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--- |
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library_name: transformers |
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language: |
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- ba |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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tags: |
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- generated_from_trainer |
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datasets: |
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- oza75/bambara-asr |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper-WOLOF-5-hours-ALFFA-dataset |
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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: Bambara-asr |
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type: oza75/bambara-asr |
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args: 'config: ba, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 25.36480142113945 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/asr-africa-research-team/ASR%20Africa/runs/bocacdf7) |
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# Whisper-WOLOF-5-hours-ALFFA-dataset |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Bambara-asr dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5488 |
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- Wer: 25.3648 |
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- Cer: 7.4292 |
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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: 32 |
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- eval_batch_size: 16 |
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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: 0.1 |
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- num_epochs: 50 |
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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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| 1.312 | 3.8760 | 500 | 0.4949 | 33.8409 | 10.1763 | |
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| 0.1965 | 7.7519 | 1000 | 0.4457 | 29.0445 | 8.7321 | |
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| 0.0184 | 11.6279 | 1500 | 0.4554 | 26.4433 | 7.7258 | |
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| 0.0049 | 15.5039 | 2000 | 0.4903 | 27.0143 | 8.0668 | |
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| 0.0024 | 19.3798 | 2500 | 0.4904 | 25.9865 | 7.8505 | |
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| 0.0012 | 23.2558 | 3000 | 0.5039 | 25.4917 | 7.5317 | |
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| 0.0005 | 27.1318 | 3500 | 0.5155 | 25.3140 | 7.5012 | |
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| 0.0003 | 31.0078 | 4000 | 0.5259 | 25.4790 | 7.5234 | |
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| 0.0002 | 34.8837 | 4500 | 0.5339 | 25.3394 | 7.4680 | |
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| 0.0002 | 38.7597 | 5000 | 0.5395 | 25.3267 | 7.4541 | |
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| 0.0002 | 42.6357 | 5500 | 0.5448 | 25.3267 | 7.4375 | |
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| 0.0001 | 46.5116 | 6000 | 0.5488 | 25.3648 | 7.4292 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.1 |
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