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--- |
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license: apache-2.0 |
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base_model: openai/whisper-medium |
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tags: |
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- generated_from_trainer |
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datasets: |
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- abdouaziiz/wolof_lam_asr |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-m-wo |
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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: abdouaziiz/wolof_lam_asr |
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type: abdouaziiz/wolof_lam_asr |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.2595195074616877 |
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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-m-wo |
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the abdouaziiz/wolof_lam_asr dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4811 |
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- Wer: 0.2595 |
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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: 8 |
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- eval_batch_size: 8 |
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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_steps: 40 |
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- training_steps: 16000 |
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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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| 0.7816 | 0.3912 | 1000 | 0.7274 | 0.6369 | |
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| 0.6368 | 0.7825 | 2000 | 0.6093 | 0.5042 | |
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| 0.3921 | 1.1737 | 3000 | 0.5506 | 0.4280 | |
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| 0.3494 | 1.5649 | 4000 | 0.5247 | 0.3115 | |
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| 0.3264 | 1.9562 | 5000 | 0.4907 | 0.3293 | |
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| 0.1734 | 2.3474 | 6000 | 0.4968 | 0.2973 | |
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| 0.1808 | 2.7387 | 7000 | 0.4811 | 0.2595 | |
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| 0.1064 | 3.1299 | 8000 | 0.4989 | 0.2490 | |
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| 0.0802 | 3.5211 | 9000 | 0.4975 | 0.2275 | |
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| 0.0745 | 3.9124 | 10000 | 0.4883 | 0.2429 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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