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VarunUOB
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speaker-segmentation-fine-tuned-callhome-jpn

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pyannet
speaker-diarization
speaker-segmentation
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  1. README.md +30 -30
  2. model.safetensors +1 -1
  3. runs/Sep03_19-18-11_09a74c860030/events.out.tfevents.1725391129.09a74c860030.1993.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [pyannote/speaker-diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) on the diarizers-community/callhome dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7390
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- - Der: 0.2115
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- - False Alarm: 0.0300
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- - Missed Detection: 0.0148
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- - Confusion: 0.1667
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  ## Model description
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@@ -56,31 +56,31 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Der | False Alarm | Missed Detection | Confusion |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
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- | 0.6055 | 1.0 | 162 | 0.7220 | 0.2327 | 0.0308 | 0.0139 | 0.1880 |
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- | 0.5431 | 2.0 | 324 | 0.6852 | 0.2248 | 0.0308 | 0.0137 | 0.1803 |
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- | 0.5333 | 3.0 | 486 | 0.6997 | 0.2243 | 0.0309 | 0.0137 | 0.1797 |
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- | 0.4688 | 4.0 | 648 | 0.6579 | 0.2175 | 0.0309 | 0.0139 | 0.1727 |
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- | 0.4674 | 5.0 | 810 | 0.6863 | 0.2206 | 0.0309 | 0.0137 | 0.1760 |
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- | 0.4568 | 6.0 | 972 | 0.6751 | 0.2151 | 0.0309 | 0.0139 | 0.1703 |
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- | 0.4528 | 7.0 | 1134 | 0.6515 | 0.2135 | 0.0307 | 0.0141 | 0.1686 |
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- | 0.4464 | 8.0 | 1296 | 0.6786 | 0.2154 | 0.0312 | 0.0139 | 0.1704 |
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- | 0.4146 | 9.0 | 1458 | 0.6735 | 0.2124 | 0.0308 | 0.0139 | 0.1677 |
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- | 0.4098 | 10.0 | 1620 | 0.6900 | 0.2132 | 0.0309 | 0.0138 | 0.1686 |
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- | 0.3943 | 11.0 | 1782 | 0.7008 | 0.2099 | 0.0306 | 0.0140 | 0.1653 |
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- | 0.3889 | 12.0 | 1944 | 0.6992 | 0.2121 | 0.0300 | 0.0144 | 0.1676 |
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- | 0.3904 | 13.0 | 2106 | 0.7262 | 0.2165 | 0.0303 | 0.0141 | 0.1720 |
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- | 0.3694 | 14.0 | 2268 | 0.7131 | 0.2114 | 0.0301 | 0.0142 | 0.1671 |
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- | 0.3753 | 15.0 | 2430 | 0.7101 | 0.2098 | 0.0304 | 0.0140 | 0.1654 |
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- | 0.3732 | 16.0 | 2592 | 0.7181 | 0.2138 | 0.0301 | 0.0145 | 0.1692 |
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- | 0.3621 | 17.0 | 2754 | 0.7293 | 0.2133 | 0.0302 | 0.0146 | 0.1684 |
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- | 0.3482 | 18.0 | 2916 | 0.7399 | 0.2126 | 0.0301 | 0.0146 | 0.1679 |
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- | 0.3503 | 19.0 | 3078 | 0.7351 | 0.2122 | 0.0300 | 0.0148 | 0.1673 |
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- | 0.3558 | 20.0 | 3240 | 0.7367 | 0.2131 | 0.0301 | 0.0147 | 0.1682 |
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- | 0.3579 | 21.0 | 3402 | 0.7437 | 0.2127 | 0.0300 | 0.0148 | 0.1679 |
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- | 0.352 | 22.0 | 3564 | 0.7420 | 0.2128 | 0.0301 | 0.0148 | 0.1679 |
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- | 0.3662 | 23.0 | 3726 | 0.7380 | 0.2116 | 0.0300 | 0.0148 | 0.1668 |
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- | 0.3381 | 24.0 | 3888 | 0.7387 | 0.2115 | 0.0300 | 0.0148 | 0.1667 |
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- | 0.3446 | 25.0 | 4050 | 0.7390 | 0.2115 | 0.0300 | 0.0148 | 0.1667 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [pyannote/speaker-diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) on the diarizers-community/callhome dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6518
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+ - Der: 0.2003
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+ - False Alarm: 0.0204
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+ - Missed Detection: 0.0126
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+ - Confusion: 0.1673
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Der | False Alarm | Missed Detection | Confusion |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
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+ | 0.6084 | 1.0 | 157 | 0.6361 | 0.2140 | 0.0209 | 0.0101 | 0.1829 |
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+ | 0.5157 | 2.0 | 314 | 0.6039 | 0.2079 | 0.0213 | 0.0101 | 0.1765 |
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+ | 0.4718 | 3.0 | 471 | 0.6117 | 0.2094 | 0.0218 | 0.0101 | 0.1775 |
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+ | 0.5069 | 4.0 | 628 | 0.6086 | 0.2129 | 0.0215 | 0.0101 | 0.1813 |
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+ | 0.47 | 5.0 | 785 | 0.5974 | 0.2040 | 0.0215 | 0.0101 | 0.1724 |
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+ | 0.4539 | 6.0 | 942 | 0.6047 | 0.2065 | 0.0219 | 0.0102 | 0.1745 |
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+ | 0.4325 | 7.0 | 1099 | 0.5944 | 0.2009 | 0.0214 | 0.0104 | 0.1691 |
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+ | 0.434 | 8.0 | 1256 | 0.6110 | 0.2059 | 0.0214 | 0.0105 | 0.1740 |
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+ | 0.4199 | 9.0 | 1413 | 0.6045 | 0.2050 | 0.0212 | 0.0106 | 0.1733 |
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+ | 0.4479 | 10.0 | 1570 | 0.6101 | 0.1990 | 0.0212 | 0.0105 | 0.1673 |
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+ | 0.392 | 11.0 | 1727 | 0.6106 | 0.2003 | 0.0208 | 0.0107 | 0.1687 |
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+ | 0.3858 | 12.0 | 1884 | 0.6279 | 0.2009 | 0.0211 | 0.0108 | 0.1689 |
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+ | 0.3686 | 13.0 | 2041 | 0.6279 | 0.1976 | 0.0209 | 0.0114 | 0.1653 |
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+ | 0.3963 | 14.0 | 2198 | 0.6263 | 0.1991 | 0.0211 | 0.0112 | 0.1668 |
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+ | 0.3521 | 15.0 | 2355 | 0.6313 | 0.1970 | 0.0206 | 0.0116 | 0.1649 |
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+ | 0.348 | 16.0 | 2512 | 0.6307 | 0.2001 | 0.0204 | 0.0123 | 0.1673 |
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+ | 0.3668 | 17.0 | 2669 | 0.6425 | 0.2012 | 0.0206 | 0.0124 | 0.1682 |
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+ | 0.3592 | 18.0 | 2826 | 0.6328 | 0.2001 | 0.0205 | 0.0124 | 0.1672 |
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+ | 0.3485 | 19.0 | 2983 | 0.6489 | 0.2006 | 0.0202 | 0.0128 | 0.1675 |
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+ | 0.3529 | 20.0 | 3140 | 0.6501 | 0.2007 | 0.0206 | 0.0123 | 0.1678 |
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+ | 0.35 | 21.0 | 3297 | 0.6473 | 0.2003 | 0.0205 | 0.0124 | 0.1674 |
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+ | 0.3549 | 22.0 | 3454 | 0.6518 | 0.2003 | 0.0205 | 0.0126 | 0.1672 |
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+ | 0.3439 | 23.0 | 3611 | 0.6523 | 0.2002 | 0.0204 | 0.0127 | 0.1671 |
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+ | 0.3495 | 24.0 | 3768 | 0.6527 | 0.2002 | 0.0204 | 0.0126 | 0.1672 |
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+ | 0.34 | 25.0 | 3925 | 0.6518 | 0.2003 | 0.0204 | 0.0126 | 0.1673 |
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  ### Framework versions
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