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hubert-classifier-aug-fold-1

Audio Classification
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hubert
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 Metrics Community
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  1. README.md +109 -80
  2. model.safetensors +1 -1
  3. runs/Jul25_21-00-30_LAPTOP-1GID9RGH/events.out.tfevents.1721916031.LAPTOP-1GID9RGH.18228.2 +2 -2
  4. runs/Jul25_21-00-30_LAPTOP-1GID9RGH/events.out.tfevents.1721918927.LAPTOP-1GID9RGH.18228.3 +3 -0
README.md CHANGED
@@ -20,12 +20,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5514
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- - Accuracy: 0.8747
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- - Precision: 0.8876
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- - Recall: 0.8747
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- - F1: 0.8740
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- - Binary: 0.9124
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  ## Model description
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@@ -60,80 +60,109 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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- | No log | 0.13 | 50 | 4.4207 | 0.0216 | 0.0078 | 0.0216 | 0.0085 | 0.1831 |
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- | No log | 0.27 | 100 | 4.3169 | 0.0351 | 0.0029 | 0.0351 | 0.0050 | 0.2505 |
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- | No log | 0.4 | 150 | 3.9821 | 0.0499 | 0.0044 | 0.0499 | 0.0076 | 0.3290 |
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- | No log | 0.54 | 200 | 3.6532 | 0.0742 | 0.0158 | 0.0742 | 0.0197 | 0.3479 |
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- | No log | 0.67 | 250 | 3.3872 | 0.0945 | 0.0193 | 0.0945 | 0.0285 | 0.3618 |
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- | No log | 0.81 | 300 | 3.1281 | 0.1781 | 0.1193 | 0.1781 | 0.1031 | 0.4216 |
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- | No log | 0.94 | 350 | 2.8421 | 0.2267 | 0.1493 | 0.2267 | 0.1418 | 0.4568 |
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- | 3.831 | 1.08 | 400 | 2.5780 | 0.3239 | 0.2944 | 0.3239 | 0.2544 | 0.5252 |
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- | 3.831 | 1.21 | 450 | 2.2529 | 0.4291 | 0.3508 | 0.4291 | 0.3436 | 0.5999 |
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- | 3.831 | 1.35 | 500 | 1.9409 | 0.5007 | 0.4489 | 0.5007 | 0.4299 | 0.6483 |
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- | 3.831 | 1.48 | 550 | 1.7221 | 0.5493 | 0.5313 | 0.5493 | 0.4903 | 0.6858 |
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- | 3.831 | 1.62 | 600 | 1.4802 | 0.6140 | 0.5899 | 0.6140 | 0.5629 | 0.7291 |
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- | 3.831 | 1.75 | 650 | 1.3410 | 0.6370 | 0.6373 | 0.6370 | 0.6061 | 0.7452 |
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- | 3.831 | 1.89 | 700 | 1.1647 | 0.7045 | 0.7115 | 0.7045 | 0.6815 | 0.7926 |
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- | 2.0299 | 2.02 | 750 | 1.0363 | 0.7287 | 0.7383 | 0.7287 | 0.7099 | 0.8100 |
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- | 2.0299 | 2.16 | 800 | 1.0080 | 0.7287 | 0.7422 | 0.7287 | 0.7109 | 0.8088 |
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- | 2.0299 | 2.29 | 850 | 0.9056 | 0.7557 | 0.7784 | 0.7557 | 0.7447 | 0.8283 |
80
- | 2.0299 | 2.43 | 900 | 0.8888 | 0.7625 | 0.7796 | 0.7625 | 0.7504 | 0.8333 |
81
- | 2.0299 | 2.56 | 950 | 0.8281 | 0.7935 | 0.8155 | 0.7935 | 0.7860 | 0.8559 |
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- | 2.0299 | 2.7 | 1000 | 0.7762 | 0.7976 | 0.8238 | 0.7976 | 0.7887 | 0.8596 |
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- | 2.0299 | 2.83 | 1050 | 0.7081 | 0.8178 | 0.8378 | 0.8178 | 0.8110 | 0.8725 |
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- | 2.0299 | 2.96 | 1100 | 0.7421 | 0.8124 | 0.8311 | 0.8124 | 0.8064 | 0.8692 |
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- | 1.081 | 3.1 | 1150 | 0.6977 | 0.8219 | 0.8429 | 0.8219 | 0.8172 | 0.8746 |
86
- | 1.081 | 3.23 | 1200 | 0.7126 | 0.8273 | 0.8521 | 0.8273 | 0.8224 | 0.8785 |
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- | 1.081 | 3.37 | 1250 | 0.7751 | 0.8030 | 0.8319 | 0.8030 | 0.7945 | 0.8617 |
88
- | 1.081 | 3.5 | 1300 | 0.6865 | 0.8313 | 0.8537 | 0.8313 | 0.8300 | 0.8827 |
89
- | 1.081 | 3.64 | 1350 | 0.6652 | 0.8367 | 0.8647 | 0.8367 | 0.8347 | 0.8860 |
90
- | 1.081 | 3.77 | 1400 | 0.6792 | 0.8367 | 0.8564 | 0.8367 | 0.8338 | 0.8839 |
91
- | 1.081 | 3.91 | 1450 | 0.6332 | 0.8448 | 0.8667 | 0.8448 | 0.8416 | 0.8904 |
92
- | 0.746 | 4.04 | 1500 | 0.6558 | 0.8367 | 0.8615 | 0.8367 | 0.8300 | 0.8856 |
93
- | 0.746 | 4.18 | 1550 | 0.5993 | 0.8543 | 0.8651 | 0.8543 | 0.8510 | 0.8978 |
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- | 0.746 | 4.31 | 1600 | 0.5672 | 0.8637 | 0.8848 | 0.8637 | 0.8613 | 0.9031 |
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- | 0.746 | 4.45 | 1650 | 0.5884 | 0.8529 | 0.8675 | 0.8529 | 0.8482 | 0.8973 |
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- | 0.746 | 4.58 | 1700 | 0.6330 | 0.8596 | 0.8753 | 0.8596 | 0.8573 | 0.9016 |
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- | 0.746 | 4.72 | 1750 | 0.5803 | 0.8516 | 0.8638 | 0.8516 | 0.8474 | 0.8958 |
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- | 0.746 | 4.85 | 1800 | 0.5519 | 0.8677 | 0.8844 | 0.8677 | 0.8667 | 0.9077 |
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- | 0.746 | 4.99 | 1850 | 0.5844 | 0.8583 | 0.8728 | 0.8583 | 0.8558 | 0.9000 |
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- | 0.5764 | 5.12 | 1900 | 0.6185 | 0.8650 | 0.8822 | 0.8650 | 0.8619 | 0.9047 |
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- | 0.5764 | 5.26 | 1950 | 0.5854 | 0.8623 | 0.8806 | 0.8623 | 0.8574 | 0.9036 |
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- | 0.5764 | 5.39 | 2000 | 0.6412 | 0.8596 | 0.8689 | 0.8596 | 0.8564 | 0.9023 |
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- | 0.5764 | 5.53 | 2050 | 0.5703 | 0.8691 | 0.8769 | 0.8691 | 0.8665 | 0.9089 |
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- | 0.5764 | 5.66 | 2100 | 0.5887 | 0.8610 | 0.8752 | 0.8610 | 0.8595 | 0.9023 |
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- | 0.5764 | 5.8 | 2150 | 0.6082 | 0.8623 | 0.8799 | 0.8623 | 0.8597 | 0.9028 |
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- | 0.5764 | 5.93 | 2200 | 0.6345 | 0.8677 | 0.8864 | 0.8677 | 0.8648 | 0.9070 |
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- | 0.4819 | 6.06 | 2250 | 0.5905 | 0.8664 | 0.8821 | 0.8664 | 0.8635 | 0.9049 |
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- | 0.4819 | 6.2 | 2300 | 0.5426 | 0.8731 | 0.8905 | 0.8731 | 0.8724 | 0.9115 |
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- | 0.4819 | 6.33 | 2350 | 0.5850 | 0.8826 | 0.8944 | 0.8826 | 0.8791 | 0.9170 |
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- | 0.4819 | 6.47 | 2400 | 0.5693 | 0.8745 | 0.8846 | 0.8745 | 0.8717 | 0.9119 |
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- | 0.4819 | 6.6 | 2450 | 0.5829 | 0.8745 | 0.8863 | 0.8745 | 0.8698 | 0.9123 |
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- | 0.4819 | 6.74 | 2500 | 0.6471 | 0.8664 | 0.8834 | 0.8664 | 0.8640 | 0.9063 |
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- | 0.4819 | 6.87 | 2550 | 0.5897 | 0.8799 | 0.8893 | 0.8799 | 0.8771 | 0.9157 |
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- | 0.4333 | 7.01 | 2600 | 0.5985 | 0.8772 | 0.8921 | 0.8772 | 0.8755 | 0.9132 |
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- | 0.4333 | 7.14 | 2650 | 0.5714 | 0.8758 | 0.8930 | 0.8758 | 0.8742 | 0.9127 |
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- | 0.4333 | 7.28 | 2700 | 0.6447 | 0.8799 | 0.8949 | 0.8799 | 0.8779 | 0.9159 |
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- | 0.4333 | 7.41 | 2750 | 0.6539 | 0.8650 | 0.8815 | 0.8650 | 0.8642 | 0.9062 |
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- | 0.4333 | 7.55 | 2800 | 0.6506 | 0.8610 | 0.8737 | 0.8610 | 0.8590 | 0.9035 |
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- | 0.4333 | 7.68 | 2850 | 0.5909 | 0.8718 | 0.8874 | 0.8718 | 0.8703 | 0.9096 |
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- | 0.4333 | 7.82 | 2900 | 0.5561 | 0.8826 | 0.8960 | 0.8826 | 0.8802 | 0.9175 |
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- | 0.4333 | 7.95 | 2950 | 0.6692 | 0.8664 | 0.8845 | 0.8664 | 0.8645 | 0.9072 |
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- | 0.3701 | 8.09 | 3000 | 0.5942 | 0.8853 | 0.8984 | 0.8853 | 0.8832 | 0.9194 |
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- | 0.3701 | 8.22 | 3050 | 0.5489 | 0.8880 | 0.9005 | 0.8880 | 0.8851 | 0.9200 |
124
- | 0.3701 | 8.36 | 3100 | 0.6005 | 0.8704 | 0.8891 | 0.8704 | 0.8680 | 0.9088 |
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- | 0.3701 | 8.49 | 3150 | 0.5953 | 0.8731 | 0.8901 | 0.8731 | 0.8692 | 0.9109 |
126
- | 0.3701 | 8.63 | 3200 | 0.6945 | 0.8704 | 0.8893 | 0.8704 | 0.8701 | 0.9096 |
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- | 0.3701 | 8.76 | 3250 | 0.6193 | 0.8677 | 0.8861 | 0.8677 | 0.8649 | 0.9062 |
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- | 0.3701 | 8.89 | 3300 | 0.6426 | 0.8745 | 0.8873 | 0.8745 | 0.8711 | 0.9123 |
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- | 0.339 | 9.03 | 3350 | 0.5156 | 0.8988 | 0.9082 | 0.8988 | 0.8969 | 0.9293 |
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- | 0.339 | 9.16 | 3400 | 0.6132 | 0.8839 | 0.8977 | 0.8839 | 0.8817 | 0.9186 |
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- | 0.339 | 9.3 | 3450 | 0.6627 | 0.8718 | 0.8847 | 0.8718 | 0.8704 | 0.9097 |
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- | 0.339 | 9.43 | 3500 | 0.6656 | 0.8745 | 0.8910 | 0.8745 | 0.8717 | 0.9121 |
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- | 0.339 | 9.57 | 3550 | 0.6487 | 0.8799 | 0.8960 | 0.8799 | 0.8781 | 0.9161 |
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- | 0.339 | 9.7 | 3600 | 0.7063 | 0.8704 | 0.8860 | 0.8704 | 0.8663 | 0.9101 |
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- | 0.339 | 9.84 | 3650 | 0.6633 | 0.8691 | 0.8858 | 0.8691 | 0.8638 | 0.9085 |
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- | 0.339 | 9.97 | 3700 | 0.6501 | 0.8772 | 0.8899 | 0.8772 | 0.8750 | 0.9143 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6112
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+ - Accuracy: 0.8733
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+ - Precision: 0.8849
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+ - Recall: 0.8733
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+ - F1: 0.8715
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+ - Binary: 0.9115
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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+ | No log | 0.24 | 50 | 4.4173 | 0.0120 | 0.0018 | 0.0120 | 0.0027 | 0.1454 |
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+ | No log | 0.48 | 100 | 4.3112 | 0.0307 | 0.0029 | 0.0307 | 0.0050 | 0.2561 |
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+ | No log | 0.72 | 150 | 3.9716 | 0.0577 | 0.0136 | 0.0577 | 0.0137 | 0.3354 |
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+ | No log | 0.96 | 200 | 3.6532 | 0.0906 | 0.0647 | 0.0906 | 0.0408 | 0.3616 |
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+ | 4.2325 | 1.2 | 250 | 3.3860 | 0.1311 | 0.0767 | 0.1311 | 0.0725 | 0.3903 |
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+ | 4.2325 | 1.44 | 300 | 3.1896 | 0.2150 | 0.1277 | 0.2150 | 0.1379 | 0.4468 |
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+ | 4.2325 | 1.68 | 350 | 2.9240 | 0.2412 | 0.1475 | 0.2412 | 0.1486 | 0.4669 |
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+ | 4.2325 | 1.92 | 400 | 2.6191 | 0.2861 | 0.2519 | 0.2861 | 0.2143 | 0.4985 |
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+ | 3.2742 | 2.16 | 450 | 2.3504 | 0.3603 | 0.2949 | 0.3603 | 0.2791 | 0.5510 |
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+ | 3.2742 | 2.4 | 500 | 2.0177 | 0.4981 | 0.4172 | 0.4981 | 0.4130 | 0.6467 |
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+ | 3.2742 | 2.63 | 550 | 1.9152 | 0.5146 | 0.5098 | 0.5146 | 0.4630 | 0.6586 |
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+ | 3.2742 | 2.87 | 600 | 1.6539 | 0.5918 | 0.5981 | 0.5918 | 0.5415 | 0.7128 |
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+ | 2.3027 | 3.11 | 650 | 1.4801 | 0.6494 | 0.6389 | 0.6494 | 0.6128 | 0.7532 |
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+ | 2.3027 | 3.35 | 700 | 1.2164 | 0.7124 | 0.6887 | 0.7124 | 0.6790 | 0.7980 |
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+ | 2.3027 | 3.59 | 750 | 1.1214 | 0.7236 | 0.7205 | 0.7236 | 0.6985 | 0.8057 |
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+ | 2.3027 | 3.83 | 800 | 1.0199 | 0.7438 | 0.7357 | 0.7438 | 0.7187 | 0.8209 |
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+ | 1.6257 | 4.07 | 850 | 0.9595 | 0.7528 | 0.7644 | 0.7528 | 0.7354 | 0.8270 |
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+ | 1.6257 | 4.31 | 900 | 0.8867 | 0.7670 | 0.7720 | 0.7670 | 0.7507 | 0.8369 |
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+ | 1.6257 | 4.55 | 950 | 0.8603 | 0.7820 | 0.7875 | 0.7820 | 0.7713 | 0.8480 |
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+ | 1.6257 | 4.79 | 1000 | 0.7999 | 0.7723 | 0.7874 | 0.7723 | 0.7638 | 0.8413 |
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+ | 1.2686 | 5.03 | 1050 | 0.7813 | 0.7948 | 0.8123 | 0.7948 | 0.7873 | 0.8577 |
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+ | 1.2686 | 5.27 | 1100 | 0.7312 | 0.8165 | 0.8300 | 0.8165 | 0.8100 | 0.8709 |
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+ | 1.2686 | 5.51 | 1150 | 0.7178 | 0.8180 | 0.8347 | 0.8180 | 0.8132 | 0.8718 |
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+ | 1.2686 | 5.75 | 1200 | 0.7108 | 0.8060 | 0.8199 | 0.8060 | 0.8001 | 0.8646 |
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+ | 1.2686 | 5.99 | 1250 | 0.6504 | 0.8247 | 0.8304 | 0.8247 | 0.8165 | 0.8772 |
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+ | 1.0234 | 6.23 | 1300 | 0.6944 | 0.8187 | 0.8310 | 0.8187 | 0.8125 | 0.8725 |
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+ | 1.0234 | 6.47 | 1350 | 0.6046 | 0.8397 | 0.8548 | 0.8397 | 0.8383 | 0.8880 |
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+ | 1.0234 | 6.71 | 1400 | 0.6195 | 0.8382 | 0.8489 | 0.8382 | 0.8335 | 0.8869 |
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+ | 1.0234 | 6.95 | 1450 | 0.6295 | 0.8412 | 0.8514 | 0.8412 | 0.8372 | 0.8894 |
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+ | 0.8831 | 7.19 | 1500 | 0.6205 | 0.8337 | 0.8419 | 0.8337 | 0.8303 | 0.8837 |
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+ | 0.8831 | 7.43 | 1550 | 0.6006 | 0.8464 | 0.8590 | 0.8464 | 0.8447 | 0.8935 |
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+ | 0.8831 | 7.66 | 1600 | 0.5860 | 0.8592 | 0.8684 | 0.8592 | 0.8579 | 0.9036 |
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+ | 0.8831 | 7.9 | 1650 | 0.5906 | 0.8419 | 0.8525 | 0.8419 | 0.8409 | 0.8909 |
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+ | 0.7822 | 8.14 | 1700 | 0.6277 | 0.8457 | 0.8567 | 0.8457 | 0.8420 | 0.8922 |
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+ | 0.7822 | 8.38 | 1750 | 0.5977 | 0.8532 | 0.8659 | 0.8532 | 0.8496 | 0.8980 |
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+ | 0.7822 | 8.62 | 1800 | 0.5970 | 0.8622 | 0.8696 | 0.8622 | 0.8601 | 0.9037 |
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+ | 0.7822 | 8.86 | 1850 | 0.5471 | 0.8607 | 0.8678 | 0.8607 | 0.8593 | 0.9034 |
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+ | 0.7039 | 9.1 | 1900 | 0.5848 | 0.8569 | 0.8687 | 0.8569 | 0.8541 | 0.8999 |
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+ | 0.7039 | 9.34 | 1950 | 0.5518 | 0.8682 | 0.8748 | 0.8682 | 0.8665 | 0.9082 |
102
+ | 0.7039 | 9.58 | 2000 | 0.5860 | 0.8667 | 0.8760 | 0.8667 | 0.8653 | 0.9069 |
103
+ | 0.7039 | 9.82 | 2050 | 0.5937 | 0.8652 | 0.8743 | 0.8652 | 0.8624 | 0.9053 |
104
+ | 0.6314 | 10.06 | 2100 | 0.5993 | 0.8607 | 0.8688 | 0.8607 | 0.8592 | 0.9021 |
105
+ | 0.6314 | 10.3 | 2150 | 0.5401 | 0.8697 | 0.8780 | 0.8697 | 0.8675 | 0.9094 |
106
+ | 0.6314 | 10.54 | 2200 | 0.5701 | 0.8607 | 0.8744 | 0.8607 | 0.8600 | 0.9026 |
107
+ | 0.6314 | 10.78 | 2250 | 0.5303 | 0.8757 | 0.8854 | 0.8757 | 0.8738 | 0.9129 |
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+ | 0.6017 | 11.02 | 2300 | 0.5408 | 0.8772 | 0.8830 | 0.8772 | 0.8752 | 0.9139 |
109
+ | 0.6017 | 11.26 | 2350 | 0.5218 | 0.8809 | 0.8857 | 0.8809 | 0.8785 | 0.9168 |
110
+ | 0.6017 | 11.5 | 2400 | 0.6290 | 0.8584 | 0.8694 | 0.8584 | 0.8555 | 0.9005 |
111
+ | 0.6017 | 11.74 | 2450 | 0.5580 | 0.8644 | 0.8715 | 0.8644 | 0.8631 | 0.9055 |
112
+ | 0.6017 | 11.98 | 2500 | 0.5415 | 0.8652 | 0.8722 | 0.8652 | 0.8641 | 0.9060 |
113
+ | 0.5539 | 12.22 | 2550 | 0.5297 | 0.8749 | 0.8835 | 0.8749 | 0.8738 | 0.9123 |
114
+ | 0.5539 | 12.46 | 2600 | 0.5721 | 0.8682 | 0.8765 | 0.8682 | 0.8659 | 0.9079 |
115
+ | 0.5539 | 12.69 | 2650 | 0.5989 | 0.8697 | 0.8802 | 0.8697 | 0.8689 | 0.9098 |
116
+ | 0.5539 | 12.93 | 2700 | 0.6499 | 0.8629 | 0.8757 | 0.8629 | 0.8613 | 0.9053 |
117
+ | 0.5168 | 13.17 | 2750 | 0.5816 | 0.8749 | 0.8831 | 0.8749 | 0.8739 | 0.9124 |
118
+ | 0.5168 | 13.41 | 2800 | 0.6052 | 0.8764 | 0.8868 | 0.8764 | 0.8746 | 0.9133 |
119
+ | 0.5168 | 13.65 | 2850 | 0.6148 | 0.8697 | 0.8803 | 0.8697 | 0.8679 | 0.9084 |
120
+ | 0.5168 | 13.89 | 2900 | 0.6010 | 0.8779 | 0.8875 | 0.8779 | 0.8764 | 0.9153 |
121
+ | 0.4881 | 14.13 | 2950 | 0.5583 | 0.8801 | 0.8893 | 0.8801 | 0.8790 | 0.9160 |
122
+ | 0.4881 | 14.37 | 3000 | 0.5880 | 0.8779 | 0.8859 | 0.8779 | 0.8763 | 0.9154 |
123
+ | 0.4881 | 14.61 | 3050 | 0.5560 | 0.8794 | 0.8893 | 0.8794 | 0.8774 | 0.9169 |
124
+ | 0.4881 | 14.85 | 3100 | 0.5339 | 0.8831 | 0.8896 | 0.8831 | 0.8813 | 0.9191 |
125
+ | 0.4611 | 15.09 | 3150 | 0.5541 | 0.8816 | 0.8869 | 0.8816 | 0.8803 | 0.9176 |
126
+ | 0.4611 | 15.33 | 3200 | 0.5848 | 0.8839 | 0.8900 | 0.8839 | 0.8822 | 0.9190 |
127
+ | 0.4611 | 15.57 | 3250 | 0.5712 | 0.8869 | 0.8924 | 0.8869 | 0.8862 | 0.9207 |
128
+ | 0.4611 | 15.81 | 3300 | 0.5159 | 0.8921 | 0.8983 | 0.8921 | 0.8916 | 0.9246 |
129
+ | 0.4345 | 16.05 | 3350 | 0.5486 | 0.8839 | 0.8920 | 0.8839 | 0.8834 | 0.9191 |
130
+ | 0.4345 | 16.29 | 3400 | 0.5568 | 0.8816 | 0.8882 | 0.8816 | 0.8806 | 0.9179 |
131
+ | 0.4345 | 16.53 | 3450 | 0.5752 | 0.8839 | 0.8896 | 0.8839 | 0.8828 | 0.9186 |
132
+ | 0.4345 | 16.77 | 3500 | 0.5716 | 0.8831 | 0.8897 | 0.8831 | 0.8814 | 0.9181 |
133
+ | 0.4208 | 17.01 | 3550 | 0.5562 | 0.8816 | 0.8906 | 0.8816 | 0.8808 | 0.9170 |
134
+ | 0.4208 | 17.25 | 3600 | 0.5623 | 0.8809 | 0.8881 | 0.8809 | 0.8804 | 0.9165 |
135
+ | 0.4208 | 17.49 | 3650 | 0.5756 | 0.8914 | 0.8982 | 0.8914 | 0.8910 | 0.9238 |
136
+ | 0.4208 | 17.72 | 3700 | 0.5662 | 0.8861 | 0.8915 | 0.8861 | 0.8849 | 0.9199 |
137
+ | 0.4208 | 17.96 | 3750 | 0.5965 | 0.8891 | 0.8952 | 0.8891 | 0.8882 | 0.9220 |
138
+ | 0.4137 | 18.2 | 3800 | 0.5827 | 0.8876 | 0.8958 | 0.8876 | 0.8871 | 0.9217 |
139
+ | 0.4137 | 18.44 | 3850 | 0.5463 | 0.8929 | 0.8998 | 0.8929 | 0.8923 | 0.9249 |
140
+ | 0.4137 | 18.68 | 3900 | 0.5731 | 0.8869 | 0.8932 | 0.8869 | 0.8858 | 0.9207 |
141
+ | 0.4137 | 18.92 | 3950 | 0.5538 | 0.8869 | 0.8933 | 0.8869 | 0.8853 | 0.9209 |
142
+ | 0.39 | 19.16 | 4000 | 0.5692 | 0.8869 | 0.8934 | 0.8869 | 0.8854 | 0.9209 |
143
+ | 0.39 | 19.4 | 4050 | 0.5288 | 0.8944 | 0.8998 | 0.8944 | 0.8934 | 0.9259 |
144
+ | 0.39 | 19.64 | 4100 | 0.5907 | 0.8884 | 0.8951 | 0.8884 | 0.8879 | 0.9219 |
145
+ | 0.39 | 19.88 | 4150 | 0.5595 | 0.8884 | 0.8963 | 0.8884 | 0.8869 | 0.9219 |
146
+ | 0.359 | 20.12 | 4200 | 0.6029 | 0.8779 | 0.8868 | 0.8779 | 0.8776 | 0.9141 |
147
+ | 0.359 | 20.36 | 4250 | 0.5650 | 0.8959 | 0.9026 | 0.8959 | 0.8956 | 0.9272 |
148
+ | 0.359 | 20.6 | 4300 | 0.5699 | 0.8869 | 0.8935 | 0.8869 | 0.8863 | 0.9211 |
149
+ | 0.359 | 20.84 | 4350 | 0.5717 | 0.8816 | 0.8884 | 0.8816 | 0.8809 | 0.9172 |
150
+ | 0.3685 | 21.08 | 4400 | 0.5991 | 0.8794 | 0.8878 | 0.8794 | 0.8780 | 0.9157 |
151
+ | 0.3685 | 21.32 | 4450 | 0.5760 | 0.8959 | 0.9037 | 0.8959 | 0.8954 | 0.9274 |
152
+ | 0.3685 | 21.56 | 4500 | 0.5753 | 0.8974 | 0.9047 | 0.8974 | 0.8966 | 0.9285 |
153
+ | 0.3685 | 21.8 | 4550 | 0.5693 | 0.8891 | 0.8959 | 0.8891 | 0.8873 | 0.9227 |
154
+ | 0.3472 | 22.04 | 4600 | 0.5866 | 0.8831 | 0.8905 | 0.8831 | 0.8820 | 0.9184 |
155
+ | 0.3472 | 22.28 | 4650 | 0.5781 | 0.8899 | 0.8969 | 0.8899 | 0.8892 | 0.9233 |
156
+ | 0.3472 | 22.51 | 4700 | 0.6050 | 0.8921 | 0.8989 | 0.8921 | 0.8910 | 0.9240 |
157
+ | 0.3472 | 22.75 | 4750 | 0.5826 | 0.8914 | 0.8965 | 0.8914 | 0.8906 | 0.9238 |
158
+ | 0.3472 | 22.99 | 4800 | 0.5809 | 0.8981 | 0.9050 | 0.8981 | 0.8973 | 0.9285 |
159
+ | 0.3316 | 23.23 | 4850 | 0.6249 | 0.8869 | 0.8942 | 0.8869 | 0.8865 | 0.9210 |
160
+ | 0.3316 | 23.47 | 4900 | 0.5971 | 0.8876 | 0.8937 | 0.8876 | 0.8869 | 0.9214 |
161
+ | 0.3316 | 23.71 | 4950 | 0.5849 | 0.8884 | 0.8948 | 0.8884 | 0.8883 | 0.9217 |
162
+ | 0.3316 | 23.95 | 5000 | 0.5806 | 0.8854 | 0.8913 | 0.8854 | 0.8854 | 0.9199 |
163
+ | 0.3066 | 24.19 | 5050 | 0.5833 | 0.8936 | 0.8996 | 0.8936 | 0.8929 | 0.9254 |
164
+ | 0.3066 | 24.43 | 5100 | 0.5802 | 0.8966 | 0.9033 | 0.8966 | 0.8963 | 0.9275 |
165
+ | 0.3066 | 24.67 | 5150 | 0.5742 | 0.8906 | 0.8971 | 0.8906 | 0.8901 | 0.9233 |
166
 
167
 
168
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