transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer ja dataset:mozilla-foundation/common_voice_13_0 base_model:openai/whisper-small license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- ja
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Small Ja - Vick
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: 'Common Voice 13 - whisper_small on ASR_JA '
      type: mozilla-foundation/common_voice_13_0
      config: ja
      split: test
      args: ja
    metrics:
    - name: Wer
      type: wer
      value: 622.012752980316
---

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# Whisper Small Ja - Vick

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 - whisper_small on ASR_JA  dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5735
- Wer Ortho: 731.1720
- Wer: 622.0128

## 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: 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: 50
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer       |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:---------:|
| 0.1701        | 1.13  | 500  | 0.4424          | 480.6484  | 2104.7685 |
| 0.0606        | 2.26  | 1000 | 0.4455          | 238.1393  | 1241.4749 |
| 0.0334        | 3.39  | 1500 | 0.4821          | 496.1941  | 1038.0787 |
| 0.0167        | 4.52  | 2000 | 0.4851          | 614.7604  | 1104.6160 |
| 0.0113        | 5.66  | 2500 | 0.5100          | 265.9686  | 457.5270  |
| 0.007         | 6.79  | 3000 | 0.5387          | 338.3004  | 569.8087  |
| 0.0072        | 7.92  | 3500 | 0.5301          | 213.4515  | 597.5880  |
| 0.005         | 9.05  | 4000 | 0.5735          | 731.1720  | 622.0128  |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
