metadata
language:
- ja
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Japanese
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0 ja
type: mozilla-foundation/common_voice_11_0
config: ja
split: test
args: ja
metrics:
- name: Wer
type: wer
value: 13.768684731417652
Whisper Small Japanese
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 ja dataset. It achieves the following results on the evaluation set:
- Loss: 0.2543
- Wer: 13.7687
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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2515 | 1.06 | 200 | 0.2881 | 16.9442 |
| 0.2212 | 2.12 | 400 | 0.2616 | 14.6884 |
| 0.0774 | 4.04 | 600 | 0.2543 | 13.7687 |
| 0.0564 | 5.09 | 800 | 0.2731 | 13.9769 |
| 0.0221 | 7.01 | 1000 | 0.2814 | 13.9700 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2