README.md

metadata

language:
  - jpn
license: apache-2.0
base_model: openai/whisper-small
tags:
  - speaker-diarization
  - speaker-segmentation
  - generated_from_trainer
datasets:
  - diarizers-community/callhome
model-index:
  - name: speaker-segmentation-fine-tuned-callhome-jpn
    results: []

speaker-segmentation-fine-tuned-callhome-jpn

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

• eval_loss: 0.8263
• eval_der: 0.2702
• eval_false_alarm: 0.0280
• eval_missed_detection: 0.1843
• eval_confusion: 0.0579
• eval_runtime: 80.4369
• eval_samples_per_second: 8.64
• eval_steps_per_second: 0.274
• step: 0

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

Framework versions

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