## Model description

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - JA 

### 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| 16.97 | 17.95 |
|with 4-grams LM| 11.77 | 12.23|
### 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| 6.82 | 7.05 |
|with 4-grams LM| 5.22 | 5.33 |
## Evaluation
Please use the eval.py file to run the evaluation:
```python
pip install mecab-python3 unidic-lite pykakasi
python eval.py --model_id vutankiet2901/wav2vec2-xls-r-1b-ja --dataset mozilla-foundation/common_voice_8_0 --config ja --split test --log_outputs
```

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 100.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 3.484         | 9.49  | 1500  | 1.1849          | 0.7543 | 0.4099 |
| 1.3582        | 18.98 | 3000  | 0.4320          | 0.3489 | 0.1591 |
| 1.1716        | 28.48 | 4500  | 0.3835          | 0.3175 | 0.1454 |
| 1.0951        | 37.97 | 6000  | 0.3732          | 0.3033 | 0.1405 |
| 1.04          | 47.47 | 7500  | 0.3485          | 0.2898 | 0.1360 |
| 0.9768        | 56.96 | 9000  | 0.3386          | 0.2787 | 0.1309 |
| 0.9129        | 66.45 | 10500 | 0.3363          | 0.2711 | 0.1272 |
| 0.8614        | 75.94 | 12000 | 0.3386          | 0.2676 | 0.1260 |
| 0.8092        | 85.44 | 13500 | 0.3356          | 0.2610 | 0.1240 |
| 0.7658        | 94.93 | 15000 | 0.3316          | 0.2564 | 0.1218 |


### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0

{"language": ["ja"], "license": "apache-2.0", "tags": ["automatic-speech-recognition", "common-voice", "hf-asr-leaderboard", "ja", "robust-speech-event"], "datasets": ["mozilla-foundation/common_voice_8_0"], "model-index": [{"name": "wav2vec2-xls-r-1b", "results": [{"task": {"type": "automatic-speech-recognition", "name": "Speech Recognition"}, "dataset": {"name": "Common Voice 7.0", "type": "mozilla-foundation/common_voice_7_0", "args": "ja"}, "metrics": [{"type": "wer", "value": 11.77, "name": "Test WER (with LM)"}, {"type": "cer", "value": 5.22, "name": "Test CER (with LM)"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Speech Recognition"}, "dataset": {"name": "Common Voice 8.0", "type": "mozilla-foundation/common_voice_8_0", "args": "ja"}, "metrics": [{"type": "wer", "value": 12.23, "name": "Test WER (with LM)"}, {"type": "cer", "value": 5.33, "name": "Test CER (with LM)"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Dev Data", "type": "speech-recognition-community-v2/dev_data", "args": "ja"}, "metrics": [{"type": "wer", "value": 29.35, "name": "Test WER (with LM)"}, {"type": "cer", "value": 16.43, "name": "Test CER (with LM)"}]}, {"task": {"type": "automatic-speech-recognition", "name": "Automatic Speech Recognition"}, "dataset": {"name": "Robust Speech Event - Test Data", "type": "speech-recognition-community-v2/eval_data", "args": "ja"}, "metrics": [{"type": "cer", "value": 19.48, "name": "Test CER"}]}]}]}
transformers pytorch tensorboard wav2vec2 automatic-speech-recognition common-voice hf-asr-leaderboard ja robust-speech-event dataset:mozilla-foundation/common_voice_8_0 license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #common-voice #hf-asr-leaderboard #ja #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 

Model description
-----------------


This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON\_VOICE\_8\_0 - JA


### Benchmark WER result:


COMMON VOICE 7.0: without LM, COMMON VOICE 8.0: 16.97
COMMON VOICE 7.0: with 4-grams LM, COMMON VOICE 8.0: 11.77


### Benchmark CER result:


COMMON VOICE 7.0: without LM, COMMON VOICE 8.0: 6.82
COMMON VOICE 7.0: with 4-grams LM, COMMON VOICE 8.0: 5.22


Evaluation
----------


Please use the URL file to run the evaluation:


Training procedure
------------------


### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 100.0
* mixed\_precision\_training: Native AMP


### Training results



### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.18.3
* Tokenizers 0.11.0



### Benchmark WER result:


COMMON VOICE 7.0: without LM, COMMON VOICE 8.0: 16.97
COMMON VOICE 7.0: with 4-grams LM, COMMON VOICE 8.0: 11.77 ### Benchmark CER result:


COMMON VOICE 7.0: without LM, COMMON VOICE 8.0: 6.82
COMMON VOICE 7.0: with 4-grams LM, COMMON VOICE 8.0: 5.22


Evaluation
----------


Please use the URL file to run the evaluation:


Training procedure
------------------ ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 100.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.18.3
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #common-voice #hf-asr-leaderboard #ja #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 ### Benchmark WER result:


COMMON VOICE 7.0: without LM, COMMON VOICE 8.0: 16.97
COMMON VOICE 7.0: with 4-grams LM, COMMON VOICE 8.0: 11.77 ### Benchmark CER result:


COMMON VOICE 7.0: without LM, COMMON VOICE 8.0: 6.82
COMMON VOICE 7.0: with 4-grams LM, COMMON VOICE 8.0: 5.22


Evaluation
----------


Please use the URL file to run the evaluation:


Training procedure
------------------ ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 100.0
* mixed\_precision\_training: Native AMP ### Training results ### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.18.3
* Tokenizers 0.11.0
passage: TAGS
#transformers #pytorch #tensorboard #wav2vec2 #automatic-speech-recognition #common-voice #hf-asr-leaderboard #ja #robust-speech-event #dataset-mozilla-foundation/common_voice_8_0 #license-apache-2.0 #model-index #endpoints_compatible #region-us 
### Benchmark WER result:


COMMON VOICE 7.0: without LM, COMMON VOICE 8.0: 16.97
COMMON VOICE 7.0: with 4-grams LM, COMMON VOICE 8.0: 11.77### Benchmark CER result:


COMMON VOICE 7.0: without LM, COMMON VOICE 8.0: 6.82
COMMON VOICE 7.0: with 4-grams LM, COMMON VOICE 8.0: 5.22


Evaluation
----------


Please use the URL file to run the evaluation:


Training procedure
------------------### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 16
* eval\_batch\_size: 8
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 64
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* lr\_scheduler\_warmup\_steps: 2000
* num\_epochs: 100.0
* mixed\_precision\_training: Native AMP### Training results### Framework versions


* Transformers 4.16.0.dev0
* Pytorch 1.10.1+cu102
* Datasets 1.18.3
* Tokenizers 0.11.0