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--- |
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base_model: facebook/wav2vec2-base |
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license: apache-2.0 |
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metrics: |
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- wer |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: pidgin-wav2vec2-base-960h |
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results: [] |
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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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# pidgin-wav2vec2-base-960h |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the [Nigerian Pidgin](https://huggingface.co/datasets/asr-nigerian-pidgin/nigerian-pidgin-1.0) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0898 |
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- Wer: 0.3966 |
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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: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 3407 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 1000 |
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- num_epochs: 30 |
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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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| 4.3949 | 1.48 | 500 | 3.3325 | 0.9999 | |
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| 2.4656 | 2.95 | 1000 | 1.4727 | 0.8026 | |
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| 1.1896 | 4.43 | 1500 | 1.0925 | 0.6252 | |
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| 0.8558 | 5.91 | 2000 | 0.9467 | 0.5422 | |
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| 0.6427 | 7.39 | 2500 | 0.9856 | 0.5096 | |
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| 0.5371 | 8.86 | 3000 | 0.9794 | 0.5093 | |
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| 0.4553 | 10.34 | 3500 | 0.8719 | 0.4641 | |
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| 0.3921 | 11.82 | 4000 | 0.9344 | 0.4566 | |
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| 0.3406 | 13.29 | 4500 | 1.0211 | 0.4550 | |
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| 0.3046 | 14.77 | 5000 | 0.8668 | 0.4423 | |
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| 0.2651 | 16.25 | 5500 | 1.0384 | 0.4261 | |
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| 0.244 | 17.73 | 6000 | 1.0437 | 0.4296 | |
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| 0.2203 | 19.2 | 6500 | 0.9244 | 0.4228 | |
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| 0.1995 | 20.68 | 7000 | 0.9832 | 0.4165 | |
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| 0.1838 | 22.16 | 7500 | 1.1455 | 0.4112 | |
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| 0.1632 | 23.63 | 8000 | 1.1102 | 0.4102 | |
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| 0.1576 | 25.11 | 8500 | 1.0769 | 0.4044 | |
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| 0.1388 | 26.59 | 9000 | 1.1008 | 0.4013 | |
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| 0.1346 | 28.06 | 9500 | 1.0940 | 0.4000 | |
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| 0.1204 | 29.54 | 10000 | 1.0898 | 0.3966 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.15.2 |
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## Citation |
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@misc{rufai2025endtoendtrainingautomaticspeech, |
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title={Towards End-to-End Training of Automatic Speech Recognition for Nigerian Pidgin}, |
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author={Amina Mardiyyah Rufai and Afolabi Abeeb and Esther Oduntan and Tayo Arulogun and Oluwabukola Adegboro and Daniel Ajisafe}, |
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year={2025}, |
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eprint={2010.11123}, |
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archivePrefix={arXiv}, |
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primaryClass={eess.AS}, |
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url={https://arxiv.org/abs/2010.11123}, |
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} |
