---
language:
- ja
license: other
tags:
- whisper-event
- generated_from_trainer
datasets:
- Elite35P-Server/EliteVoiceProject
metrics:
- wer
model-index:
- name: Whisper Small Japanese Elite
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Elite35P-Server/EliteVoiceProject youtube
      type: Elite35P-Server/EliteVoiceProject
      config: youtube
      split: test
      args: youtube
    metrics:
    - name: Wer
      type: wer
      value: 31.536388140161726
---

<!-- 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 Japanese Elite

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Elite35P-Server/EliteVoiceProject youtube dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1596
- Wer: 31.5364

## 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: 100
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0003        | 52.0  | 1000  | 0.8053          | 28.8410 |
| 0.0           | 105.0 | 2000  | 0.8636          | 28.5714 |
| 0.0           | 157.0 | 3000  | 0.9056          | 28.0323 |
| 0.0           | 210.0 | 4000  | 0.9414          | 28.8410 |
| 0.0           | 263.0 | 5000  | 0.9842          | 31.2668 |
| 0.0           | 315.0 | 6000  | 1.0223          | 31.2668 |
| 0.0           | 368.0 | 7000  | 1.0677          | 31.2668 |
| 0.0           | 421.0 | 8000  | 1.1079          | 31.2668 |
| 0.0           | 473.0 | 9000  | 1.1468          | 31.5364 |
| 0.0           | 526.0 | 10000 | 1.1596          | 31.5364 |


### Framework versions

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