---
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 - Ruhullah Shaikh
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13
      type: mozilla-foundation/common_voice_13_0
      config: dv
      split: test
      args: dv
    metrics:
    - name: Wer
      type: wer
      value: 10.97645790590117
---

<!-- 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 - Ruhullah Shaikh

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3049
- Wer Ortho: 57.3995
- Wer: 10.9765

## 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: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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     |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 0.1224        | 1.6313  | 500  | 0.1725          | 63.0197   | 13.4872 |
| 0.0448        | 3.2626  | 1000 | 0.1690          | 58.1378   | 11.5189 |
| 0.0297        | 4.8940  | 1500 | 0.1814          | 60.0251   | 11.5450 |
| 0.006         | 6.5253  | 2000 | 0.2352          | 58.2701   | 11.3503 |
| 0.0018        | 8.1566  | 2500 | 0.2639          | 58.3676   | 11.1364 |
| 0.0008        | 9.7879  | 3000 | 0.2888          | 57.7686   | 11.0738 |
| 0.0002        | 11.4192 | 3500 | 0.3015          | 57.3369   | 10.9938 |
| 0.0002        | 13.0506 | 4000 | 0.3049          | 57.3995   | 10.9765 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1