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--- |
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license: apache-2.0 |
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language: |
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- ja |
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tags: |
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- automatic-speech-recognition |
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- robust-speech-event |
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- common-voice |
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- ja |
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datasets: |
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- mozilla-foundation/common_voice_7_0 |
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model-index: |
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- name: wav2vec2-xls-r-1b |
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results: |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 7.0 |
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type: mozilla-foundation/common_voice_7_0 |
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args: ja |
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metrics: |
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- name: Test WER (with LM) |
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type: wer |
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value: 7.98 |
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- name: Test CER (with LM) |
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type: cer |
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value: 3.42 |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 8.0 |
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type: mozilla-foundation/common_voice_8_0 |
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args: ja |
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metrics: |
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- name: Test WER (with LM) |
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type: wer |
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value: 7.88 |
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- name: Test CER (with LM) |
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type: cer |
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value: 3.35 |
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- task: |
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name: Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: ja |
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metrics: |
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- name: Test WER (with LM) |
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type: wer |
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value: 28.07 |
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- name: Test CER (with LM) |
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type: cer |
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value: 16.27 |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Robust Speech Event - Test Data |
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type: speech-recognition-community-v2/eval_data |
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args: ja |
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metrics: |
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- name: Test CER |
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type: cer |
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value: 19.89 |
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--- |
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## Model description |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on my collection of Public Japanese Voice datasets for research [Common Voice 7.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_7_0), [JUST](https://sites.google.com/site/shinnosuketakamichi/publication/jsut) (Japanese speech corpus of Saruwatari-lab., University of Tokyo), [JSSS](https://sites.google.com/site/shinnosuketakamichi/research-topics/jsss_corpus) (Japanese speech corpus for summarization and simplification), [CSS10](https://paperswithcode.com/dataset/css10) (A collection of single speaker speech datasets). You can find in preprocessing dataset in here VUMICHIEN/COMMON_VOICE_LARGE_JSUT_JSSS_CSS10. |
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### Total training data: |
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~60 hours |
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### Benchmark WER result: |
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| | [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) |
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|---|---|---| |
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|without LM| 10.96 | 10.91 | |
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|with 4-grams LM| 7.98 | 7.88 | |
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### Benchmark CER result: |
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| | [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) |
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|---|---|---| |
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|without LM| 4.28 | 4.22 | |
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|with 4-grams LM| 3.42 | 3.35 | |
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## Evaluation |
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Please use the eval.py file to run the evaluation: |
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```python |
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pip install mecab-python3 unidic-lite pykakasi |
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python eval.py --model_id vumichien/wav2vec2-xls-r-1b-japanese --dataset mozilla-foundation/common_voice_7_0 --config ja --split test --chunk_length_s 5.0 --stride_length_s 1.0 --log_outputs |
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``` |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 1000 |
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- num_epochs: 100.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| 2.2896 | 3.37 | 1500 | 0.4748 | 0.4013 | 0.1767 | |
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| 1.1608 | 6.74 | 3000 | 0.3350 | 0.3159 | 0.1456 | |
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| 1.1042 | 10.11 | 4500 | 0.3119 | 0.2971 | 0.1400 | |
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| 1.0494 | 13.48 | 6000 | 0.2974 | 0.2867 | 0.1353 | |
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| 1.0061 | 16.85 | 7500 | 0.2802 | 0.2746 | 0.1300 | |
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| 0.9629 | 20.22 | 9000 | 0.2844 | 0.2776 | 0.1326 | |
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| 0.9267 | 23.59 | 10500 | 0.2577 | 0.2603 | 0.1255 | |
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| 0.8984 | 26.96 | 12000 | 0.2508 | 0.2531 | 0.1226 | |
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| 0.8729 | 30.34 | 13500 | 0.2629 | 0.2606 | 0.1254 | |
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| 0.8546 | 33.71 | 15000 | 0.2402 | 0.2447 | 0.1193 | |
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| 0.8304 | 37.08 | 16500 | 0.2532 | 0.2472 | 0.1209 | |
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| 0.8075 | 40.45 | 18000 | 0.2439 | 0.2469 | 0.1198 | |
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| 0.7827 | 43.82 | 19500 | 0.2387 | 0.2372 | 0.1167 | |
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| 0.7627 | 47.19 | 21000 | 0.2344 | 0.2331 | 0.1147 | |
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| 0.7402 | 50.56 | 22500 | 0.2314 | 0.2299 | 0.1135 | |
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| 0.718 | 53.93 | 24000 | 0.2257 | 0.2267 | 0.1114 | |
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| 0.7016 | 57.3 | 25500 | 0.2204 | 0.2184 | 0.1089 | |
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| 0.6804 | 60.67 | 27000 | 0.2227 | 0.2181 | 0.1085 | |
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| 0.6625 | 64.04 | 28500 | 0.2138 | 0.2112 | 0.1058 | |
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| 0.6465 | 67.42 | 30000 | 0.2141 | 0.2081 | 0.1044 | |
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| 0.6238 | 70.79 | 31500 | 0.2172 | 0.2082 | 0.1050 | |
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| 0.6062 | 74.16 | 33000 | 0.2174 | 0.2058 | 0.1043 | |
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| 0.588 | 77.53 | 34500 | 0.2156 | 0.2034 | 0.1027 | |
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| 0.5722 | 80.9 | 36000 | 0.2162 | 0.2032 | 0.1029 | |
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| 0.5585 | 84.27 | 37500 | 0.2156 | 0.2022 | 0.1021 | |
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| 0.5456 | 87.64 | 39000 | 0.2126 | 0.1993 | 0.1009 | |
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| 0.5325 | 91.01 | 40500 | 0.2121 | 0.1966 | 0.1003 | |
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| 0.5229 | 94.38 | 42000 | 0.2104 | 0.1941 | 0.0991 | |
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| 0.5134 | 97.75 | 43500 | 0.2108 | 0.1948 | 0.0992 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.17.1.dev0 |
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- Tokenizers 0.11.0 |
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