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--- |
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model-index: |
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- name: mHuBERT-147-br |
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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_15_0 |
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type: common_voice_15_0 |
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config: br |
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split: test |
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args: br |
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metrics: |
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- name: WER |
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type: wer |
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value: 47.0 |
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- name: CER |
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type: cer |
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value: 16.7 |
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language: |
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- br |
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metrics: |
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- wer |
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base_model: utter-project/mHuBERT-147 |
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pipeline_tag: automatic-speech-recognition |
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datasets: |
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- mozilla-foundation/common_voice_15_0 |
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--- |
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# mHuBERT-147-br |
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This model is a fine-tuned version of [utter-project/mHuBERT-147](https://huggingface.co/utter-project/mHuBERT-147) on Mozilla Common Voice 15 Breton dataset and [Roadennoù](https://github.com/gweltou/roadennou) dataset. |
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It achieves the following results on the validation set: |
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- Loss: 0.7331 |
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- Wer: 50.09 |
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- Cer: 16.45 |
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## Model description |
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This model was trained to assess the performance mHubert-147 for finetuning a Breton ASR model. |
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## Intended uses & limitations |
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This model is a research model and shouldn't be used in production. |
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## Training and evaluation data |
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90% of the Roadennoù dataset was used for training, the remaining 10% was used for validation in addition to MCV15-br validation dataset. |
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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: 3.8e-05 |
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- train_batch_size: 8 |
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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: 16 |
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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: 52 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.39.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
