NoahDrisort/speaker-segmentation-fine-tuned-callhome-jpn

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speaker-segmentation-fine-tuned-callhome-jpn

This model is a fine-tuned version of pyannote/segmentation-3.0 on the diarizers-community/callhome jpn dataset. It achieves the following results on the evaluation set:

• —Loss: 0.4828
• —Der: 0.1446
• —False Alarm: 0.0404
• —Missed Detection: 0.0606
• —Confusion: 0.0435

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: cosine
• —num_epochs: 5.0

Training results

Framework versions

• —Transformers 4.40.1
• —Pytorch 2.2.2+cu118
• —Datasets 2.18.0
• —Tokenizers 0.19.1