kamilakesbi
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speaker-segmentation-fine-tuned-callhome-jpn

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kamilakesbi commited on Apr 26

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 This model is a fine-tuned version of [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the diarizers-community/callhome jpn dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7498
-- Der: 0.2258
-- False Alarm: 0.0470
-- Missed Detection: 0.1339
-- Confusion: 0.0449
 ## Model description
@@ -54,11 +54,11 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
-| 0.5797        | 1.0   | 328  | 0.7543          | 0.2334 | 0.0582      | 0.1277           | 0.0476    |
-| 0.5578        | 2.0   | 656  | 0.7684          | 0.2306 | 0.0446      | 0.1401           | 0.0458    |
-| 0.5213        | 3.0   | 984  | 0.7569          | 0.2289 | 0.0463      | 0.1368           | 0.0459    |
-| 0.4971        | 4.0   | 1312 | 0.7448          | 0.2273 | 0.0489      | 0.1329           | 0.0456    |
-| 0.5026        | 5.0   | 1640 | 0.7498          | 0.2258 | 0.0470      | 0.1339           | 0.0449    |
 ### Framework versions

 This model is a fine-tuned version of [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the diarizers-community/callhome jpn dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.7433
+- Der: 0.2234
+- False Alarm: 0.0478
+- Missed Detection: 0.1328
+- Confusion: 0.0428
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.5771        | 1.0   | 328  | 0.7534          | 0.2321 | 0.0564      | 0.1261           | 0.0496    |
+| 0.5388        | 2.0   | 656  | 0.7503          | 0.2261 | 0.0485      | 0.1347           | 0.0429    |
+| 0.5061        | 3.0   | 984  | 0.7486          | 0.2248 | 0.0475      | 0.1350           | 0.0423    |
+| 0.4883        | 4.0   | 1312 | 0.7374          | 0.2227 | 0.0492      | 0.1315           | 0.0421    |
+| 0.493         | 5.0   | 1640 | 0.7433          | 0.2234 | 0.0478      | 0.1328           | 0.0428    |
 ### Framework versions

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