---
language:
- en
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: BANG - v1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Radio-Modified Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: hi
      split: test
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 3.2167950562939134
---

<!-- 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. -->

# BANG - v1

This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) on the Radio-Modified Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0031
- Wer: 3.2168

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.2164        | 5.0237  | 1000 | 0.1425          | 23.3895 |
| 0.0328        | 11.0023 | 2000 | 0.0373          | 9.2948  |
| 0.0134        | 16.026  | 3000 | 0.0078          | 5.3966  |
| 0.0021        | 22.0045 | 4000 | 0.0031          | 3.2168  |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1