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dmusingu
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muk-luganda-digits-classification

Audio Classification
Transformers
Safetensors
wav2vec2
Generated from Trainer
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End of training

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  1. README.md +63 -63
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 2.4964
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- - Accuracy: 0.3667
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  ## Model description
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@@ -38,7 +38,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 1e-05
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  - train_batch_size: 4
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  - eval_batch_size: 1
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  - seed: 42
@@ -51,66 +51,66 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 2.3029 | 1.0 | 60 | 2.3031 | 0.0667 |
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- | 2.3018 | 2.0 | 120 | 2.3056 | 0.0667 |
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- | 2.2994 | 3.0 | 180 | 2.2999 | 0.1333 |
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- | 2.2935 | 4.0 | 240 | 2.2990 | 0.0667 |
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- | 2.287 | 5.0 | 300 | 2.3021 | 0.1 |
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- | 2.2777 | 6.0 | 360 | 2.3070 | 0.1 |
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- | 2.2558 | 7.0 | 420 | 2.3024 | 0.1 |
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- | 2.2326 | 8.0 | 480 | 2.3030 | 0.1 |
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- | 2.1915 | 9.0 | 540 | 2.2621 | 0.2 |
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- | 2.1423 | 10.0 | 600 | 2.2680 | 0.1667 |
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- | 2.079 | 11.0 | 660 | 2.2347 | 0.2333 |
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- | 2.0082 | 12.0 | 720 | 2.2083 | 0.2667 |
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- | 1.9388 | 13.0 | 780 | 2.1809 | 0.2667 |
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- | 1.8631 | 14.0 | 840 | 2.1715 | 0.3667 |
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- | 1.8218 | 15.0 | 900 | 2.1598 | 0.3 |
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- | 1.7112 | 16.0 | 960 | 2.1145 | 0.3333 |
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- | 1.6316 | 17.0 | 1020 | 2.1664 | 0.3 |
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- | 1.5869 | 18.0 | 1080 | 2.1852 | 0.3333 |
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- | 1.5166 | 19.0 | 1140 | 2.2421 | 0.3 |
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- | 1.4676 | 20.0 | 1200 | 2.2286 | 0.2667 |
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- | 1.4119 | 21.0 | 1260 | 2.0431 | 0.3333 |
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- | 1.355 | 22.0 | 1320 | 2.2048 | 0.3 |
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- | 1.2626 | 23.0 | 1380 | 2.0693 | 0.3 |
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- | 1.2237 | 24.0 | 1440 | 2.0888 | 0.3333 |
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- | 1.1686 | 25.0 | 1500 | 2.0231 | 0.4667 |
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- | 1.1277 | 26.0 | 1560 | 1.9774 | 0.4 |
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- | 1.1061 | 27.0 | 1620 | 1.9195 | 0.4 |
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- | 1.0296 | 28.0 | 1680 | 1.9851 | 0.4 |
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- | 0.9938 | 29.0 | 1740 | 1.9041 | 0.4 |
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- | 0.9104 | 30.0 | 1800 | 2.0739 | 0.4 |
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- | 0.8894 | 31.0 | 1860 | 2.0402 | 0.4333 |
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- | 0.8386 | 32.0 | 1920 | 2.0462 | 0.4333 |
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- | 0.7863 | 33.0 | 1980 | 2.0242 | 0.4 |
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- | 0.7464 | 34.0 | 2040 | 1.9713 | 0.4 |
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- | 0.7254 | 35.0 | 2100 | 2.0689 | 0.3667 |
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- | 0.6726 | 36.0 | 2160 | 2.1829 | 0.3333 |
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- | 0.6348 | 37.0 | 2220 | 2.1640 | 0.3333 |
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- | 0.6372 | 38.0 | 2280 | 2.1810 | 0.4 |
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- | 0.6318 | 39.0 | 2340 | 1.9867 | 0.4333 |
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- | 0.5468 | 40.0 | 2400 | 2.1383 | 0.4333 |
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- | 0.5434 | 41.0 | 2460 | 2.1016 | 0.3667 |
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- | 0.5148 | 42.0 | 2520 | 2.2827 | 0.3667 |
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- | 0.4843 | 43.0 | 2580 | 2.0657 | 0.4333 |
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- | 0.457 | 44.0 | 2640 | 2.1263 | 0.4 |
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- | 0.4493 | 45.0 | 2700 | 2.2703 | 0.3667 |
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- | 0.4155 | 46.0 | 2760 | 2.2780 | 0.4 |
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- | 0.4027 | 47.0 | 2820 | 2.2483 | 0.3667 |
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- | 0.4152 | 48.0 | 2880 | 2.2511 | 0.3667 |
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- | 0.3978 | 49.0 | 2940 | 2.3178 | 0.3333 |
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- | 0.3794 | 50.0 | 3000 | 2.3588 | 0.3667 |
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- | 0.3568 | 51.0 | 3060 | 2.4206 | 0.3667 |
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- | 0.3381 | 52.0 | 3120 | 2.4859 | 0.3333 |
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- | 0.3622 | 53.0 | 3180 | 2.4684 | 0.3667 |
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- | 0.376 | 54.0 | 3240 | 2.5034 | 0.3667 |
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- | 0.3348 | 55.0 | 3300 | 2.5368 | 0.3667 |
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- | 0.3438 | 56.0 | 3360 | 2.4634 | 0.4 |
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- | 0.3421 | 57.0 | 3420 | 2.4767 | 0.3667 |
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- | 0.3279 | 58.0 | 3480 | 2.4778 | 0.3333 |
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- | 0.337 | 59.0 | 3540 | 2.4917 | 0.3333 |
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- | 0.3212 | 60.0 | 3600 | 2.4964 | 0.3667 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 4.3197
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+ - Accuracy: 0.4
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 3e-05
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  - train_batch_size: 4
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  - eval_batch_size: 1
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 2.3032 | 1.0 | 60 | 2.2913 | 0.1667 |
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+ | 2.3008 | 2.0 | 120 | 2.2853 | 0.1333 |
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+ | 2.2908 | 3.0 | 180 | 2.2906 | 0.1 |
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+ | 2.2746 | 4.0 | 240 | 2.2676 | 0.2333 |
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+ | 2.227 | 5.0 | 300 | 2.2602 | 0.1333 |
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+ | 2.1679 | 6.0 | 360 | 2.2250 | 0.1333 |
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+ | 2.0793 | 7.0 | 420 | 2.1667 | 0.3 |
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+ | 1.9567 | 8.0 | 480 | 2.3147 | 0.1333 |
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+ | 1.8217 | 9.0 | 540 | 2.0799 | 0.3 |
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+ | 1.6949 | 10.0 | 600 | 2.1671 | 0.2 |
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+ | 1.677 | 11.0 | 660 | 2.1748 | 0.2667 |
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+ | 1.5748 | 12.0 | 720 | 2.1790 | 0.2 |
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+ | 1.4176 | 13.0 | 780 | 2.1468 | 0.2333 |
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+ | 1.2679 | 14.0 | 840 | 2.1294 | 0.3 |
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+ | 1.2619 | 15.0 | 900 | 1.9716 | 0.3667 |
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+ | 1.0977 | 16.0 | 960 | 2.0866 | 0.3 |
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+ | 1.0127 | 17.0 | 1020 | 2.0008 | 0.3333 |
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+ | 0.9106 | 18.0 | 1080 | 2.1988 | 0.3667 |
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+ | 0.8672 | 19.0 | 1140 | 1.9639 | 0.4 |
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+ | 0.7688 | 20.0 | 1200 | 2.1911 | 0.3 |
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+ | 0.6587 | 21.0 | 1260 | 2.2897 | 0.4 |
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+ | 0.5866 | 22.0 | 1320 | 2.5786 | 0.3333 |
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+ | 0.5267 | 23.0 | 1380 | 2.4252 | 0.3667 |
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+ | 0.5111 | 24.0 | 1440 | 2.6801 | 0.3667 |
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+ | 0.4246 | 25.0 | 1500 | 2.9816 | 0.3333 |
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+ | 0.476 | 26.0 | 1560 | 3.2478 | 0.3 |
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+ | 0.4169 | 27.0 | 1620 | 3.3604 | 0.3333 |
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+ | 0.3443 | 28.0 | 1680 | 3.5810 | 0.3333 |
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+ | 0.3004 | 29.0 | 1740 | 3.2561 | 0.4 |
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+ | 0.2123 | 30.0 | 1800 | 2.9655 | 0.5 |
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+ | 0.2302 | 31.0 | 1860 | 3.5154 | 0.4 |
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+ | 0.3316 | 32.0 | 1920 | 3.6515 | 0.3667 |
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+ | 0.1991 | 33.0 | 1980 | 3.5827 | 0.4333 |
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+ | 0.236 | 34.0 | 2040 | 3.5531 | 0.4 |
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+ | 0.2409 | 35.0 | 2100 | 3.4890 | 0.4333 |
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+ | 0.2284 | 36.0 | 2160 | 3.6660 | 0.4667 |
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+ | 0.2485 | 37.0 | 2220 | 4.2194 | 0.3667 |
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+ | 0.2069 | 38.0 | 2280 | 4.2314 | 0.3667 |
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+ | 0.2054 | 39.0 | 2340 | 4.0748 | 0.4 |
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+ | 0.1547 | 40.0 | 2400 | 4.1912 | 0.3667 |
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+ | 0.2477 | 41.0 | 2460 | 4.5107 | 0.3 |
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+ | 0.1631 | 42.0 | 2520 | 4.4653 | 0.3 |
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+ | 0.1864 | 43.0 | 2580 | 4.4574 | 0.3333 |
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+ | 0.1747 | 44.0 | 2640 | 4.4162 | 0.4 |
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+ | 0.168 | 45.0 | 2700 | 4.4537 | 0.3333 |
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+ | 0.1869 | 46.0 | 2760 | 4.1755 | 0.4 |
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+ | 0.149 | 47.0 | 2820 | 4.3228 | 0.3667 |
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+ | 0.2153 | 48.0 | 2880 | 4.6288 | 0.3667 |
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+ | 0.2022 | 49.0 | 2940 | 4.3906 | 0.3667 |
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+ | 0.1711 | 50.0 | 3000 | 4.4324 | 0.3333 |
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+ | 0.1527 | 51.0 | 3060 | 4.3020 | 0.3667 |
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+ | 0.1597 | 52.0 | 3120 | 4.4839 | 0.3667 |
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+ | 0.1717 | 53.0 | 3180 | 4.6492 | 0.3333 |
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+ | 0.2392 | 54.0 | 3240 | 4.6018 | 0.3667 |
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+ | 0.1743 | 55.0 | 3300 | 4.4345 | 0.3667 |
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+ | 0.1432 | 56.0 | 3360 | 4.3939 | 0.3667 |
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+ | 0.1834 | 57.0 | 3420 | 4.3642 | 0.4 |
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+ | 0.1457 | 58.0 | 3480 | 4.3267 | 0.4 |
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+ | 0.1335 | 59.0 | 3540 | 4.3221 | 0.4 |
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+ | 0.1305 | 60.0 | 3600 | 4.3197 | 0.4 |
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  ### Framework versions
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