---
license: apache-2.0
tags:
- generated_from_trainer
- whisper-event
datasets:
- vumichien/preprocessed_jsut_jsss_css10_common_voice_11
metrics:
- wer
- cer
base_model: openai/whisper-large-v2
model-index:
- name: openai/whisper-large-v2
  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: 7.6453
      name: Wer
    - type: cer
      value: 4.7187
      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: 11.69
      name: WER
    - type: cer
      value: 7.12
      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 vumichien/preprocessed_jsut_jsss_css10_common_voice_11 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2284
- Wer: 7.6453
- Cer: 4.7187

## 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    |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|
| 0.1912        | 0.55  | 1000  | 0.1828          | 11.2314 | 7.0357 |
| 0.1329        | 1.1   | 2000  | 0.1618          | 9.4172  | 5.9028 |
| 0.0912        | 1.65  | 3000  | 0.1616          | 8.9257  | 5.4711 |
| 0.0576        | 2.2   | 4000  | 0.1664          | 8.5861  | 5.3055 |
| 0.0449        | 2.74  | 5000  | 0.1642          | 8.4510  | 5.2930 |
| 0.02          | 3.29  | 6000  | 0.1799          | 8.1537  | 5.0354 |
| 0.019         | 3.84  | 7000  | 0.1801          | 8.125   | 5.0827 |
| 0.0067        | 4.39  | 8000  | 0.2003          | 7.8412  | 4.8133 |
| 0.006         | 4.94  | 9000  | 0.2071          | 7.5811  | 4.7023 |
| 0.0022        | 5.49  | 10000 | 0.2284          | 7.6453  | 4.7187 |


### Framework versions

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