Whisper Small ig
This model is a fine-tuned version of openai/whisper-small on the google/fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 1.5879
- Wer: 46.1037
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: 1e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1171 | 0.2 | 1000 | 1.2732 | 44.9937 |
| 0.028 | 1.0814 | 2000 | 1.4495 | 46.2251 |
| 0.0277 | 1.2814 | 3000 | 1.4894 | 45.3892 |
| 0.0084 | 2.1628 | 4000 | 1.5629 | 44.6881 |
| 0.0065 | 3.0442 | 5000 | 1.5879 | 46.1037 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
Citation
@misc{deepdml/whisper-small-ig-mix,
title={Fine-tuned Whisper small ASR model for speech recognition in Igbo},
author={Jimenez, David},
howpublished={\url{https://huggingface.co/deepdml/whisper-small-ig-mix}},
year={2025}
}