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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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- stuttered-speech |
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- speech-recognition |
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- asr |
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- whisper |
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- disfluency |
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- generated_from_trainer |
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datasets: |
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- arielcerdap/TimeStamped |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small Optimized for Stuttered Speech |
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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: TimeStamped |
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type: arielcerdap/TimeStamped |
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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: 15.852285521278992 |
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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 Optimized for Stuttered Speech |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the TimeStamped dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0628 |
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- Wer: 15.8523 |
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- Wer Ortho: 9.0384 |
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- Cer: 9.0083 |
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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: 8e-06 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- training_steps: 8000 |
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- mixed_precision_training: Native AMP |
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- label_smoothing_factor: 0.1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Ortho | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:-------:|:---------:|:-------:| |
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| 1.5552 | 5.8187 | 500 | 1.7178 | 23.1142 | 12.5690 | 12.5620 | |
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| 1.4449 | 11.6316 | 1000 | 1.7658 | 14.3774 | 9.1288 | 9.1103 | |
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| 1.4477 | 17.4444 | 1500 | 1.8778 | 18.3517 | 13.5472 | 13.5171 | |
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| 1.4132 | 23.2573 | 2000 | 1.8607 | 13.6005 | 7.7101 | 7.6846 | |
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| 1.4065 | 29.0702 | 2500 | 1.8845 | 14.4112 | 8.2271 | 8.1993 | |
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| 1.4182 | 34.8889 | 3000 | 1.9307 | 14.4112 | 7.9953 | 7.9675 | |
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| 1.4177 | 40.7018 | 3500 | 1.9481 | 17.6649 | 10.8814 | 10.8535 | |
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| 1.4036 | 46.5146 | 4000 | 1.9508 | 15.2105 | 8.5331 | 8.5076 | |
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| 1.4012 | 52.3275 | 4500 | 1.9831 | 15.4695 | 8.7324 | 8.7069 | |
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| 1.4005 | 58.1404 | 5000 | 2.0116 | 15.6046 | 8.8252 | 8.7973 | |
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| 1.4143 | 63.9591 | 5500 | 2.0306 | 15.6609 | 8.9318 | 8.9040 | |
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| 1.4141 | 69.7719 | 6000 | 2.0445 | 15.7172 | 8.9573 | 8.9295 | |
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| 1.414 | 75.5848 | 6500 | 2.0525 | 15.8410 | 9.0083 | 8.9805 | |
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| 1.3998 | 81.3977 | 7000 | 2.0598 | 15.8523 | 9.0361 | 9.0060 | |
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| 1.3997 | 87.2105 | 7500 | 2.0625 | 15.8635 | 9.0454 | 9.0153 | |
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| 1.3997 | 93.0234 | 8000 | 2.0628 | 15.8523 | 9.0384 | 9.0083 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.4.1 |
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- Tokenizers 0.21.1 |
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