---
language:
- ja
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Japanese
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 ja
      type: mozilla-foundation/common_voice_11_0
      config: ja
      split: test
      args: ja
    metrics:
    - type: wer
      value: 13.467905405405405
      name: Wer
    - type: cer
      value: 8.6022
      name: Cer
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: google/fleurs
      type: google/fleurs
      config: ja_jp
      split: test
    metrics:
    - type: wer
      value: 21.46
      name: WER
---

<!-- 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 Japanese

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 ja dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4232
- Wer: 13.4679
- Cer: 8.6022

## 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: 64
- eval_batch_size: 32
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
| 0.0167        | 7.0   | 1000 | 0.3066          | 13.6740 | 8.5733 |
| 0.0021        | 14.01 | 2000 | 0.3579          | 13.8733 | 8.7816 |
| 0.0006        | 21.01 | 3000 | 0.4025          | 13.5794 | 8.6173 |
| 0.0004        | 28.01 | 4000 | 0.4232          | 13.4679 | 8.6022 |
| 0.0004        | 35.01 | 5000 | 0.4319          | 13.4747 | 8.6213 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2