syvai/speaker-segmentation

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speaker-segmentation-fine-tuned

This model is a fine-tuned version of pyannote/segmentation-3.0 on the syvai/synthetic-diarization-mixed-speakers dataset. It achieves the following results on the evaluation set:

• —Loss: 0.2088
• —Model Preparation Time: 0.0013
• —Der: 0.0754
• —False Alarm: 0.0218
• —Missed Detection: 0.0180
• —Confusion: 0.0356

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
• —trainbatchsize: 32
• —evalbatchsize: 32
• —seed: 42
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: cosine
• —num_epochs: 5.0

Training results

Framework versions

• —Transformers 4.53.0
• —Pytorch 2.7.1+cu126
• —Datasets 3.6.0
• —Tokenizers 0.21.2