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---
base_model: facebook/wav2vec2-base
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: pidgin-wav2vec2-base-960h
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# pidgin-wav2vec2-base-960h
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.
It achieves the following results on the evaluation set:
- Loss: 1.0898
- Wer: 0.3966
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 3407
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.3949 | 1.48 | 500 | 3.3325 | 0.9999 |
| 2.4656 | 2.95 | 1000 | 1.4727 | 0.8026 |
| 1.1896 | 4.43 | 1500 | 1.0925 | 0.6252 |
| 0.8558 | 5.91 | 2000 | 0.9467 | 0.5422 |
| 0.6427 | 7.39 | 2500 | 0.9856 | 0.5096 |
| 0.5371 | 8.86 | 3000 | 0.9794 | 0.5093 |
| 0.4553 | 10.34 | 3500 | 0.8719 | 0.4641 |
| 0.3921 | 11.82 | 4000 | 0.9344 | 0.4566 |
| 0.3406 | 13.29 | 4500 | 1.0211 | 0.4550 |
| 0.3046 | 14.77 | 5000 | 0.8668 | 0.4423 |
| 0.2651 | 16.25 | 5500 | 1.0384 | 0.4261 |
| 0.244 | 17.73 | 6000 | 1.0437 | 0.4296 |
| 0.2203 | 19.2 | 6500 | 0.9244 | 0.4228 |
| 0.1995 | 20.68 | 7000 | 0.9832 | 0.4165 |
| 0.1838 | 22.16 | 7500 | 1.1455 | 0.4112 |
| 0.1632 | 23.63 | 8000 | 1.1102 | 0.4102 |
| 0.1576 | 25.11 | 8500 | 1.0769 | 0.4044 |
| 0.1388 | 26.59 | 9000 | 1.1008 | 0.4013 |
| 0.1346 | 28.06 | 9500 | 1.0940 | 0.4000 |
| 0.1204 | 29.54 | 10000 | 1.0898 | 0.3966 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.15.2
## Citation
@misc{rufai2025endtoendtrainingautomaticspeech,
title={Towards End-to-End Training of Automatic Speech Recognition for Nigerian Pidgin},
author={Amina Mardiyyah Rufai and Afolabi Abeeb and Esther Oduntan and Tayo Arulogun and Oluwabukola Adegboro and Daniel Ajisafe},
year={2025},
eprint={2010.11123},
archivePrefix={arXiv},
primaryClass={eess.AS},
url={https://arxiv.org/abs/2010.11123},
} |