---
library_name: transformers
language:
- dv
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- alakxender/dhivehi-audio-kn
metrics:
- wer
model-index:
- name: Whisper Small Dv - Sanchit Gandhi
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Dhivehi Audio Dataset
      type: alakxender/dhivehi-audio-kn
    metrics:
    - name: Wer
      type: wer
      value: 7.089537018152152
---

<!-- 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 - Sanchit Gandhi

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Dhivehi Audio Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1480
- Wer Ortho: 42.2207
- Wer: 7.0895

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|
| 0.0605        | 2.3923  | 500  | 0.0790          | 46.1564   | 7.7177 |
| 0.0281        | 4.7847  | 1000 | 0.0854          | 43.5270   | 7.3792 |
| 0.0085        | 7.1770  | 1500 | 0.1165          | 43.3261   | 7.2649 |
| 0.0051        | 9.5694  | 2000 | 0.1230          | 43.4601   | 7.0120 |
| 0.0031        | 11.9617 | 2500 | 0.1358          | 42.3045   | 6.8937 |
| 0.0025        | 14.3541 | 3000 | 0.1438          | 42.9744   | 6.9957 |
| 0.0035        | 16.7464 | 3500 | 0.1413          | 42.3547   | 6.8040 |
| 0.0017        | 19.1388 | 4000 | 0.1480          | 42.2207   | 7.0895 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.10.0+cu130
- Datasets 4.5.0
- Tokenizers 0.21.4