| --- |
| 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: 0.5964 |
| - Model Preparation Time: 0.0059 |
| - Der: 0.2071 |
| - False Alarm: 0.0393 |
| - Missed Detection: 0.0410 |
| - Confusion: 0.1268 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:-----------:|:----------------:|:---------:| |
| | 0.7607 | 1.0 | 72 | 0.6580 | 0.0059 | 0.2281 | 0.0444 | 0.0462 | 0.1375 | |
| | 0.6374 | 2.0 | 144 | 0.6117 | 0.0059 | 0.2152 | 0.0385 | 0.0452 | 0.1315 | |
| | 0.5943 | 3.0 | 216 | 0.6168 | 0.0059 | 0.2163 | 0.0431 | 0.0412 | 0.1320 | |
| | 0.5547 | 4.0 | 288 | 0.6026 | 0.0059 | 0.2077 | 0.0401 | 0.0410 | 0.1265 | |
| | 0.5579 | 5.0 | 360 | 0.5964 | 0.0059 | 0.2071 | 0.0393 | 0.0410 | 0.1268 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.49.0 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.4.1 |
| - Tokenizers 0.21.1 |
|
|
