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End of training

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README.md CHANGED
@@ -22,12 +22,12 @@ 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 speaker-segmentation dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4833
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- - Model Preparation Time: 0.014
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- - Der: 0.1592
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- - False Alarm: 0.0257
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- - Missed Detection: 0.0139
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- - Confusion: 0.1196
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  ## Model description
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@@ -58,11 +58,11 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der | False Alarm | Missed Detection | Confusion |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:-----------:|:----------------:|:---------:|
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- | 0.4966 | 1.0 | 104 | 0.5339 | 0.014 | 0.1742 | 0.0272 | 0.0153 | 0.1317 |
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- | 0.4372 | 2.0 | 208 | 0.4908 | 0.014 | 0.1606 | 0.0257 | 0.0139 | 0.1210 |
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- | 0.4143 | 3.0 | 312 | 0.4868 | 0.014 | 0.1607 | 0.0251 | 0.0146 | 0.1211 |
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- | 0.3953 | 4.0 | 416 | 0.4840 | 0.014 | 0.1600 | 0.0258 | 0.0138 | 0.1204 |
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- | 0.3828 | 5.0 | 520 | 0.4833 | 0.014 | 0.1592 | 0.0257 | 0.0139 | 0.1196 |
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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 speaker-segmentation dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3831
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+ - Model Preparation Time: 0.0038
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+ - Der: 0.1279
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+ - False Alarm: 0.0209
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+ - Missed Detection: 0.0105
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+ - Confusion: 0.0965
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der | False Alarm | Missed Detection | Confusion |
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  |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:-----------:|:----------------:|:---------:|
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+ | 0.4394 | 1.0 | 570 | 0.4349 | 0.0038 | 0.1462 | 0.0209 | 0.0115 | 0.1138 |
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+ | 0.3989 | 2.0 | 1140 | 0.4134 | 0.0038 | 0.1385 | 0.0211 | 0.0107 | 0.1067 |
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+ | 0.3797 | 3.0 | 1710 | 0.3871 | 0.0038 | 0.1302 | 0.0211 | 0.0104 | 0.0986 |
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+ | 0.3518 | 4.0 | 2280 | 0.3817 | 0.0038 | 0.1263 | 0.0209 | 0.0106 | 0.0948 |
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+ | 0.3269 | 5.0 | 2850 | 0.3831 | 0.0038 | 0.1279 | 0.0209 | 0.0105 | 0.0965 |
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  ### Framework versions
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