---
license: mit
base_model: pyannote/segmentation-3.0
tags:
- speaker-diarization
- speaker-segmentation
- generated_from_trainer
datasets:
- sparkleai/Diarizers_dataset_test
model-index:
- name: Diarizers_finetuned_model_test
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Diarizers_finetuned_model_test

This model is a fine-tuned version of [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the sparkleai/Diarizers_dataset_test default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7692
- Der: 0.2484
- False Alarm: 0.0450
- Missed Detection: 0.0910
- Confusion: 0.1124

## 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: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
| No log        | 1.0   | 6    | 0.8050          | 0.2813 | 0.0708      | 0.1119           | 0.0986    |
| No log        | 2.0   | 12   | 0.7748          | 0.2592 | 0.0547      | 0.0991           | 0.1054    |
| No log        | 3.0   | 18   | 0.7718          | 0.2502 | 0.0447      | 0.0941           | 0.1114    |
| No log        | 4.0   | 24   | 0.7677          | 0.2484 | 0.0448      | 0.0915           | 0.1121    |
| No log        | 5.0   | 30   | 0.7692          | 0.2484 | 0.0450      | 0.0910           | 0.1124    |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1