---
language:
- en
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- alxfng/noisycommonvoice
metrics:
- wer
model-index:
- name: Whisper Base Noisy
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Noisy Common Voice
      type: alxfng/noisycommonvoice
      config: en
      split: None
    metrics:
    - name: Wer
      type: wer
      value: 59.32123598390824
---

<!-- 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 Base Noisy

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Noisy Common Voice dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4454
- Wer: 59.3212

## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3125        | 3.19  | 1000 | 1.0918          | 56.8476 |
| 0.0585        | 6.39  | 2000 | 1.2650          | 58.9703 |
| 0.0153        | 9.58  | 3000 | 1.3946          | 58.3412 |
| 0.0066        | 12.78 | 4000 | 1.4454          | 59.3212 |


### Framework versions

- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3