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: 13.326167779676846
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: 0.4317
- Wer: 13.3262
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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.042 | 3.03 | 2000 | 0.3056 | 12.9174 |
| 0.0085 | 7.01 | 4000 | 0.3752 | 13.1746 |
| 0.0047 | 10.04 | 6000 | 0.4103 | 13.5817 |
| 0.0042 | 14.01 | 8000 | 0.4202 | 13.5323 |
| 0.0051 | 17.05 | 10000 | 0.4317 | 13.3262 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2