---
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 twitch
      type: Elite35P-Server/EliteVoiceProject
      config: twitch
      split: test
      args: twitch
    metrics:
    - name: Wer
      type: wer
      value: 23.296888141295206
---

<!-- 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 twitch dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9180
- Wer: 23.2969

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.0033        | 18.0  | 1000  | 0.6728          | 25.3154 |
| 0.008         | 37.0  | 2000  | 0.6984          | 23.3810 |
| 0.0002        | 56.0  | 3000  | 0.7486          | 24.4743 |
| 0.0001        | 75.0  | 4000  | 0.7753          | 24.4743 |
| 0.0           | 94.0  | 5000  | 0.8014          | 24.0538 |
| 0.0           | 113.0 | 6000  | 0.8244          | 24.3902 |
| 0.0           | 132.0 | 7000  | 0.8468          | 23.8015 |
| 0.0           | 150.0 | 8000  | 0.8699          | 23.4651 |
| 0.0           | 169.0 | 9000  | 0.8936          | 23.2128 |
| 0.0           | 188.0 | 10000 | 0.9180          | 23.2969 |


### Framework versions

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