|
--- |
|
language: ja |
|
datasets: |
|
- common_voice |
|
metrics: |
|
- wer |
|
tags: |
|
- audio |
|
- automatic-speech-recognition |
|
- speech |
|
- xlsr-fine-tuning-week |
|
license: apache-2.0 |
|
model-index: |
|
- name: wav2vec2-live-japanese |
|
results: |
|
- task: |
|
name: Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: Common Voice Japanese |
|
type: common_voice |
|
args: ja |
|
metrics: |
|
- name: Test WER |
|
type: wer |
|
value: 22.08% |
|
- name: Test CER |
|
type: cer |
|
value: 10.08% |
|
--- |
|
|
|
# wav2vec2-live-japanese |
|
|
|
https://github.com/ttop32/wav2vec2-live-japanese-translator |
|
Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Japanese using the |
|
- common_voice |
|
- JSUT |
|
- CSS10 |
|
- TEDxJP-10K |
|
- JVS |
|
|
|
## 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: 0.0003 |
|
- train_batch_size: 3 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 6 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 50 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Framework versions |
|
|
|
- Transformers 4.10.0 |
|
- Pytorch 1.9.1 |
|
- Datasets 1.11.0 |
|
- Tokenizers 0.10.3 |
|
|
