 | 0.425 | 0.0010 |
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+ | No log | 3.0 | 21 | 1.2827 | 0.725 | 0.0009 |
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+ | No log | 4.0 | 28 | 1.1343 | 0.7 | 0.0009 |
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+ | No log | 5.0 | 35 | 1.0062 | 0.7 | 0.0009 |
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+ | No log | 6.0 | 42 | 0.8774 | 0.75 | 0.0009 |
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+ | No log | 7.0 | 49 | 0.8032 | 0.75 | 0.0009 |
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+ | No log | 8.0 | 56 | 0.7309 | 0.8 | 0.0009 |
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+ | No log | 9.0 | 63 | 0.6953 | 0.8 | 0.0008 |
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+ | No log | 10.0 | 70 | 0.6711 | 0.725 | 0.0008 |
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+ | No log | 11.0 | 77 | 0.5830 | 0.9 | 0.0008 |
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+ | No log | 12.0 | 84 | 0.6111 | 0.775 | 0.0008 |
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+ | No log | 13.0 | 91 | 0.6019 | 0.8 | 0.0008 |
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+ | No log | 14.0 | 98 | 0.4941 | 0.9 | 0.0008 |
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+ | No log | 15.0 | 105 | 0.4901 | 0.875 | 0.0008 |
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+ | No log | 16.0 | 112 | 0.4450 | 0.9 | 0.0007 |
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+ | No log | 17.0 | 119 | 0.5169 | 0.775 | 0.0007 |
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+ | No log | 18.0 | 126 | 0.4281 | 0.9 | 0.0007 |
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+ | No log | 19.0 | 133 | 0.4314 | 0.875 | 0.0007 |
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+ | No log | 20.0 | 140 | 0.4408 | 0.85 | 0.0007 |
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+ | No log | 21.0 | 147 | 0.3775 | 0.825 | 0.0007 |
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+ | No log | 22.0 | 154 | 0.3641 | 0.875 | 0.0006 |
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+ | No log | 23.0 | 161 | 0.3698 | 0.925 | 0.0006 |
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+ | No log | 24.0 | 168 | 0.3470 | 0.925 | 0.0006 |
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+ | No log | 25.0 | 175 | 0.3649 | 0.9 | 0.0006 |
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+ | No log | 26.0 | 182 | 0.3400 | 0.95 | 0.0006 |
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+ | No log | 27.0 | 189 | 0.3451 | 0.925 | 0.0006 |
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+ | No log | 28.0 | 196 | 0.3841 | 0.875 | 0.0005 |
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+ | No log | 29.0 | 203 | 0.3141 | 0.95 | 0.0005 |
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+ | No log | 30.0 | 210 | 0.3150 | 0.95 | 0.0005 |
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+ | No log | 31.0 | 217 | 0.3493 | 0.9 | 0.0005 |
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+ | No log | 32.0 | 224 | 0.3115 | 0.95 | 0.0005 |
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+ | No log | 33.0 | 231 | 0.3133 | 0.95 | 0.0005 |
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+ | No log | 34.0 | 238 | 0.3169 | 0.925 | 0.0004 |
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+ | No log | 35.0 | 245 | 0.3054 | 0.95 | 0.0004 |
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+ | No log | 36.0 | 252 | 0.2951 | 0.975 | 0.0004 |
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+ | No log | 37.0 | 259 | 0.3018 | 0.9 | 0.0004 |
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+ | No log | 38.0 | 266 | 0.2918 | 0.9 | 0.0004 |
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+ | No log | 39.0 | 273 | 0.2817 | 0.95 | 0.0003 |
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+ | No log | 40.0 | 280 | 0.2723 | 0.95 | 0.0003 |
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+ | No log | 41.0 | 287 | 0.2618 | 0.95 | 0.0003 |
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+ | No log | 42.0 | 294 | 0.2779 | 0.95 | 0.0003 |
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+ | No log | 43.0 | 301 | 0.2806 | 0.95 | 0.0003 |
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+ | No log | 44.0 | 308 | 0.2560 | 0.95 | 0.0003 |
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+ | No log | 45.0 | 315 | 0.2566 | 0.95 | 0.0003 |
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+ | No log | 46.0 | 322 | 0.2543 | 0.95 | 0.0002 |
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+ | No log | 47.0 | 329 | 0.2784 | 0.975 | 0.0002 |
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+ | No log | 48.0 | 336 | 0.2974 | 0.925 | 0.0002 |
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+ | No log | 49.0 | 343 | 0.2755 | 0.975 | 0.0002 |
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+ | No log | 50.0 | 350 | 0.2532 | 0.95 | 0.0002 |
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+ | No log | 51.0 | 357 | 0.2495 | 0.95 | 0.0001 |
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+ | No log | 52.0 | 364 | 0.2700 | 0.95 | 0.0001 |
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+ | No log | 53.0 | 371 | 0.2808 | 0.95 | 0.0001 |
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+ | No log | 54.0 | 378 | 0.2848 | 0.975 | 0.0001 |
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+ | No log | 55.0 | 385 | 0.2728 | 0.975 | 0.0001 |
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+ | No log | 56.0 | 392 | 0.2646 | 0.975 | 0.0001 |
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+ | No log | 57.0 | 399 | 0.2592 | 0.975 | 5e-05 |
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+ | No log | 58.0 | 406 | 0.2561 | 0.975 | 0.0000 |
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+ | No log | 59.0 | 413 | 0.2525 | 0.975 | 0.0000 |
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+ | No log | 60.0 | 420 | 0.2525 | 0.975 | 0.0 |
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  ### Framework versions
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