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--- |
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language: ru |
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datasets: |
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- mozilla-foundation/common_voice_8_0 |
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metrics: |
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- wer |
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- cer |
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tags: |
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- audio |
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- automatic-speech-recognition |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- mozilla-foundation/common_voice_8_0 |
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- robust-speech-event |
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- speech |
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model-index: |
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- name: XLS-R 1B Wav2Vec2 Russian by Rasmus Toivanen |
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results: |
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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: Common Voice 8 |
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type: mozilla-foundation/common_voice_8_0 |
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args: ru |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 10.83 |
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- name: Test CER |
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type: cer |
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value: 2.41 |
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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 - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: ru |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 37.71 |
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- name: Test CER |
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type: cer |
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value: 12.98 |
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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: ru |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 31.89 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# wav2vec2-xlsr-1b-ru |
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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 the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1352 |
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- Wer: 0.0971 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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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: 32 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 500 |
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- num_epochs: 10 |
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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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 0.5462 | 0.35 | 500 | 0.4027 | 0.3575 | |
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| 0.498 | 0.69 | 1000 | 0.2588 | 0.2513 | |
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| 0.4279 | 1.04 | 1500 | 0.2265 | 0.2204 | |
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| 0.4099 | 1.38 | 2000 | 0.2189 | 0.1979 | |
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| 0.4688 | 1.73 | 2500 | 0.2100 | 0.1920 | |
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| 0.2241 | 2.07 | 3000 | 0.1980 | 0.1767 | |
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| 0.2056 | 2.42 | 3500 | 0.2020 | 0.1683 | |
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| 0.3423 | 2.76 | 4000 | 0.1862 | 0.1606 | |
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| 0.2478 | 3.11 | 4500 | 0.1787 | 0.1563 | |
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| 0.3079 | 3.45 | 5000 | 0.1759 | 0.1555 | |
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| 0.2477 | 3.8 | 5500 | 0.1713 | 0.1423 | |
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| 0.1718 | 4.14 | 6000 | 0.1695 | 0.1391 | |
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| 0.1675 | 4.49 | 6500 | 0.1677 | 0.1372 | |
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| 0.1631 | 4.83 | 7000 | 0.1652 | 0.1333 | |
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| 0.1429 | 5.18 | 7500 | 0.1605 | 0.1308 | |
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| 0.1505 | 5.52 | 8000 | 0.1612 | 0.1245 | |
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| 0.1385 | 5.87 | 8500 | 0.1487 | 0.1225 | |
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| 0.1285 | 6.22 | 9000 | 0.1526 | 0.1201 | |
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| 0.1153 | 6.56 | 9500 | 0.1464 | 0.1172 | |
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| 0.1159 | 6.91 | 10000 | 0.1505 | 0.1143 | |
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| 0.1061 | 7.25 | 10500 | 0.1444 | 0.1106 | |
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| 0.1016 | 7.6 | 11000 | 0.1427 | 0.1075 | |
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| 0.1125 | 7.94 | 11500 | 0.1386 | 0.1045 | |
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| 0.0937 | 8.29 | 12000 | 0.1403 | 0.1022 | |
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| 0.1059 | 8.63 | 12500 | 0.1406 | 0.1022 | |
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| 0.0857 | 8.98 | 13000 | 0.1372 | 0.0992 | |
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| 0.0901 | 9.32 | 13500 | 0.1380 | 0.0977 | |
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| 0.0913 | 9.67 | 14000 | 0.1352 | 0.0971 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.0 |
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