---
license: mit
base_model: pyannote/segmentation-3.0
tags:
- speaker-diarization
- speaker-segmentation
- generated_from_trainer
datasets:
- ArtFair/diarizers_dataset_70-15-15
model-index:
- name: fine_tuned_segmentation-3.0_1e-5_32
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# fine_tuned_segmentation-3.0_1e-5_32

This model is a fine-tuned version of [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the ArtFair/diarizers_dataset_70-15-15 default dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4908
- Der: 0.3585
- False Alarm: 0.2041
- Missed Detection: 0.1214
- Confusion: 0.0330

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
| 0.621         | 1.0   | 929  | 0.5601          | 0.3774 | 0.2133      | 0.1279           | 0.0361    |
| 0.5472        | 2.0   | 1858 | 0.5149          | 0.3680 | 0.2084      | 0.1254           | 0.0342    |
| 0.5353        | 3.0   | 2787 | 0.4969          | 0.3615 | 0.2049      | 0.1234           | 0.0333    |
| 0.517         | 4.0   | 3716 | 0.4919          | 0.3590 | 0.2042      | 0.1216           | 0.0331    |
| 0.5217        | 5.0   | 4645 | 0.4908          | 0.3585 | 0.2041      | 0.1214           | 0.0330    |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.4.1+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2