---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- speaker-diarization
- speaker-segmentation
- generated_from_trainer
model-index:
- name: speaker-segmentation-eng
  results: []
---


# speaker-segmentation-eng

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: 0.4666
- Der: 0.1827
- False Alarm: 0.0590
- Missed Detection: 0.0715
- Confusion: 0.0522

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
| 0.4224        | 1.0   | 181  | 0.4837          | 0.1939 | 0.0599      | 0.0764           | 0.0576    |
| 0.409         | 2.0   | 362  | 0.4692          | 0.1884 | 0.0618      | 0.0724           | 0.0543    |
| 0.3919        | 3.0   | 543  | 0.4700          | 0.1875 | 0.0638      | 0.0698           | 0.0540    |
| 0.3693        | 4.0   | 724  | 0.4718          | 0.1848 | 0.0602      | 0.0714           | 0.0533    |
| 0.358         | 5.0   | 905  | 0.4606          | 0.1810 | 0.0544      | 0.0754           | 0.0512    |
| 0.355         | 6.0   | 1086 | 0.4631          | 0.1826 | 0.0638      | 0.0677           | 0.0512    |
| 0.3563        | 7.0   | 1267 | 0.4646          | 0.1809 | 0.0587      | 0.0716           | 0.0505    |
| 0.347         | 8.0   | 1448 | 0.4682          | 0.1820 | 0.0581      | 0.0720           | 0.0519    |
| 0.3463        | 9.0   | 1629 | 0.4684          | 0.1827 | 0.0586      | 0.0718           | 0.0523    |
| 0.3299        | 10.0  | 1810 | 0.4666          | 0.1827 | 0.0590      | 0.0715           | 0.0522    |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1