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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:
- Loss: 0.4792
- Der: 0.1886
- False Alarm: 0.0606
- Missed Detection: 0.0736
- Confusion: 0.0544
## 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Der | False Alarm | Missed Detection | Confusion |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
| 0.3877 | 1.0 | 362 | 0.4746 | 0.1886 | 0.0603 | 0.0737 | 0.0547 |
| 0.4206 | 2.0 | 724 | 0.4904 | 0.1956 | 0.0656 | 0.0733 | 0.0566 |
| 0.3933 | 3.0 | 1086 | 0.4704 | 0.1855 | 0.0589 | 0.0737 | 0.0529 |
| 0.3708 | 4.0 | 1448 | 0.4759 | 0.1879 | 0.0600 | 0.0739 | 0.0540 |
| 0.3516 | 5.0 | 1810 | 0.4792 | 0.1886 | 0.0606 | 0.0736 | 0.0544 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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