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whitneyten
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whitneyTest

Transformers
TensorBoard
Safetensors
Indonesian
pyannet
speaker-diarization
speaker-segmentation
modality:audio
modality:text
format:parquet
Generated from Trainer
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End of training

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  1. README.md +11 -11
  2. model.safetensors +1 -1
  3. runs/Mar19_02-28-16_8c65687103bb/events.out.tfevents.1742351310.8c65687103bb.1810.0 +2 -2
README.md CHANGED
@@ -25,12 +25,12 @@ 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: 0.3788
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- - Model Preparation Time: 0.0136
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- - Der: 0.1188
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- - False Alarm: 0.0628
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- - Missed Detection: 0.0216
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- - Confusion: 0.0345
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  ## Model description
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@@ -61,11 +61,11 @@ 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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- | 0.6461 | 1.0 | 47 | 0.4021 | 0.0136 | 0.1318 | 0.0649 | 0.0218 | 0.0450 |
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- | 0.5224 | 2.0 | 94 | 0.3720 | 0.0136 | 0.1179 | 0.0632 | 0.0217 | 0.0330 |
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- | 0.4869 | 3.0 | 141 | 0.3716 | 0.0136 | 0.1180 | 0.0636 | 0.0208 | 0.0337 |
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- | 0.4707 | 4.0 | 188 | 0.3707 | 0.0136 | 0.1175 | 0.0622 | 0.0224 | 0.0329 |
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- | 0.4697 | 5.0 | 235 | 0.3788 | 0.0136 | 0.1188 | 0.0628 | 0.0216 | 0.0345 |
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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: 0.3704
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+ - Model Preparation Time: 0.0044
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+ - Der: 0.1155
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+ - False Alarm: 0.0620
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+ - Missed Detection: 0.0226
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+ - Confusion: 0.0309
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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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+ | 0.6461 | 1.0 | 47 | 0.4057 | 0.0044 | 0.1306 | 0.0644 | 0.0200 | 0.0463 |
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+ | 0.5281 | 2.0 | 94 | 0.3752 | 0.0044 | 0.1212 | 0.0624 | 0.0230 | 0.0358 |
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+ | 0.4805 | 3.0 | 141 | 0.3693 | 0.0044 | 0.1140 | 0.0626 | 0.0202 | 0.0312 |
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+ | 0.4664 | 4.0 | 188 | 0.3706 | 0.0044 | 0.1149 | 0.0616 | 0.0229 | 0.0304 |
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+ | 0.4654 | 5.0 | 235 | 0.3704 | 0.0044 | 0.1155 | 0.0620 | 0.0226 | 0.0309 |
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  ### Framework versions
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