Albayzín-RTVE2024
Collection
This collection has the models used for the Albayzín diarization Challenge by the UR team.
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7 items
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Updated
This model is a fine-tuned version of diarizers-community/speaker-segmentation-fine-tuned-callhome-spa on the diarizers-community/callhome dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
Training Loss | Epoch | Step | Validation Loss | Der | False Alarm | Missed Detection | Confusion |
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0.3117 | 1.0 | 281 | 0.3448 | 0.2096 | 0.1526 | 0.0545 | 0.0024 |
0.2973 | 2.0 | 562 | 0.3260 | 0.1961 | 0.1359 | 0.0601 | 0.0001 |
0.2937 | 3.0 | 843 | 0.3413 | 0.2027 | 0.1468 | 0.0555 | 0.0004 |
0.2953 | 4.0 | 1124 | 0.3466 | 0.2023 | 0.1467 | 0.0555 | 0.0000 |
0.2725 | 5.0 | 1405 | 0.3513 | 0.2029 | 0.1480 | 0.0549 | 0.0000 |
Base model
pyannote/segmentation-3.0