| --- |
| library_name: transformers |
| language: |
| - id |
| license: mit |
| base_model: pyannote/speaker-diarization-3.1 |
| tags: |
| - speaker-diarization |
| - speaker-segmentation |
| - modality:audio |
| - modality:text |
| - format:parquet |
| - generated_from_trainer |
| datasets: |
| - speaker-segmentation |
| model-index: |
| - name: speaker-segmentation-fine-tuned-id |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # speaker-segmentation-fine-tuned-id |
|
|
| 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. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6384 |
| - Model Preparation Time: 0.0039 |
| - Der: 0.2151 |
| - False Alarm: 0.0579 |
| - Missed Detection: 0.0412 |
| - Confusion: 0.1160 |
|
|
| ## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der | False Alarm | Missed Detection | Confusion | |
| |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:-----------:|:----------------:|:---------:| |
| | 0.6696 | 1.0 | 151 | 0.6690 | 0.0039 | 0.2248 | 0.0590 | 0.0445 | 0.1214 | |
| | 0.6283 | 2.0 | 302 | 0.6558 | 0.0039 | 0.2187 | 0.0575 | 0.0417 | 0.1196 | |
| | 0.6013 | 3.0 | 453 | 0.6436 | 0.0039 | 0.2159 | 0.0584 | 0.0405 | 0.1170 | |
| | 0.5765 | 4.0 | 604 | 0.6379 | 0.0039 | 0.2135 | 0.0579 | 0.0413 | 0.1142 | |
| | 0.5594 | 5.0 | 755 | 0.6384 | 0.0039 | 0.2151 | 0.0579 | 0.0412 | 0.1160 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.49.0 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.4.1 |
| - Tokenizers 0.21.1 |
|
|
