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--- |
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language: |
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- ceb |
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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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- nlewins/ceb-sentences-with-audio |
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- nlewins/standard_dataset_nonsynthetic |
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model-index: |
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- name: Whisper finetuned for ceb |
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results: [] |
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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 finetuned for ceb |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co./openai/whisper-small) on the Fleurs Ceb subset, LSK nonsynthetic, Onetalk Q&A, and Ceb sentences dataset dataset. |
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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-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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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: 100 |
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- training_steps: 20000 |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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