---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- elite_voice_project
metrics:
- wer
model-index:
- name: whisper-small-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: 4.878048780487805
---

<!-- 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-small-ja-elite

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the elite_voice_project dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1502
- Wer: 4.8780

## 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: 16
- eval_batch_size: 8
- 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: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0004        | 58.0  | 1000 | 0.1129          | 1.8293 |
| 0.0           | 117.0 | 2000 | 0.1232          | 1.8293 |
| 0.0           | 176.0 | 3000 | 0.1327          | 1.8293 |
| 0.0           | 235.0 | 4000 | 0.1401          | 4.8780 |
| 0.0           | 294.0 | 5000 | 0.1502          | 4.8780 |


### Framework versions

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