---
language:
- dv
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Dv - Mark Redito
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13 - Dhivehi
      type: mozilla-foundation/common_voice_13_0
      config: dv
      split: test
      args: dv
    metrics:
    - name: Wer
      type: wer
      value: 10.863441944570019
---

<!-- 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. -->

# Whisper Small Dv - Mark Redito

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 - Dhivehi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3041
- Wer Ortho: 56.8563
- Wer: 10.8634

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 0.121         | 1.6287  | 500  | 0.1725          | 62.6994   | 13.3481 |
| 0.0435        | 3.2573  | 1000 | 0.1651          | 57.9567   | 11.5659 |
| 0.0296        | 4.8860  | 1500 | 0.1829          | 58.1517   | 11.6076 |
| 0.0071        | 6.5147  | 2000 | 0.2369          | 58.8203   | 11.4198 |
| 0.0016        | 8.1433  | 2500 | 0.2718          | 57.9915   | 11.2129 |
| 0.0011        | 9.7720  | 3000 | 0.2923          | 57.1349   | 11.1242 |
| 0.0002        | 11.4007 | 3500 | 0.3001          | 56.8633   | 10.9173 |
| 0.0002        | 13.0293 | 4000 | 0.3041          | 56.8563   | 10.8634 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1