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End of training

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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: 0.7308
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- - Accuracy: 0.8585
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- - Precision: 0.8738
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- - Recall: 0.8585
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- - F1: 0.8578
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- - Binary: 0.8997
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  ## Model description
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@@ -52,6 +52,7 @@ The following hyperparameters were used during training:
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  - total_train_batch_size: 128
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
 
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  - num_epochs: 30
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  - mixed_precision_training: Native AMP
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@@ -59,101 +60,94 @@ 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 | 3.8576 | 0.0621 | 0.0074 | 0.0621 | 0.0112 | 0.3362 |
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- | No log | 0.27 | 100 | 3.4091 | 0.0931 | 0.0349 | 0.0931 | 0.0334 | 0.3617 |
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- | No log | 0.4 | 150 | 3.2224 | 0.1053 | 0.0231 | 0.1053 | 0.0330 | 0.3698 |
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- | No log | 0.54 | 200 | 3.0715 | 0.1215 | 0.0509 | 0.1215 | 0.0558 | 0.3800 |
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- | No log | 0.67 | 250 | 2.7013 | 0.2416 | 0.1533 | 0.2416 | 0.1549 | 0.4665 |
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- | No log | 0.81 | 300 | 2.4186 | 0.3077 | 0.2216 | 0.3077 | 0.2178 | 0.5124 |
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- | No log | 0.94 | 350 | 2.2086 | 0.3725 | 0.2827 | 0.3725 | 0.2882 | 0.5592 |
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- | 3.209 | 1.08 | 400 | 1.9624 | 0.4534 | 0.4314 | 0.4534 | 0.3907 | 0.6155 |
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- | 3.209 | 1.21 | 450 | 1.7552 | 0.5344 | 0.4957 | 0.5344 | 0.4788 | 0.6735 |
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- | 3.209 | 1.35 | 500 | 1.5887 | 0.5668 | 0.5359 | 0.5668 | 0.5127 | 0.6957 |
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- | 3.209 | 1.48 | 550 | 1.4249 | 0.6073 | 0.5999 | 0.6073 | 0.5671 | 0.7248 |
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- | 3.209 | 1.62 | 600 | 1.2562 | 0.6397 | 0.6424 | 0.6397 | 0.6007 | 0.7486 |
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- | 3.209 | 1.75 | 650 | 1.1504 | 0.6680 | 0.6724 | 0.6680 | 0.6379 | 0.7683 |
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- | 3.209 | 1.89 | 700 | 1.0797 | 0.6991 | 0.7111 | 0.6991 | 0.6753 | 0.7896 |
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- | 1.7186 | 2.02 | 750 | 1.0473 | 0.7314 | 0.7634 | 0.7314 | 0.7173 | 0.8139 |
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- | 1.7186 | 2.16 | 800 | 0.9383 | 0.7503 | 0.7777 | 0.7503 | 0.7343 | 0.8271 |
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- | 1.7186 | 2.29 | 850 | 0.9288 | 0.7679 | 0.7842 | 0.7679 | 0.7567 | 0.8393 |
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- | 1.7186 | 2.43 | 900 | 0.8284 | 0.7746 | 0.7897 | 0.7746 | 0.7679 | 0.8432 |
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- | 1.7186 | 2.56 | 950 | 0.8246 | 0.7800 | 0.8108 | 0.7800 | 0.7729 | 0.8474 |
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- | 1.7186 | 2.7 | 1000 | 0.8581 | 0.7665 | 0.7893 | 0.7665 | 0.7586 | 0.8370 |
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- | 1.7186 | 2.83 | 1050 | 0.7753 | 0.7962 | 0.8151 | 0.7962 | 0.7919 | 0.8583 |
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- | 1.7186 | 2.96 | 1100 | 0.7556 | 0.8043 | 0.8205 | 0.8043 | 0.7965 | 0.8641 |
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- | 1.0562 | 3.1 | 1150 | 0.8130 | 0.7962 | 0.8149 | 0.7962 | 0.7913 | 0.8567 |
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- | 1.0562 | 3.23 | 1200 | 0.7633 | 0.7895 | 0.8189 | 0.7895 | 0.7880 | 0.8528 |
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- | 1.0562 | 3.37 | 1250 | 0.6852 | 0.8178 | 0.8352 | 0.8178 | 0.8135 | 0.8742 |
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- | 1.0562 | 3.5 | 1300 | 0.8465 | 0.7638 | 0.8001 | 0.7638 | 0.7588 | 0.8347 |
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- | 1.0562 | 3.64 | 1350 | 0.7130 | 0.8111 | 0.8215 | 0.8111 | 0.8026 | 0.8686 |
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- | 1.0562 | 3.77 | 1400 | 0.7425 | 0.8057 | 0.8242 | 0.8057 | 0.8040 | 0.8657 |
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- | 1.0562 | 3.91 | 1450 | 0.7719 | 0.8057 | 0.8220 | 0.8057 | 0.8030 | 0.8634 |
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- | 0.782 | 4.04 | 1500 | 0.6581 | 0.8354 | 0.8497 | 0.8354 | 0.8332 | 0.8850 |
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- | 0.782 | 4.18 | 1550 | 0.7134 | 0.8124 | 0.8281 | 0.8124 | 0.8095 | 0.8682 |
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- | 0.782 | 4.31 | 1600 | 0.6923 | 0.8259 | 0.8455 | 0.8259 | 0.8234 | 0.8795 |
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- | 0.782 | 4.45 | 1650 | 0.6699 | 0.8367 | 0.8539 | 0.8367 | 0.8347 | 0.8868 |
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- | 0.782 | 4.58 | 1700 | 0.6169 | 0.8475 | 0.8597 | 0.8475 | 0.8456 | 0.8926 |
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- | 0.782 | 4.72 | 1750 | 0.6198 | 0.8381 | 0.8491 | 0.8381 | 0.8349 | 0.8870 |
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- | 0.782 | 4.85 | 1800 | 0.6939 | 0.8313 | 0.8502 | 0.8313 | 0.8318 | 0.8823 |
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- | 0.782 | 4.99 | 1850 | 0.7710 | 0.8205 | 0.8408 | 0.8205 | 0.8147 | 0.8729 |
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- | 0.6114 | 5.12 | 1900 | 0.6556 | 0.8381 | 0.8495 | 0.8381 | 0.8362 | 0.8880 |
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- | 0.6114 | 5.26 | 1950 | 0.7667 | 0.8151 | 0.8332 | 0.8151 | 0.8129 | 0.8698 |
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- | 0.6114 | 5.39 | 2000 | 0.7299 | 0.8232 | 0.8413 | 0.8232 | 0.8200 | 0.8748 |
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- | 0.6114 | 5.53 | 2050 | 0.7309 | 0.8327 | 0.8419 | 0.8327 | 0.8266 | 0.8835 |
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- | 0.6114 | 5.66 | 2100 | 0.7464 | 0.8192 | 0.8344 | 0.8192 | 0.8165 | 0.8750 |
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- | 0.6114 | 5.8 | 2150 | 0.7440 | 0.8340 | 0.8484 | 0.8340 | 0.8323 | 0.8849 |
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- | 0.6114 | 5.93 | 2200 | 0.7002 | 0.8475 | 0.8594 | 0.8475 | 0.8455 | 0.8935 |
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- | 0.5068 | 6.06 | 2250 | 0.7030 | 0.8448 | 0.8599 | 0.8448 | 0.8421 | 0.8912 |
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- | 0.5068 | 6.2 | 2300 | 0.7355 | 0.8421 | 0.8560 | 0.8421 | 0.8398 | 0.8889 |
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- | 0.5068 | 6.33 | 2350 | 0.7511 | 0.8246 | 0.8339 | 0.8246 | 0.8209 | 0.8771 |
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- | 0.5068 | 6.47 | 2400 | 0.6739 | 0.8421 | 0.8534 | 0.8421 | 0.8408 | 0.8903 |
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- | 0.5068 | 6.6 | 2450 | 0.6982 | 0.8475 | 0.8654 | 0.8475 | 0.8441 | 0.8931 |
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- | 0.5068 | 6.74 | 2500 | 0.7522 | 0.8408 | 0.8531 | 0.8408 | 0.8394 | 0.8880 |
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- | 0.5068 | 6.87 | 2550 | 0.7261 | 0.8354 | 0.8479 | 0.8354 | 0.8323 | 0.8856 |
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- | 0.4429 | 7.01 | 2600 | 0.7445 | 0.8421 | 0.8557 | 0.8421 | 0.8402 | 0.8896 |
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- | 0.4429 | 7.14 | 2650 | 0.7698 | 0.8327 | 0.8406 | 0.8327 | 0.8290 | 0.8823 |
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- | 0.4429 | 7.28 | 2700 | 0.8428 | 0.8273 | 0.8433 | 0.8273 | 0.8254 | 0.8806 |
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- | 0.4429 | 7.41 | 2750 | 0.8403 | 0.8259 | 0.8443 | 0.8259 | 0.8242 | 0.8789 |
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- | 0.4429 | 7.55 | 2800 | 0.7045 | 0.8381 | 0.8527 | 0.8381 | 0.8372 | 0.8866 |
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- | 0.4429 | 7.68 | 2850 | 0.8546 | 0.8327 | 0.8441 | 0.8327 | 0.8309 | 0.8825 |
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- | 0.4429 | 7.82 | 2900 | 0.7722 | 0.8340 | 0.8511 | 0.8340 | 0.8350 | 0.8830 |
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- | 0.4429 | 7.95 | 2950 | 0.7198 | 0.8435 | 0.8590 | 0.8435 | 0.8432 | 0.8927 |
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- | 0.3872 | 8.09 | 3000 | 0.7239 | 0.8408 | 0.8510 | 0.8408 | 0.8382 | 0.8914 |
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- | 0.3872 | 8.22 | 3050 | 0.7778 | 0.8475 | 0.8572 | 0.8475 | 0.8452 | 0.8950 |
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- | 0.3872 | 8.36 | 3100 | 0.8277 | 0.8394 | 0.8513 | 0.8394 | 0.8378 | 0.8892 |
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- | 0.3872 | 8.49 | 3150 | 0.7813 | 0.8462 | 0.8587 | 0.8462 | 0.8459 | 0.8912 |
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- | 0.3872 | 8.63 | 3200 | 0.7736 | 0.8394 | 0.8503 | 0.8394 | 0.8373 | 0.8880 |
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- | 0.3872 | 8.76 | 3250 | 0.7917 | 0.8394 | 0.8530 | 0.8394 | 0.8371 | 0.8883 |
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- | 0.3872 | 8.89 | 3300 | 0.7909 | 0.8475 | 0.8565 | 0.8475 | 0.8456 | 0.8930 |
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- | 0.3527 | 9.03 | 3350 | 0.7729 | 0.8529 | 0.8659 | 0.8529 | 0.8506 | 0.8977 |
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- | 0.3527 | 9.16 | 3400 | 0.8406 | 0.8475 | 0.8635 | 0.8475 | 0.8443 | 0.8937 |
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- | 0.3527 | 9.3 | 3450 | 0.7908 | 0.8435 | 0.8561 | 0.8435 | 0.8406 | 0.8910 |
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- | 0.3527 | 9.43 | 3500 | 0.8294 | 0.8300 | 0.8432 | 0.8300 | 0.8279 | 0.8808 |
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- | 0.3527 | 9.57 | 3550 | 0.8214 | 0.8421 | 0.8559 | 0.8421 | 0.8418 | 0.8897 |
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- | 0.3527 | 9.7 | 3600 | 0.8200 | 0.8435 | 0.8571 | 0.8435 | 0.8426 | 0.8918 |
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- | 0.3527 | 9.84 | 3650 | 0.7658 | 0.8502 | 0.8594 | 0.8502 | 0.8487 | 0.8969 |
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- | 0.3527 | 9.97 | 3700 | 0.8817 | 0.8354 | 0.8505 | 0.8354 | 0.8350 | 0.8842 |
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- | 0.3278 | 10.11 | 3750 | 0.8310 | 0.8489 | 0.8660 | 0.8489 | 0.8493 | 0.8950 |
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- | 0.3278 | 10.24 | 3800 | 0.6998 | 0.8664 | 0.8765 | 0.8664 | 0.8654 | 0.9072 |
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- | 0.3278 | 10.38 | 3850 | 0.7762 | 0.8435 | 0.8588 | 0.8435 | 0.8439 | 0.8904 |
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- | 0.3278 | 10.51 | 3900 | 0.9134 | 0.8435 | 0.8563 | 0.8435 | 0.8427 | 0.8920 |
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- | 0.3278 | 10.65 | 3950 | 0.7972 | 0.8556 | 0.8722 | 0.8556 | 0.8542 | 0.8988 |
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- | 0.3278 | 10.78 | 4000 | 0.8311 | 0.8610 | 0.8727 | 0.8610 | 0.8598 | 0.9043 |
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- | 0.3278 | 10.92 | 4050 | 0.8660 | 0.8543 | 0.8647 | 0.8543 | 0.8540 | 0.8993 |
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- | 0.2997 | 11.05 | 4100 | 0.8472 | 0.8556 | 0.8679 | 0.8556 | 0.8544 | 0.8988 |
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- | 0.2997 | 11.19 | 4150 | 0.7564 | 0.8556 | 0.8672 | 0.8556 | 0.8544 | 0.9001 |
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- | 0.2997 | 11.32 | 4200 | 0.7832 | 0.8529 | 0.8684 | 0.8529 | 0.8527 | 0.9005 |
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- | 0.2997 | 11.46 | 4250 | 0.8058 | 0.8623 | 0.8735 | 0.8623 | 0.8591 | 0.9049 |
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- | 0.2997 | 11.59 | 4300 | 0.7588 | 0.8623 | 0.8788 | 0.8623 | 0.8613 | 0.9054 |
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- | 0.2997 | 11.73 | 4350 | 0.8209 | 0.8462 | 0.8658 | 0.8462 | 0.8472 | 0.8926 |
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- | 0.2997 | 11.86 | 4400 | 0.7649 | 0.8650 | 0.8815 | 0.8650 | 0.8660 | 0.9043 |
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- | 0.2997 | 11.99 | 4450 | 0.7985 | 0.8529 | 0.8671 | 0.8529 | 0.8514 | 0.8966 |
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- | 0.283 | 12.13 | 4500 | 0.7353 | 0.8543 | 0.8640 | 0.8543 | 0.8529 | 0.8977 |
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- | 0.283 | 12.26 | 4550 | 0.7714 | 0.8543 | 0.8658 | 0.8543 | 0.8529 | 0.8992 |
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- | 0.283 | 12.4 | 4600 | 0.8393 | 0.8502 | 0.8629 | 0.8502 | 0.8476 | 0.8945 |
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- | 0.283 | 12.53 | 4650 | 0.7847 | 0.8556 | 0.8652 | 0.8556 | 0.8534 | 0.9001 |
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- | 0.283 | 12.67 | 4700 | 0.8041 | 0.8623 | 0.8722 | 0.8623 | 0.8590 | 0.9043 |
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- | 0.283 | 12.8 | 4750 | 0.8478 | 0.8475 | 0.8592 | 0.8475 | 0.8458 | 0.8939 |
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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: 0.7259
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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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  - total_train_batch_size: 128
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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  - num_epochs: 30
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  - mixed_precision_training: Native AMP
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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 | 4.4197 | 0.0270 | 0.0232 | 0.0270 | 0.0117 | 0.1849 |
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+ | 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 |
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+ | 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 |
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+ | 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 |
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+ | 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 |
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+ | 2.1078 | 2.29 | 850 | 0.9295 | 0.7409 | 0.7557 | 0.7409 | 0.7242 | 0.8189 |
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+ | 2.1078 | 2.43 | 900 | 0.8473 | 0.7760 | 0.7916 | 0.7760 | 0.7673 | 0.8444 |
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+ | 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 |
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+ | 2.1078 | 2.83 | 1050 | 0.7345 | 0.8084 | 0.8208 | 0.8084 | 0.8027 | 0.8650 |
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+ | 2.1078 | 2.96 | 1100 | 0.7217 | 0.7935 | 0.7964 | 0.7935 | 0.7835 | 0.8557 |
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+ | 1.1182 | 3.1 | 1150 | 0.7444 | 0.7895 | 0.8096 | 0.7895 | 0.7827 | 0.8545 |
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+ | 1.1182 | 3.23 | 1200 | 0.7182 | 0.8057 | 0.8153 | 0.8057 | 0.7971 | 0.8638 |
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+ | 1.1182 | 3.37 | 1250 | 0.6496 | 0.8313 | 0.8414 | 0.8313 | 0.8267 | 0.8808 |
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+ | 1.1182 | 3.5 | 1300 | 0.7163 | 0.8111 | 0.8349 | 0.8111 | 0.8101 | 0.8684 |
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+ | 1.1182 | 3.64 | 1350 | 0.7026 | 0.8354 | 0.8543 | 0.8354 | 0.8309 | 0.8846 |
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+ | 1.1182 | 3.77 | 1400 | 0.6504 | 0.8246 | 0.8381 | 0.8246 | 0.8194 | 0.8765 |
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+ | 1.1182 | 3.91 | 1450 | 0.6685 | 0.8381 | 0.8525 | 0.8381 | 0.8358 | 0.8879 |
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+ | 0.7752 | 4.04 | 1500 | 0.6600 | 0.8340 | 0.8528 | 0.8340 | 0.8314 | 0.8839 |
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+ | 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 |
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+ | 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 |
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+ | 0.6054 | 5.12 | 1900 | 0.6444 | 0.8367 | 0.8471 | 0.8367 | 0.8302 | 0.8853 |
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+ | 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 |
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+ | 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 |
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+ | 0.6054 | 5.8 | 2150 | 0.5879 | 0.8516 | 0.8646 | 0.8516 | 0.8483 | 0.8958 |
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+ | 0.6054 | 5.93 | 2200 | 0.5808 | 0.8570 | 0.8701 | 0.8570 | 0.8551 | 0.9000 |
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+ | 0.5025 | 6.06 | 2250 | 0.6637 | 0.8516 | 0.8711 | 0.8516 | 0.8482 | 0.8962 |
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+ | 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 |
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+ | 0.5025 | 6.6 | 2450 | 0.5817 | 0.8664 | 0.8795 | 0.8664 | 0.8645 | 0.9062 |
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+ | 0.5025 | 6.74 | 2500 | 0.6881 | 0.8529 | 0.8673 | 0.8529 | 0.8487 | 0.8977 |
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+ | 0.5025 | 6.87 | 2550 | 0.6868 | 0.8421 | 0.8563 | 0.8421 | 0.8388 | 0.8907 |
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+ | 0.4381 | 7.01 | 2600 | 0.6270 | 0.8677 | 0.8823 | 0.8677 | 0.8664 | 0.9086 |
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+ | 0.4381 | 7.14 | 2650 | 0.7011 | 0.8583 | 0.8703 | 0.8583 | 0.8537 | 0.9001 |
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+ | 0.4381 | 7.28 | 2700 | 0.6665 | 0.8570 | 0.8757 | 0.8570 | 0.8548 | 0.8992 |
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+ | 0.4381 | 7.41 | 2750 | 0.6948 | 0.8421 | 0.8586 | 0.8421 | 0.8425 | 0.8911 |
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+ | 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 |
123
+ | 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 |
125
+ | 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 |
127
+ | 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 |
130
+ | 0.3473 | 9.16 | 3400 | 0.6828 | 0.8650 | 0.8767 | 0.8650 | 0.8636 | 0.9047 |
131
+ | 0.3473 | 9.3 | 3450 | 0.6625 | 0.8826 | 0.8967 | 0.8826 | 0.8817 | 0.9179 |
132
+ | 0.3473 | 9.43 | 3500 | 0.7111 | 0.8583 | 0.8692 | 0.8583 | 0.8559 | 0.9011 |
133
+ | 0.3473 | 9.57 | 3550 | 0.7215 | 0.8475 | 0.8608 | 0.8475 | 0.8449 | 0.8950 |
134
+ | 0.3473 | 9.7 | 3600 | 0.7040 | 0.8556 | 0.8654 | 0.8556 | 0.8527 | 0.9001 |
135
+ | 0.3473 | 9.84 | 3650 | 0.6809 | 0.8556 | 0.8674 | 0.8556 | 0.8531 | 0.8996 |
136
+ | 0.3473 | 9.97 | 3700 | 0.7191 | 0.8610 | 0.8754 | 0.8610 | 0.8609 | 0.9034 |
137
+ | 0.3245 | 10.11 | 3750 | 0.7053 | 0.8610 | 0.8682 | 0.8610 | 0.8586 | 0.9045 |
138
+ | 0.3245 | 10.24 | 3800 | 0.6594 | 0.8745 | 0.8869 | 0.8745 | 0.8739 | 0.9132 |
139
+ | 0.3245 | 10.38 | 3850 | 0.6882 | 0.8745 | 0.8872 | 0.8745 | 0.8735 | 0.9113 |
140
+ | 0.3245 | 10.51 | 3900 | 0.7113 | 0.8596 | 0.8732 | 0.8596 | 0.8584 | 0.9035 |
141
+ | 0.3245 | 10.65 | 3950 | 0.7299 | 0.8677 | 0.8836 | 0.8677 | 0.8675 | 0.9070 |
142
+ | 0.3245 | 10.78 | 4000 | 0.6812 | 0.8758 | 0.8861 | 0.8758 | 0.8745 | 0.9132 |
143
+ | 0.3245 | 10.92 | 4050 | 0.6459 | 0.8812 | 0.8927 | 0.8812 | 0.8788 | 0.9170 |
144
+ | 0.2964 | 11.05 | 4100 | 0.7044 | 0.8677 | 0.8805 | 0.8677 | 0.8665 | 0.9072 |
145
+ | 0.2964 | 11.19 | 4150 | 0.6455 | 0.8677 | 0.8758 | 0.8677 | 0.8663 | 0.9086 |
146
+ | 0.2964 | 11.32 | 4200 | 0.7581 | 0.8704 | 0.8790 | 0.8704 | 0.8692 | 0.9093 |
147
+ | 0.2964 | 11.46 | 4250 | 0.7489 | 0.8623 | 0.8781 | 0.8623 | 0.8588 | 0.9038 |
148
+ | 0.2964 | 11.59 | 4300 | 0.7293 | 0.8556 | 0.8677 | 0.8556 | 0.8541 | 0.8991 |
149
+ | 0.2964 | 11.73 | 4350 | 0.7996 | 0.8570 | 0.8662 | 0.8570 | 0.8550 | 0.8991 |
150
+ | 0.2964 | 11.86 | 4400 | 0.7340 | 0.8556 | 0.8670 | 0.8556 | 0.8531 | 0.8985 |
 
 
 
 
 
 
 
151
 
152
 
153
  ### Framework versions
runs/Jul20_12-49-17_LAPTOP-1GID9RGH/events.out.tfevents.1721454559.LAPTOP-1GID9RGH.23448.4 CHANGED
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- size 52931
 
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+ oid sha256:ba6f44361127576f63800ca3df5c9e897ff4930e9902937112ed68f987eaa1ad
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+ size 57883
runs/Jul20_12-49-17_LAPTOP-1GID9RGH/events.out.tfevents.1721457470.LAPTOP-1GID9RGH.23448.5 ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:38702a8dc1e2fc144c63e0ceea1e1588a9b985f22ea1e9e706314e3c5e51ad62
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