---
language:
- ja
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-large-v2
model-index:
- name: Whisper Large V2 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: 8.1166
      name: Wer
    - type: cer
      value: 5.0032
      name: Cer
---

<!-- 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. -->

# openai/whisper-large-v2

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2352
- Wer: 8.1166
- Cer: 5.0032

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|
| 0.0897        | 0.1   | 1000  | 0.1884          | 11.0068 | 6.6992 |
| 0.0396        | 0.2   | 2000  | 0.1749          | 9.7399  | 5.9350 |
| 0.036         | 1.1   | 3000  | 0.1698          | 9.1419  | 5.6781 |
| 0.012         | 1.2   | 4000  | 0.1849          | 9.3041  | 5.7661 |
| 0.0151        | 2.09  | 5000  | 0.1879          | 9.1959  | 5.6761 |
| 0.0047        | 2.19  | 6000  | 0.2097          | 8.6706  | 5.4422 |
| 0.0046        | 3.09  | 7000  | 0.2040          | 8.8277  | 5.4717 |
| 0.0015        | 3.19  | 8000  | 0.2260          | 8.4949  | 5.3101 |
| 0.0013        | 4.09  | 9000  | 0.2339          | 8.3716  | 5.1471 |
| 0.0005        | 4.19  | 10000 | 0.2352          | 8.1166  | 5.0032 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2