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hubert-classifier-aug-fold-2

Audio Classification
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hubert
Generated from Trainer
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  1. README.md +80 -94
  2. model.safetensors +1 -1
  3. runs/Jul21_04-05-29_LAPTOP-1GID9RGH/events.out.tfevents.1721509530.LAPTOP-1GID9RGH.8660.4 +2 -2
  4. runs/Jul21_04-05-29_LAPTOP-1GID9RGH/events.out.tfevents.1721511880.LAPTOP-1GID9RGH.8660.5 +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: 0.7259
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- - Accuracy: 0.8720
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- - Precision: 0.8869
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- - Recall: 0.8720
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- - F1: 0.8705
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- - Binary: 0.9115
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  ## Model description
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@@ -60,94 +60,80 @@ 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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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
63
- | No log | 0.13 | 50 | 4.4197 | 0.0270 | 0.0232 | 0.0270 | 0.0117 | 0.1849 |
64
- | No log | 0.27 | 100 | 4.2998 | 0.0432 | 0.0232 | 0.0432 | 0.0109 | 0.3126 |
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- | No log | 0.4 | 150 | 3.9731 | 0.0553 | 0.0154 | 0.0553 | 0.0170 | 0.3332 |
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- | No log | 0.54 | 200 | 3.6492 | 0.0594 | 0.0211 | 0.0594 | 0.0169 | 0.3355 |
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- | No log | 0.67 | 250 | 3.4482 | 0.0945 | 0.0252 | 0.0945 | 0.0317 | 0.3599 |
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- | No log | 0.81 | 300 | 3.2094 | 0.1215 | 0.0559 | 0.1215 | 0.0495 | 0.3815 |
69
- | No log | 0.94 | 350 | 3.0184 | 0.1660 | 0.1000 | 0.1660 | 0.0883 | 0.4140 |
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- | 3.8426 | 1.08 | 400 | 2.6834 | 0.2807 | 0.2104 | 0.2807 | 0.2054 | 0.4961 |
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- | 3.8426 | 1.21 | 450 | 2.3799 | 0.3900 | 0.3073 | 0.3900 | 0.3055 | 0.5725 |
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- | 3.8426 | 1.35 | 500 | 2.0607 | 0.4440 | 0.4235 | 0.4440 | 0.3765 | 0.6111 |
73
- | 3.8426 | 1.48 | 550 | 1.7232 | 0.5520 | 0.5014 | 0.5520 | 0.4917 | 0.6857 |
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- | 3.8426 | 1.62 | 600 | 1.5077 | 0.6019 | 0.5531 | 0.6019 | 0.5435 | 0.7232 |
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- | 3.8426 | 1.75 | 650 | 1.3166 | 0.6181 | 0.6024 | 0.6181 | 0.5743 | 0.7335 |
76
- | 3.8426 | 1.89 | 700 | 1.2097 | 0.6802 | 0.6583 | 0.6802 | 0.6449 | 0.7750 |
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- | 2.1078 | 2.02 | 750 | 1.1776 | 0.6856 | 0.6934 | 0.6856 | 0.6510 | 0.7808 |
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- | 2.1078 | 2.16 | 800 | 1.0102 | 0.7382 | 0.7335 | 0.7382 | 0.7132 | 0.8152 |
79
- | 2.1078 | 2.29 | 850 | 0.9295 | 0.7409 | 0.7557 | 0.7409 | 0.7242 | 0.8189 |
80
- | 2.1078 | 2.43 | 900 | 0.8473 | 0.7760 | 0.7916 | 0.7760 | 0.7673 | 0.8444 |
81
- | 2.1078 | 2.56 | 950 | 0.7956 | 0.8057 | 0.8147 | 0.8057 | 0.7962 | 0.8632 |
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- | 2.1078 | 2.7 | 1000 | 0.8091 | 0.7908 | 0.8199 | 0.7908 | 0.7817 | 0.8534 |
83
- | 2.1078 | 2.83 | 1050 | 0.7345 | 0.8084 | 0.8208 | 0.8084 | 0.8027 | 0.8650 |
84
- | 2.1078 | 2.96 | 1100 | 0.7217 | 0.7935 | 0.7964 | 0.7935 | 0.7835 | 0.8557 |
85
- | 1.1182 | 3.1 | 1150 | 0.7444 | 0.7895 | 0.8096 | 0.7895 | 0.7827 | 0.8545 |
86
- | 1.1182 | 3.23 | 1200 | 0.7182 | 0.8057 | 0.8153 | 0.8057 | 0.7971 | 0.8638 |
87
- | 1.1182 | 3.37 | 1250 | 0.6496 | 0.8313 | 0.8414 | 0.8313 | 0.8267 | 0.8808 |
88
- | 1.1182 | 3.5 | 1300 | 0.7163 | 0.8111 | 0.8349 | 0.8111 | 0.8101 | 0.8684 |
89
- | 1.1182 | 3.64 | 1350 | 0.7026 | 0.8354 | 0.8543 | 0.8354 | 0.8309 | 0.8846 |
90
- | 1.1182 | 3.77 | 1400 | 0.6504 | 0.8246 | 0.8381 | 0.8246 | 0.8194 | 0.8765 |
91
- | 1.1182 | 3.91 | 1450 | 0.6685 | 0.8381 | 0.8525 | 0.8381 | 0.8358 | 0.8879 |
92
- | 0.7752 | 4.04 | 1500 | 0.6600 | 0.8340 | 0.8528 | 0.8340 | 0.8314 | 0.8839 |
93
- | 0.7752 | 4.18 | 1550 | 0.6048 | 0.8475 | 0.8594 | 0.8475 | 0.8440 | 0.8920 |
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- | 0.7752 | 4.31 | 1600 | 0.5907 | 0.8435 | 0.8575 | 0.8435 | 0.8397 | 0.8906 |
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- | 0.7752 | 4.45 | 1650 | 0.6118 | 0.8502 | 0.8673 | 0.8502 | 0.8476 | 0.8949 |
96
- | 0.7752 | 4.58 | 1700 | 0.6096 | 0.8610 | 0.8724 | 0.8610 | 0.8581 | 0.9024 |
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- | 0.7752 | 4.72 | 1750 | 0.6032 | 0.8529 | 0.8694 | 0.8529 | 0.8499 | 0.8977 |
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- | 0.7752 | 4.85 | 1800 | 0.6705 | 0.8502 | 0.8625 | 0.8502 | 0.8447 | 0.8962 |
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- | 0.7752 | 4.99 | 1850 | 0.6740 | 0.8381 | 0.8538 | 0.8381 | 0.8331 | 0.8877 |
100
- | 0.6054 | 5.12 | 1900 | 0.6444 | 0.8367 | 0.8471 | 0.8367 | 0.8302 | 0.8853 |
101
- | 0.6054 | 5.26 | 1950 | 0.6167 | 0.8529 | 0.8648 | 0.8529 | 0.8500 | 0.8976 |
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- | 0.6054 | 5.39 | 2000 | 0.6535 | 0.8462 | 0.8657 | 0.8462 | 0.8429 | 0.8939 |
103
- | 0.6054 | 5.53 | 2050 | 0.6420 | 0.8556 | 0.8688 | 0.8556 | 0.8550 | 0.8992 |
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- | 0.6054 | 5.66 | 2100 | 0.6535 | 0.8543 | 0.8696 | 0.8543 | 0.8523 | 0.8977 |
105
- | 0.6054 | 5.8 | 2150 | 0.5879 | 0.8516 | 0.8646 | 0.8516 | 0.8483 | 0.8958 |
106
- | 0.6054 | 5.93 | 2200 | 0.5808 | 0.8570 | 0.8701 | 0.8570 | 0.8551 | 0.9000 |
107
- | 0.5025 | 6.06 | 2250 | 0.6637 | 0.8516 | 0.8711 | 0.8516 | 0.8482 | 0.8962 |
108
- | 0.5025 | 6.2 | 2300 | 0.6450 | 0.8583 | 0.8734 | 0.8583 | 0.8540 | 0.9009 |
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- | 0.5025 | 6.33 | 2350 | 0.6152 | 0.8664 | 0.8768 | 0.8664 | 0.8644 | 0.9082 |
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- | 0.5025 | 6.47 | 2400 | 0.6640 | 0.8475 | 0.8620 | 0.8475 | 0.8432 | 0.8934 |
111
- | 0.5025 | 6.6 | 2450 | 0.5817 | 0.8664 | 0.8795 | 0.8664 | 0.8645 | 0.9062 |
112
- | 0.5025 | 6.74 | 2500 | 0.6881 | 0.8529 | 0.8673 | 0.8529 | 0.8487 | 0.8977 |
113
- | 0.5025 | 6.87 | 2550 | 0.6868 | 0.8421 | 0.8563 | 0.8421 | 0.8388 | 0.8907 |
114
- | 0.4381 | 7.01 | 2600 | 0.6270 | 0.8677 | 0.8823 | 0.8677 | 0.8664 | 0.9086 |
115
- | 0.4381 | 7.14 | 2650 | 0.7011 | 0.8583 | 0.8703 | 0.8583 | 0.8537 | 0.9001 |
116
- | 0.4381 | 7.28 | 2700 | 0.6665 | 0.8570 | 0.8757 | 0.8570 | 0.8548 | 0.8992 |
117
- | 0.4381 | 7.41 | 2750 | 0.6948 | 0.8421 | 0.8586 | 0.8421 | 0.8425 | 0.8911 |
118
- | 0.4381 | 7.55 | 2800 | 0.6832 | 0.8570 | 0.8710 | 0.8570 | 0.8542 | 0.9005 |
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- | 0.4381 | 7.68 | 2850 | 0.6391 | 0.8623 | 0.8782 | 0.8623 | 0.8620 | 0.9038 |
120
- | 0.4381 | 7.82 | 2900 | 0.8113 | 0.8448 | 0.8609 | 0.8448 | 0.8411 | 0.8946 |
121
- | 0.4381 | 7.95 | 2950 | 0.6688 | 0.8623 | 0.8724 | 0.8623 | 0.8603 | 0.9049 |
122
- | 0.381 | 8.09 | 3000 | 0.6731 | 0.8529 | 0.8652 | 0.8529 | 0.8508 | 0.8972 |
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- | 0.381 | 8.22 | 3050 | 0.8063 | 0.8340 | 0.8507 | 0.8340 | 0.8300 | 0.8839 |
124
- | 0.381 | 8.36 | 3100 | 0.6534 | 0.8596 | 0.8719 | 0.8596 | 0.8567 | 0.9009 |
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- | 0.381 | 8.49 | 3150 | 0.6772 | 0.8596 | 0.8730 | 0.8596 | 0.8574 | 0.9024 |
126
- | 0.381 | 8.63 | 3200 | 0.6293 | 0.8637 | 0.8754 | 0.8637 | 0.8630 | 0.9042 |
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- | 0.381 | 8.76 | 3250 | 0.6644 | 0.8570 | 0.8705 | 0.8570 | 0.8543 | 0.9001 |
128
- | 0.381 | 8.89 | 3300 | 0.6469 | 0.8623 | 0.8758 | 0.8623 | 0.8614 | 0.9043 |
129
- | 0.3473 | 9.03 | 3350 | 0.6055 | 0.8731 | 0.8833 | 0.8731 | 0.8722 | 0.9104 |
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- | 0.3473 | 9.16 | 3400 | 0.6828 | 0.8650 | 0.8767 | 0.8650 | 0.8636 | 0.9047 |
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- | 0.3473 | 9.3 | 3450 | 0.6625 | 0.8826 | 0.8967 | 0.8826 | 0.8817 | 0.9179 |
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- | 0.3473 | 9.43 | 3500 | 0.7111 | 0.8583 | 0.8692 | 0.8583 | 0.8559 | 0.9011 |
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- | 0.3473 | 9.57 | 3550 | 0.7215 | 0.8475 | 0.8608 | 0.8475 | 0.8449 | 0.8950 |
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- | 0.3473 | 9.7 | 3600 | 0.7040 | 0.8556 | 0.8654 | 0.8556 | 0.8527 | 0.9001 |
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- | 0.3473 | 9.84 | 3650 | 0.6809 | 0.8556 | 0.8674 | 0.8556 | 0.8531 | 0.8996 |
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- | 0.3473 | 9.97 | 3700 | 0.7191 | 0.8610 | 0.8754 | 0.8610 | 0.8609 | 0.9034 |
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- | 0.3245 | 10.11 | 3750 | 0.7053 | 0.8610 | 0.8682 | 0.8610 | 0.8586 | 0.9045 |
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- | 0.3245 | 10.24 | 3800 | 0.6594 | 0.8745 | 0.8869 | 0.8745 | 0.8739 | 0.9132 |
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- | 0.3245 | 10.38 | 3850 | 0.6882 | 0.8745 | 0.8872 | 0.8745 | 0.8735 | 0.9113 |
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- | 0.3245 | 10.51 | 3900 | 0.7113 | 0.8596 | 0.8732 | 0.8596 | 0.8584 | 0.9035 |
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- | 0.3245 | 10.65 | 3950 | 0.7299 | 0.8677 | 0.8836 | 0.8677 | 0.8675 | 0.9070 |
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- | 0.3245 | 10.78 | 4000 | 0.6812 | 0.8758 | 0.8861 | 0.8758 | 0.8745 | 0.9132 |
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- | 0.3245 | 10.92 | 4050 | 0.6459 | 0.8812 | 0.8927 | 0.8812 | 0.8788 | 0.9170 |
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- | 0.2964 | 11.05 | 4100 | 0.7044 | 0.8677 | 0.8805 | 0.8677 | 0.8665 | 0.9072 |
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- | 0.2964 | 11.19 | 4150 | 0.6455 | 0.8677 | 0.8758 | 0.8677 | 0.8663 | 0.9086 |
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- | 0.2964 | 11.32 | 4200 | 0.7581 | 0.8704 | 0.8790 | 0.8704 | 0.8692 | 0.9093 |
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- | 0.2964 | 11.46 | 4250 | 0.7489 | 0.8623 | 0.8781 | 0.8623 | 0.8588 | 0.9038 |
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- | 0.2964 | 11.59 | 4300 | 0.7293 | 0.8556 | 0.8677 | 0.8556 | 0.8541 | 0.8991 |
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- | 0.2964 | 11.73 | 4350 | 0.7996 | 0.8570 | 0.8662 | 0.8570 | 0.8550 | 0.8991 |
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- | 0.2964 | 11.86 | 4400 | 0.7340 | 0.8556 | 0.8670 | 0.8556 | 0.8531 | 0.8985 |
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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: 0.5616
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+ - Accuracy: 0.8814
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+ - Precision: 0.8965
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+ - Recall: 0.8814
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+ - F1: 0.8795
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+ - Binary: 0.9182
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  ## Model description
31
 
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
62
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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+ | No log | 0.13 | 50 | 4.4205 | 0.0310 | 0.0078 | 0.0310 | 0.0104 | 0.2054 |
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+ | No log | 0.27 | 100 | 4.3291 | 0.0445 | 0.0108 | 0.0445 | 0.0126 | 0.2987 |
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+ | No log | 0.4 | 150 | 3.9426 | 0.0688 | 0.0295 | 0.0688 | 0.0221 | 0.3405 |
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+ | No log | 0.54 | 200 | 3.5950 | 0.0823 | 0.0420 | 0.0823 | 0.0336 | 0.3548 |
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+ | No log | 0.67 | 250 | 3.3440 | 0.1323 | 0.0736 | 0.1323 | 0.0675 | 0.3893 |
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+ | No log | 0.81 | 300 | 3.0808 | 0.2105 | 0.1599 | 0.2105 | 0.1353 | 0.4457 |
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+ | No log | 0.94 | 350 | 2.8041 | 0.3212 | 0.2060 | 0.3212 | 0.2180 | 0.5235 |
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+ | 3.8037 | 1.08 | 400 | 2.4494 | 0.3603 | 0.2731 | 0.3603 | 0.2746 | 0.5495 |
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+ | 3.8037 | 1.21 | 450 | 2.1029 | 0.4588 | 0.3806 | 0.4588 | 0.3860 | 0.6201 |
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+ | 3.8037 | 1.35 | 500 | 1.8222 | 0.5317 | 0.5092 | 0.5317 | 0.4811 | 0.6730 |
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+ | 3.8037 | 1.48 | 550 | 1.6391 | 0.5533 | 0.5401 | 0.5533 | 0.5040 | 0.6862 |
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+ | 3.8037 | 1.62 | 600 | 1.3955 | 0.6464 | 0.6432 | 0.6464 | 0.6129 | 0.7538 |
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+ | 3.8037 | 1.75 | 650 | 1.3006 | 0.6653 | 0.6734 | 0.6653 | 0.6399 | 0.7645 |
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+ | 3.8037 | 1.89 | 700 | 1.2028 | 0.6721 | 0.6946 | 0.6721 | 0.6492 | 0.7707 |
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+ | 1.9419 | 2.02 | 750 | 1.0903 | 0.6910 | 0.6900 | 0.6910 | 0.6661 | 0.7846 |
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+ | 1.9419 | 2.16 | 800 | 1.1952 | 0.7099 | 0.7198 | 0.7099 | 0.6923 | 0.7962 |
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+ | 1.9419 | 2.29 | 850 | 0.9361 | 0.7341 | 0.7547 | 0.7341 | 0.7222 | 0.8146 |
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+ | 1.9419 | 2.43 | 900 | 0.8789 | 0.7490 | 0.7725 | 0.7490 | 0.7348 | 0.8252 |
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+ | 1.9419 | 2.56 | 950 | 0.8519 | 0.7787 | 0.8015 | 0.7787 | 0.7714 | 0.8453 |
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+ | 1.9419 | 2.7 | 1000 | 0.8211 | 0.7692 | 0.7978 | 0.7692 | 0.7610 | 0.8394 |
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+ | 1.9419 | 2.83 | 1050 | 0.7343 | 0.7922 | 0.8128 | 0.7922 | 0.7849 | 0.8563 |
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+ | 1.9419 | 2.96 | 1100 | 0.8199 | 0.7760 | 0.8004 | 0.7760 | 0.7703 | 0.8451 |
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+ | 1.0676 | 3.1 | 1150 | 0.6783 | 0.8016 | 0.8161 | 0.8016 | 0.7956 | 0.8610 |
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+ | 1.0676 | 3.23 | 1200 | 0.7483 | 0.8043 | 0.8285 | 0.8043 | 0.7991 | 0.8638 |
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+ | 1.0676 | 3.37 | 1250 | 0.8469 | 0.7881 | 0.8090 | 0.7881 | 0.7795 | 0.8514 |
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+ | 1.0676 | 3.5 | 1300 | 0.7466 | 0.8003 | 0.8228 | 0.8003 | 0.7963 | 0.8603 |
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+ | 1.0676 | 3.64 | 1350 | 0.7441 | 0.8084 | 0.8375 | 0.8084 | 0.8059 | 0.8656 |
90
+ | 1.0676 | 3.77 | 1400 | 0.6885 | 0.8124 | 0.8380 | 0.8124 | 0.8082 | 0.8695 |
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+ | 1.0676 | 3.91 | 1450 | 0.8319 | 0.7787 | 0.8045 | 0.7787 | 0.7729 | 0.8459 |
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+ | 0.75 | 4.04 | 1500 | 0.8044 | 0.8057 | 0.8320 | 0.8057 | 0.8017 | 0.8648 |
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+ | 0.75 | 4.18 | 1550 | 0.8120 | 0.8016 | 0.8230 | 0.8016 | 0.7964 | 0.8618 |
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+ | 0.75 | 4.31 | 1600 | 0.7503 | 0.8016 | 0.8166 | 0.8016 | 0.7965 | 0.8629 |
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+ | 0.75 | 4.45 | 1650 | 0.7646 | 0.8097 | 0.8269 | 0.8097 | 0.8025 | 0.8682 |
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+ | 0.75 | 4.58 | 1700 | 0.7328 | 0.8246 | 0.8442 | 0.8246 | 0.8189 | 0.8784 |
97
+ | 0.75 | 4.72 | 1750 | 0.7019 | 0.8300 | 0.8479 | 0.8300 | 0.8270 | 0.8831 |
98
+ | 0.75 | 4.85 | 1800 | 0.6364 | 0.8408 | 0.8558 | 0.8408 | 0.8379 | 0.8885 |
99
+ | 0.75 | 4.99 | 1850 | 0.6562 | 0.8259 | 0.8461 | 0.8259 | 0.8214 | 0.8787 |
100
+ | 0.5856 | 5.12 | 1900 | 0.6412 | 0.8340 | 0.8500 | 0.8340 | 0.8304 | 0.8843 |
101
+ | 0.5856 | 5.26 | 1950 | 0.6739 | 0.8340 | 0.8548 | 0.8340 | 0.8333 | 0.8843 |
102
+ | 0.5856 | 5.39 | 2000 | 0.7564 | 0.8097 | 0.8367 | 0.8097 | 0.8090 | 0.8673 |
103
+ | 0.5856 | 5.53 | 2050 | 0.6495 | 0.8286 | 0.8473 | 0.8286 | 0.8264 | 0.8807 |
104
+ | 0.5856 | 5.66 | 2100 | 0.7090 | 0.8165 | 0.8328 | 0.8165 | 0.8159 | 0.8717 |
105
+ | 0.5856 | 5.8 | 2150 | 0.7712 | 0.8435 | 0.8654 | 0.8435 | 0.8419 | 0.8897 |
106
+ | 0.5856 | 5.93 | 2200 | 0.7484 | 0.8273 | 0.8467 | 0.8273 | 0.8230 | 0.8802 |
107
+ | 0.4896 | 6.06 | 2250 | 0.7999 | 0.8178 | 0.8344 | 0.8178 | 0.8163 | 0.8725 |
108
+ | 0.4896 | 6.2 | 2300 | 0.7098 | 0.8300 | 0.8501 | 0.8300 | 0.8280 | 0.8821 |
109
+ | 0.4896 | 6.33 | 2350 | 0.8158 | 0.8259 | 0.8434 | 0.8259 | 0.8226 | 0.8783 |
110
+ | 0.4896 | 6.47 | 2400 | 0.6873 | 0.8381 | 0.8592 | 0.8381 | 0.8367 | 0.8868 |
111
+ | 0.4896 | 6.6 | 2450 | 0.7824 | 0.8178 | 0.8394 | 0.8178 | 0.8156 | 0.8730 |
112
+ | 0.4896 | 6.74 | 2500 | 0.6733 | 0.8448 | 0.8631 | 0.8448 | 0.8444 | 0.8915 |
113
+ | 0.4896 | 6.87 | 2550 | 0.7658 | 0.8381 | 0.8577 | 0.8381 | 0.8347 | 0.8862 |
114
+ | 0.4288 | 7.01 | 2600 | 0.7045 | 0.8367 | 0.8536 | 0.8367 | 0.8343 | 0.8853 |
115
+ | 0.4288 | 7.14 | 2650 | 0.6885 | 0.8570 | 0.8748 | 0.8570 | 0.8545 | 0.8995 |
116
+ | 0.4288 | 7.28 | 2700 | 0.7015 | 0.8475 | 0.8632 | 0.8475 | 0.8462 | 0.8934 |
117
+ | 0.4288 | 7.41 | 2750 | 0.7385 | 0.8381 | 0.8539 | 0.8381 | 0.8363 | 0.8870 |
118
+ | 0.4288 | 7.55 | 2800 | 0.7196 | 0.8475 | 0.8597 | 0.8475 | 0.8473 | 0.8930 |
119
+ | 0.4288 | 7.68 | 2850 | 0.7285 | 0.8421 | 0.8558 | 0.8421 | 0.8399 | 0.8887 |
120
+ | 0.4288 | 7.82 | 2900 | 0.7507 | 0.8367 | 0.8513 | 0.8367 | 0.8346 | 0.8849 |
121
+ | 0.4288 | 7.95 | 2950 | 0.8049 | 0.8259 | 0.8522 | 0.8259 | 0.8225 | 0.8779 |
122
+ | 0.3797 | 8.09 | 3000 | 0.7337 | 0.8529 | 0.8652 | 0.8529 | 0.8494 | 0.8978 |
123
+ | 0.3797 | 8.22 | 3050 | 0.7414 | 0.8475 | 0.8628 | 0.8475 | 0.8451 | 0.8924 |
124
+ | 0.3797 | 8.36 | 3100 | 0.8024 | 0.8394 | 0.8592 | 0.8394 | 0.8364 | 0.8877 |
125
+ | 0.3797 | 8.49 | 3150 | 0.7642 | 0.8435 | 0.8635 | 0.8435 | 0.8405 | 0.8904 |
126
+ | 0.3797 | 8.63 | 3200 | 0.7560 | 0.8448 | 0.8641 | 0.8448 | 0.8415 | 0.8906 |
127
+ | 0.3797 | 8.76 | 3250 | 0.7889 | 0.8408 | 0.8640 | 0.8408 | 0.8373 | 0.8887 |
128
+ | 0.3797 | 8.89 | 3300 | 0.7479 | 0.8448 | 0.8624 | 0.8448 | 0.8436 | 0.8915 |
129
+ | 0.3486 | 9.03 | 3350 | 0.7430 | 0.8543 | 0.8727 | 0.8543 | 0.8529 | 0.8977 |
130
+ | 0.3486 | 9.16 | 3400 | 0.7325 | 0.8394 | 0.8549 | 0.8394 | 0.8367 | 0.8877 |
131
+ | 0.3486 | 9.3 | 3450 | 0.7623 | 0.8489 | 0.8641 | 0.8489 | 0.8441 | 0.8949 |
132
+ | 0.3486 | 9.43 | 3500 | 0.7893 | 0.8462 | 0.8645 | 0.8462 | 0.8425 | 0.8924 |
133
+ | 0.3486 | 9.57 | 3550 | 0.8721 | 0.8273 | 0.8504 | 0.8273 | 0.8239 | 0.8808 |
134
+ | 0.3486 | 9.7 | 3600 | 0.7886 | 0.8489 | 0.8699 | 0.8489 | 0.8454 | 0.8939 |
135
+ | 0.3486 | 9.84 | 3650 | 0.7844 | 0.8502 | 0.8692 | 0.8502 | 0.8469 | 0.8953 |
136
+ | 0.3486 | 9.97 | 3700 | 0.9039 | 0.8232 | 0.8471 | 0.8232 | 0.8179 | 0.8769 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
137
 
138
 
139
  ### Framework versions
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