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

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speaker-segmentation-fine-tuned-callhome-eng

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

• —Loss: 0.4597
• —Der: 0.1816
• —False Alarm: 0.0595
• —Missed Detection: 0.0708
• —Confusion: 0.0513

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

Training results

Framework versions

• —Transformers 4.40.0
• —Pytorch 2.2.1+cu121
• —Datasets 2.19.0
• —Tokenizers 0.19.1