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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: whisper-base-ja-cv11
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_11_0
      type: common_voice_11_0
      config: ja
      split: test
      args: ja
    metrics:
    - name: Wer
      type: wer
      value: 21.991788980318223
---

<!-- 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-base-ja-cv11

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6532
- Wer: 21.9918

## 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: constant_with_warmup
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.3273        | 3.02  | 1000  | 0.4225          | 20.8253 |
| 0.0923        | 7.0   | 2000  | 0.4643          | 21.2200 |
| 0.0164        | 10.02 | 3000  | 0.5403          | 22.9627 |
| 0.006         | 14.01 | 4000  | 0.5820          | 21.0861 |
| 0.0046        | 17.02 | 5000  | 0.5852          | 22.0728 |
| 0.0034        | 21.01 | 6000  | 0.6113          | 21.6623 |
| 0.0028        | 24.03 | 7000  | 0.6582          | 22.3266 |
| 0.0025        | 28.01 | 8000  | 0.6350          | 22.2332 |
| 0.0029        | 32.0  | 9000  | 0.6468          | 22.1098 |
| 0.0014        | 35.02 | 10000 | 0.6532          | 21.9918 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2