metadata
license: mit
base_model: pyannote/segmentation-3.0
tags:
- speaker-diarization
- speaker-segmentation
- generated_from_trainer
datasets:
- diarizers-community/callhome
model-index:
- name: speaker-segmentation-fine-tuned-callhome-eng
results: []
speaker-segmentation-fine-tuned-callhome-eng
This model is a fine-tuned version of pyannote/segmentation-3.0 on the diarizers-community/callhome eng dataset. It achieves the following results on the evaluation set:
- Loss: 0.4632
- Der: 0.1810
- False Alarm: 0.0575
- Missed Detection: 0.0707
- Confusion: 0.0528
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 5.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Der | False Alarm | Missed Detection | Confusion |
|---|---|---|---|---|---|---|---|
| 0.4223 | 1.0 | 362 | 0.4718 | 0.1890 | 0.0617 | 0.0724 | 0.0549 |
| 0.3832 | 2.0 | 724 | 0.4581 | 0.1836 | 0.0561 | 0.0749 | 0.0526 |
| 0.3812 | 3.0 | 1086 | 0.4676 | 0.1846 | 0.0598 | 0.0702 | 0.0546 |
| 0.3607 | 4.0 | 1448 | 0.4610 | 0.1819 | 0.0585 | 0.0701 | 0.0533 |
| 0.3581 | 5.0 | 1810 | 0.4632 | 0.1810 | 0.0575 | 0.0707 | 0.0528 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1