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:
type: automatic-speech-recognition
name: 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:
- type: wer
value: 13.467905405405405
name: Wer
- type: cer
value: 8.6022
name: Cer
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: ja_jp
split: test
metrics:
- type: wer
value: 21.46
name: WER
- type: cer
value: 13.65
name: CER
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: 0.4232
- Wer: 13.4679
- Cer: 8.6022
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.0167 | 7.0 | 1000 | 0.3066 | 13.6740 | 8.5733 |
| 0.0021 | 14.01 | 2000 | 0.3579 | 13.8733 | 8.7816 |
| 0.0006 | 21.01 | 3000 | 0.4025 | 13.5794 | 8.6173 |
| 0.0004 | 28.01 | 4000 | 0.4232 | 13.4679 | 8.6022 |
| 0.0004 | 35.01 | 5000 | 0.4319 | 13.4747 | 8.6213 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2