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--- |
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language: |
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- uk |
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license: apache-2.0 |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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model-index: |
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- name: ukrainian-data2vec-asr |
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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 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: uk |
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split: test |
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args: uk |
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metrics: |
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- name: Wer |
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type: wer |
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value: 17.042283338786351 |
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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 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: uk |
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split: validation |
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args: uk |
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metrics: |
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- name: Wer |
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type: wer |
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value: 17.634350000973198 |
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--- |
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# Respeecher/ukrainian-data2vec-asr |
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This model is a fine-tuned version of [Respeecher/ukrainian-data2vec](https://huggingface.co/Respeecher/ukrainian-data2vec) on the [Common Voice 11.0 dataset Ukrainian Train part](https://huggingface.co/datasets/mozilla-foundation/common_voice_11_0/viewer/uk/train). |
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It achieves the following results: |
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- eval_wer: 17.634350000973198 |
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- test_wer: 17.042283338786351 |
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## How to Get Started with the Model |
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```python |
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from transformers import AutoProcessor, Data2VecAudioForCTC |
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import torch |
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from datasets import load_dataset, Audio |
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dataset = load_dataset("mozilla-foundation/common_voice_11_0", "uk", split="test") |
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# Resample |
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dataset = dataset.cast_column("audio", Audio(sampling_rate=16_000)) |
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processor = AutoProcessor.from_pretrained("Respeecher/ukrainian-data2vec-asr") |
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model = Data2VecAudioForCTC.from_pretrained("Respeecher/ukrainian-data2vec-asr") |
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model.eval() |
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sampling_rate = dataset.features["audio"].sampling_rate |
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inputs = processor(dataset[1]["audio"]["array"], sampling_rate=sampling_rate, return_tensors="pt") |
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with torch.no_grad(): |
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logits = model(**inputs).logits |
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predicted_ids = torch.argmax(logits, dim=-1) |
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transcription = processor.batch_decode(predicted_ids) |
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transcription[0] |
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``` |
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## Training Details |
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Training code and instructions are available on [our github](https://github.com/respeecher/ukrainian_asr) |
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