---
language:
- spa
license: apache-2.0
base_model: openai/whisper-small
tags:
- speaker-diarization
- speaker-segmentation
- generated_from_trainer
datasets:
- diarizers-community/callhome
model-index:
- name: mrm8488/speaker-segmentation-fine-tuned-callhome-spa
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mrm8488/speaker-segmentation-fine-tuned-callhome-spa

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: 0.5179
- Der: 0.1717
- False Alarm: 0.0717
- Missed Detection: 0.0687
- Confusion: 0.0312

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
| 0.6432        | 1.0   | 382  | 0.5219          | 0.1750 | 0.0646      | 0.0755           | 0.0349    |
| 0.6133        | 2.0   | 764  | 0.5387          | 0.1821 | 0.0749      | 0.0717           | 0.0356    |
| 0.615         | 3.0   | 1146 | 0.5146          | 0.1729 | 0.0748      | 0.0666           | 0.0315    |
| 0.6268        | 4.0   | 1528 | 0.5220          | 0.1727 | 0.0711      | 0.0690           | 0.0326    |
| 0.6037        | 5.0   | 1910 | 0.5179          | 0.1717 | 0.0717      | 0.0687           | 0.0312    |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1