---
language:
- en
base_model: openai/wav2vec2
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: BANG WAV2VEC v1 (EN)
  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: en
      split: test
      args: 'config: en, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 99.57036953835787
---

<!-- 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 WAV2VEC v1 (EN)

This model is a fine-tuned version of [openai/wav2vec2](https://huggingface.co/openai/wav2vec2) on the Radio-Modified Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 261.3464
- Wer: 99.5704

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 500
- training_steps: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 206.0696      | 0.1667 | 1000 | 368.4753        | 98.1649 |
| 164.236       | 0.3333 | 2000 | 310.1212        | 98.1649 |
| 168.343       | 0.5    | 3000 | 299.5959        | 98.1649 |
| 165.9723      | 0.6667 | 4000 | 293.7289        | 98.1635 |
| 155.8457      | 0.8333 | 5000 | 265.2044        | 98.1635 |
| 155.6296      | 1.0    | 6000 | 261.3464        | 99.5704 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1