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--- |
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language: |
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- ig |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- generated_from_trainer |
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datasets: |
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- google/fleurs |
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- deepdml/igbo-dict-expansion-16khz |
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- deepdml/igbo-dict-16khz |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Base ig |
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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: google/fleurs |
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type: google/fleurs |
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config: ig_ng |
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split: test |
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args: ig_ng |
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metrics: |
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- name: Wer |
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type: wer |
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value: 54.948739128322245 |
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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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# Whisper Base ig |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the google/fleurs dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0933 |
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- Wer: 54.9487 |
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- Cer: 21.3532 |
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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: 1e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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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_ratio: 0.04 |
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- training_steps: 5000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:| |
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| 0.2087 | 0.2 | 1000 | 0.8427 | 54.4143 | 20.1160 | |
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| 0.0734 | 1.0814 | 2000 | 0.9702 | 55.5707 | 21.6200 | |
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| 0.0609 | 1.2814 | 3000 | 1.0272 | 54.0256 | 20.4927 | |
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| 0.0336 | 2.1628 | 4000 | 1.0804 | 54.4337 | 20.4677 | |
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| 0.0341 | 3.0442 | 5000 | 1.0933 | 54.9487 | 21.3532 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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## Citation |
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Please cite the model using the following BibTeX entry: |
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```bibtex |
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@misc{deepdml/whisper-base-ig-mix-norm, |
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title={Fine-tuned Whisper base ASR model for speech recognition in Lingala}, |
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author={Jimenez, David}, |
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howpublished={\url{https://huggingface.co/deepdml/whisper-base-ig-mix-norm}}, |
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year={2025} |
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} |
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``` |
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