---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- vumichien/preprocessed_jsut_jsss_css10_common_voice_11
metrics:
- wer
base_model: openai/whisper-medium
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: 8.7213
      name: Wer
    - type: cer
      value: 5.4698
      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: 12.825163229350192
      name: WER
    - type: cer
      value: 7.797336057522297
      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 vumichien/preprocessed_jsut_jsss_css10_common_voice_11 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2836
- Wer: 8.7213
- Cer: 5.4698

## 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     | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|
| 0.1106        | 1.1   | 1000  | 0.1827          | 10.3480 | 6.4784 |
| 0.0487        | 2.2   | 2000  | 0.1799          | 9.4764  | 5.9127 |
| 0.0243        | 3.29  | 3000  | 0.1950          | 9.2111  | 5.8069 |
| 0.0106        | 4.39  | 4000  | 0.2113          | 8.9713  | 5.5756 |
| 0.0054        | 5.49  | 5000  | 0.2325          | 8.6470  | 5.4041 |
| 0.0031        | 6.59  | 6000  | 0.2462          | 8.7078  | 5.4409 |
| 0.0014        | 7.68  | 7000  | 0.2608          | 8.7145  | 5.4849 |
| 0.0009        | 8.78  | 8000  | 0.2695          | 8.6301  | 5.3876 |
| 0.0004        | 9.88  | 9000  | 0.2794          | 8.6064  | 5.3528 |
| 0.0003        | 10.98 | 10000 | 0.2836          | 8.7213  | 5.4698 |


### Framework versions

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