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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- afrispeech-200 |
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metrics: |
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- wer |
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model-index: |
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- name: afrispeech_large_A100 |
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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: afrispeech-200 |
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type: afrispeech-200 |
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config: all |
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split: train |
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args: all |
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metrics: |
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- name: Wer |
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type: wer |
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value: 14.81 |
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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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# afrispeech_large_A100 |
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the afrispeech-200 dataset. |
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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: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 500 |
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- training_steps: 2000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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https://huggingface.co/Seyfelislem/afrispeech_large_A100/tensorboard |
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### Framework versions |
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- Transformers 4.29.1 |
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- Pytorch 1.13.1 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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