---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- elite_voice_project
metrics:
- wer
model-index:
- name: whisper-base-ja-elite
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: elite_voice_project
      type: elite_voice_project
      config: twitter
      split: test
      args: twitter
    metrics:
    - name: Wer
      type: wer
      value: 11.585365853658537
---

<!-- 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-elite

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the elite_voice_project dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1459
- Wer: 11.5854

## 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: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0009        | 29.01 | 1000 | 0.1459          | 11.5854 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2