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 Base 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: 21.991788980318223
Whisper Base Japanese
This model is a fine-tuned version of openai/whisper-base on the mozilla-foundation/common_voice_11_0 ja dataset. It achieves the following results on the evaluation set:
- Loss: 0.6532
- Wer: 21.9918
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: 32
- 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3273 | 3.02 | 1000 | 0.4225 | 20.8253 |
| 0.0923 | 7.0 | 2000 | 0.4643 | 21.2200 |
| 0.0164 | 10.02 | 3000 | 0.5403 | 22.9627 |
| 0.006 | 14.01 | 4000 | 0.5820 | 21.0861 |
| 0.0046 | 17.02 | 5000 | 0.5852 | 22.0728 |
| 0.0034 | 21.01 | 6000 | 0.6113 | 21.6623 |
| 0.0028 | 24.03 | 7000 | 0.6582 | 22.3266 |
| 0.0025 | 28.01 | 8000 | 0.6350 | 22.2332 |
| 0.0029 | 32.0 | 9000 | 0.6468 | 22.1098 |
| 0.0014 | 35.02 | 10000 | 0.6532 | 21.9918 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2