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--- |
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license: apache-2.0 |
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language: |
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- ru |
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tags: |
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- generated_from_trainer |
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- hf-asr-leaderboard |
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- robust-speech-event |
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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-xls-r-300m-Russian-small |
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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 ru |
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type: common_voice |
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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: 48.38 |
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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: 58.25 |
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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: 56.83 |
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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-xls-r-300m-Russian-small |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3514 |
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- Wer: 0.4838 |
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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: 0.0003 |
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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: 2 |
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- total_train_batch_size: 32 |
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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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| 5.512 | 1.32 | 400 | 3.2207 | 1.0 | |
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| 3.1562 | 2.65 | 800 | 3.0166 | 1.0 | |
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| 1.5211 | 3.97 | 1200 | 0.7134 | 0.8275 | |
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| 0.6724 | 5.3 | 1600 | 0.4713 | 0.6402 | |
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| 0.4693 | 6.62 | 2000 | 0.3904 | 0.5668 | |
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| 0.3693 | 7.95 | 2400 | 0.3609 | 0.5121 | |
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| 0.3004 | 9.27 | 2800 | 0.3514 | 0.4838 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.14.0 |
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- Tokenizers 0.10.3 |
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