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--- |
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language: |
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- ba |
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license: apache-2.0 |
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tags: |
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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_7_0 |
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- robust-speech-event |
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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-large-xls-r-300m-bashkir-cv7_opt |
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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 7 |
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type: mozilla-foundation/common_voice_7_0 |
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args: ba |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 0.04440795062008041 |
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- name: "Test CER" |
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type: "cer" |
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value: 0.010491234992390509 |
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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-large-xls-r-300m-bashkir-cv7_opt |
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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 MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - BA dataset. |
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It achieves the following results on the evaluation set: |
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- Training Loss: 0.268400 |
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- Validation Loss: 0.088252 |
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- WER without LM: 0.085588 |
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- WER with LM: 0.04440795062008041 |
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- CER with LM: 0.010491234992390509 |
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## Model description |
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Trained with this [jupiter notebook](https://drive.google.com/file/d/1KohDXZtKBWXVPZYlsLtqfxJGBzKmTtSh/view?usp=sharing) |
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## Intended uses & limitations |
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In order to reduce the number of characters, the following letters have been replaced or removed: |
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- 'я' -> 'йа' |
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- 'ю' -> 'йу' |
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- 'ё' -> 'йо' |
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- 'е' -> 'йэ' for first letter |
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- 'е' -> 'э' for other cases |
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- 'ъ' -> deleted |
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- 'ь' -> deleted |
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Therefore, in order to get the correct text, you need to do the reverse transformation and use the language model. |
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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: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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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: 300 |
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- num_epochs: 50 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.16.1 |
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- Pytorch 1.10.0+cu113 |
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- Datasets 1.18.2 |
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- Tokenizers 0.10.3 |
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