---
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 Medium 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: 9.035472972972974
      name: WER
    - type: cer
      value: 5.61
      name: CER
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: google/fleurs ja_jp
      type: google/fleurs
      config: ja_jp
      split: test
    metrics:
    - type: wer
      value: 13.56
      name: WER
    - type: cer
      value: 8.01
      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-medium

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3029
- Wer: 9.0355

## 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0392        | 3.03  | 1000 | 0.2023          | 10.1807 |
| 0.0036        | 7.01  | 2000 | 0.2478          | 9.4409  |
| 0.0013        | 10.04 | 3000 | 0.2791          | 9.1014  |
| 0.0002        | 14.01 | 4000 | 0.2970          | 9.0625  |
| 0.0002        | 17.04 | 5000 | 0.3029          | 9.0355  |


### Framework versions

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