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--- |
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library_name: transformers |
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language: |
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- en |
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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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- mozilla-foundation/common_voice_13_0 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Finetune - IERG4320 Project |
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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: Common Voice 13 |
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type: mozilla-foundation/common_voice_13_0 |
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config: en |
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split: None |
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args: en |
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metrics: |
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- name: Wer |
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type: wer |
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value: 15.386343216531895 |
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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 Finetune - IERG4320 Project |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3882 |
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- Wer Ortho: 19.0538 |
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- Wer: 15.3863 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: constant_with_warmup |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 3 |
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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 Ortho | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:| |
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| 0.2577 | 0.9994 | 786 | 0.3589 | 18.3396 | 14.9067 | |
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| 0.1716 | 2.0 | 1573 | 0.3671 | 18.6104 | 14.9992 | |
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| 0.1058 | 2.9981 | 2358 | 0.3882 | 19.0538 | 15.3863 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.5.1 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.4 |
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