---
language:
- en
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small English
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 en
      type: mozilla-foundation/common_voice_11_0
      config: en
      split: test
      args: en
    metrics:
    - name: Wer
      type: wer
      value: 13.058509783761204
---

<!-- 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 English

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 en dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3269
- Wer: 13.0585

## 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: 32
- eval_batch_size: 16
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1537        | 0.1   | 1000  | 0.4405          | 17.9276 |
| 0.2378        | 0.2   | 2000  | 0.4009          | 15.9888 |
| 0.1709        | 0.3   | 3000  | 0.3852          | 15.4953 |
| 0.2792        | 0.4   | 4000  | 0.3699          | 14.8758 |
| 0.2172        | 0.5   | 5000  | 0.3577          | 14.2660 |
| 0.3616        | 0.6   | 6000  | 0.4042          | 18.1846 |
| 0.2456        | 0.7   | 7000  | 0.3375          | 13.3091 |
| 0.2505        | 0.8   | 8000  | 0.3395          | 13.6227 |
| 0.2563        | 0.9   | 9000  | 0.3305          | 13.1408 |
| 0.2395        | 1.0   | 10000 | 0.3269          | 13.0585 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.11.1.dev0
- Tokenizers 0.13.2