---
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-10e
  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-10e

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: 0.5210
- Der: 0.1743
- False Alarm: 0.0765
- Missed Detection: 0.0670
- Confusion: 0.0308

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
| 0.6545        | 1.0   | 382  | 0.5338          | 0.1797 | 0.0637      | 0.0805           | 0.0355    |
| 0.6125        | 2.0   | 764  | 0.5097          | 0.1738 | 0.0720      | 0.0692           | 0.0326    |
| 0.6118        | 3.0   | 1146 | 0.5102          | 0.1709 | 0.0588      | 0.0799           | 0.0322    |
| 0.6064        | 4.0   | 1528 | 0.5138          | 0.1707 | 0.0657      | 0.0754           | 0.0296    |
| 0.572         | 5.0   | 1910 | 0.5126          | 0.1727 | 0.0709      | 0.0714           | 0.0304    |
| 0.5671        | 6.0   | 2292 | 0.5161          | 0.1731 | 0.0771      | 0.0654           | 0.0306    |
| 0.533         | 7.0   | 2674 | 0.5143          | 0.1732 | 0.0712      | 0.0715           | 0.0305    |
| 0.551         | 8.0   | 3056 | 0.5207          | 0.1739 | 0.0716      | 0.0717           | 0.0307    |
| 0.5543        | 9.0   | 3438 | 0.5199          | 0.1738 | 0.0756      | 0.0676           | 0.0306    |
| 0.5234        | 10.0  | 3820 | 0.5210          | 0.1743 | 0.0765      | 0.0670           | 0.0308    |


### Framework versions

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