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speaker-segmentation-fine-tuned-callhome-jpn – AI Model by Sathyag007 | AlphaNeural AI
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speaker-segmentation-fine-tuned-callhome-jpn
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transformers
safetensors
pyannet
speaker-diarization
speaker-segmentation
generated_from_trainer
diarizers-community/callhome
pyannote/segmentation-3.0
finetune
mit
endpoints_compatible
us
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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.
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: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 5.0
Training results
Framework versions
Transformers 5.14.1
Pytorch 2.13.0+cu130
Datasets 5.0.0
Tokenizers 0.22.2
