---
language:
- en
license: apache-2.0
base_model: openai/whisper-small
tags:
- speaker-diarization
- speaker-segmentation
- generated_from_trainer
datasets:
- diarizers-community/ami_speaker_diarization_dataset
model-index:
- name: speaker-segmentation-fine-tuned-ami-speaker-diarization
  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-ami-speaker-diarization

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the diarizers-community/ami_speaker_diarization_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4425
- Der: 0.1760
- False Alarm: 0.0627
- Missed Detection: 0.0634
- Confusion: 0.0499

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
| 0.3957        | 1.0   | 1809 | 0.4538          | 0.1799 | 0.0605      | 0.0656           | 0.0537    |
| 0.4027        | 2.0   | 3618 | 0.4446          | 0.1780 | 0.0645      | 0.0627           | 0.0508    |
| 0.3639        | 3.0   | 5427 | 0.4504          | 0.1798 | 0.0669      | 0.0604           | 0.0524    |
| 0.3764        | 4.0   | 7236 | 0.4431          | 0.1762 | 0.0632      | 0.0623           | 0.0508    |
| 0.3916        | 5.0   | 9045 | 0.4425          | 0.1760 | 0.0627      | 0.0634           | 0.0499    |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.19.1