speaker-segmentation-fine-tuned-callhome-jpn
This model is a fine-tuned version of pyannote/speaker-diarization-3.1 on the diarizers-community/callhome dataset. It achieves the following results on the evaluation set:
- Loss: 0.6518
- Der: 0.2003
- False Alarm: 0.0204
- Missed Detection: 0.0126
- Confusion: 0.1673
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Der | False Alarm | Missed Detection | Confusion |
|---|---|---|---|---|---|---|---|
| 0.6084 | 1.0 | 157 | 0.6361 | 0.2140 | 0.0209 | 0.0101 | 0.1829 |
| 0.5157 | 2.0 | 314 | 0.6039 | 0.2079 | 0.0213 | 0.0101 | 0.1765 |
| 0.4718 | 3.0 | 471 | 0.6117 | 0.2094 | 0.0218 | 0.0101 | 0.1775 |
| 0.5069 | 4.0 | 628 | 0.6086 | 0.2129 | 0.0215 | 0.0101 | 0.1813 |
| 0.47 | 5.0 | 785 | 0.5974 | 0.2040 | 0.0215 | 0.0101 | 0.1724 |
| 0.4539 | 6.0 | 942 | 0.6047 | 0.2065 | 0.0219 | 0.0102 | 0.1745 |
| 0.4325 | 7.0 | 1099 | 0.5944 | 0.2009 | 0.0214 | 0.0104 | 0.1691 |
| 0.434 | 8.0 | 1256 | 0.6110 | 0.2059 | 0.0214 | 0.0105 | 0.1740 |
| 0.4199 | 9.0 | 1413 | 0.6045 | 0.2050 | 0.0212 | 0.0106 | 0.1733 |
| 0.4479 | 10.0 | 1570 | 0.6101 | 0.1990 | 0.0212 | 0.0105 | 0.1673 |
| 0.392 | 11.0 | 1727 | 0.6106 | 0.2003 | 0.0208 | 0.0107 | 0.1687 |
| 0.3858 | 12.0 | 1884 | 0.6279 | 0.2009 | 0.0211 | 0.0108 | 0.1689 |
| 0.3686 | 13.0 | 2041 | 0.6279 | 0.1976 | 0.0209 | 0.0114 | 0.1653 |
| 0.3963 | 14.0 | 2198 | 0.6263 | 0.1991 | 0.0211 | 0.0112 | 0.1668 |
| 0.3521 | 15.0 | 2355 | 0.6313 | 0.1970 | 0.0206 | 0.0116 | 0.1649 |
| 0.348 | 16.0 | 2512 | 0.6307 | 0.2001 | 0.0204 | 0.0123 | 0.1673 |
| 0.3668 | 17.0 | 2669 | 0.6425 | 0.2012 | 0.0206 | 0.0124 | 0.1682 |
| 0.3592 | 18.0 | 2826 | 0.6328 | 0.2001 | 0.0205 | 0.0124 | 0.1672 |
| 0.3485 | 19.0 | 2983 | 0.6489 | 0.2006 | 0.0202 | 0.0128 | 0.1675 |
| 0.3529 | 20.0 | 3140 | 0.6501 | 0.2007 | 0.0206 | 0.0123 | 0.1678 |
| 0.35 | 21.0 | 3297 | 0.6473 | 0.2003 | 0.0205 | 0.0124 | 0.1674 |
| 0.3549 | 22.0 | 3454 | 0.6518 | 0.2003 | 0.0205 | 0.0126 | 0.1672 |
| 0.3439 | 23.0 | 3611 | 0.6523 | 0.2002 | 0.0204 | 0.0127 | 0.1671 |
| 0.3495 | 24.0 | 3768 | 0.6527 | 0.2002 | 0.0204 | 0.0126 | 0.1672 |
| 0.34 | 25.0 | 3925 | 0.6518 | 0.2003 | 0.0204 | 0.0126 | 0.1673 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for VarunUOB/speaker-segmentation-fine-tuned-callhome-jpn
Base model
pyannote/speaker-diarization-3.1