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---
license: apache-2.0
language:
- ja
tags:
- automatic-speech-recognition
- robust-speech-event
- common-voice
- ja
model-index:
- name: wav2vec2-large-xlsr-53-ja
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 7.0
type: mozilla-foundation/common_voice_8_0
args: ja
metrics:
- name: Test WER (with LM)
type: wer
value: 15.37
- name: Test CER (with LM)
type: cer
value: 6.91
---
## Model description
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - JA dataset.
### Benchmark WER result:
| | [COMMON VOICE 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) | [COMMON VOICE 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0)
|---|---|---|
|without LM| 15.74 | 25.10 |
|with 4-grams LM| 15.37 | 16.09 |
### Benchmark CER result:
| | [COMMON VOICE 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0) | [COMMON VOICE 8.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0)
|---|---|---|
|without LM| 9.51 | 9.95 |
|with 4-grams LM| 6.91 | 7.15 |
## Evaluation
Please use the eval.py file to run the evaluation:
```python
python eval.py --model_id vutankiet2901/wav2vec2-large-xlsr-53-ja --dataset mozilla-foundation/common_voice_7_0 --config ja --split test --log_outputs
```
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 50.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 4.7776 | 4.73 | 1500 | 2.9540 | 0.9772 | 0.8489 |
| 1.9076 | 9.46 | 3000 | 0.7146 | 0.5371 | 0.2484 |
| 1.507 | 14.2 | 4500 | 0.5843 | 0.4689 | 0.2196 |
| 1.3742 | 18.93 | 6000 | 0.5286 | 0.4321 | 0.1988 |
| 1.2776 | 23.66 | 7500 | 0.5007 | 0.4056 | 0.1870 |
| 1.2003 | 28.39 | 9000 | 0.4676 | 0.3848 | 0.1802 |
| 1.1281 | 33.12 | 10500 | 0.4524 | 0.3694 | 0.1720 |
| 1.0657 | 37.85 | 12000 | 0.4449 | 0.3590 | 0.1681 |
| 1.0129 | 42.59 | 13500 | 0.4266 | 0.3423 | 0.1617 |
| 0.9691 | 47.32 | 15000 | 0.4214 | 0.3375 | 0.1587 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0
|