speaker-segmentation-fine-tuned-callhome-hi
This model is a fine-tuned version of pyannote/speaker-diarization-3.1 on the diarizers-community/callhome dataset. It achieves the following results on the evaluation set:
- Loss: 0.5013
- Der: 0.1688
- False Alarm: 0.0283
- Missed Detection: 0.0343
- Confusion: 0.1061
Model description
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Intended uses & limitations
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Training and evaluation data
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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 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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Der | False Alarm | Missed Detection | Confusion |
|---|---|---|---|---|---|---|---|
| 0.475 | 1.0 | 194 | 0.5013 | 0.1688 | 0.0283 | 0.0343 | 0.1061 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for abhimehra8194/speaker-segmentation-fine-tuned-callhome-hindi-3
Base model
pyannote/speaker-diarization-3.1