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--- |
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library_name: transformers |
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license: mit |
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datasets: |
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- Tarakeshwaran/Whisper-train-data |
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language: |
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- en |
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metrics: |
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- wer |
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base_model: |
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- openai/whisper-small |
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pipeline_tag: automatic-speech-recognition |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Whisper Small En - Tarakeshwaran |
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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: minimal_common_voice_en |
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type: Tarakeshwaran/Whisper-train-data |
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args: 'config: en, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 13.170732 |
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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 Small En - Tarakeshwaran |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the minimal_common_voice_en dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.041972 |
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- Wer: 13.170732 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: adamw_bnb_8bit |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 25 |
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- training_steps: 100 |
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- mixed_precision_training: Native AMP |
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### Framework versions |
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- Transformers 4.47.0.dev0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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