---
library_name: transformers
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 - Leon Lee
  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: 9.938449768751955
---

<!-- 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 - Leon Lee

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: 0.4909
- Wer Ortho: 53.6249
- Wer: 9.9384

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 0.0162        | 6.4935  | 500  | 0.2193          | 57.3020   | 11.4285 |
| 0.0027        | 12.9870 | 1000 | 0.2799          | 55.4287   | 10.4983 |
| 0.0013        | 19.4805 | 1500 | 0.3227          | 55.2824   | 10.5105 |
| 0.0007        | 25.9740 | 2000 | 0.3129          | 54.6069   | 10.4149 |
| 0.0           | 32.4675 | 2500 | 0.3903          | 53.6249   | 9.9680  |
| 0.0           | 38.9610 | 3000 | 0.4478          | 53.6945   | 9.9332  |
| 0.0           | 45.4545 | 3500 | 0.4796          | 53.6458   | 9.9524  |
| 0.0           | 51.9481 | 4000 | 0.4909          | 53.6249   | 9.9384  |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0