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---
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: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# speaker-segmentation-fine-tuned-callhome-jpn
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/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
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