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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-large-v3 |
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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 Large V3 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: 10.391803647827066 |
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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 Large V3 Optimized for Stuttered Speech |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the TimeStamped dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8521 |
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- Wer: 10.3918 |
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- Wer Ortho: 5.5937 |
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- Cer: 5.5914 |
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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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| 1.4877 | 5.8187 | 500 | 1.6643 | 12.9475 | 7.3346 | 7.4041 | |
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| 1.4373 | 11.6316 | 1000 | 1.6887 | 14.1410 | 9.0894 | 9.1010 | |
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| 1.4112 | 17.4444 | 1500 | 1.7115 | 10.0203 | 5.5033 | 5.5149 | |
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| 1.4089 | 23.2573 | 2000 | 1.7320 | 9.7838 | 5.4036 | 5.4129 | |
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| 1.4085 | 29.0702 | 2500 | 1.7222 | 10.0090 | 5.3503 | 5.3572 | |
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| 1.4176 | 34.8889 | 3000 | 1.7498 | 11.8442 | 7.0101 | 7.0101 | |
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| 1.4162 | 40.7018 | 3500 | 1.7794 | 11.7654 | 6.9683 | 6.9683 | |
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| 1.4045 | 46.5146 | 4000 | 1.7699 | 12.1031 | 7.1074 | 7.1051 | |
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| 1.401 | 52.3275 | 4500 | 1.7946 | 12.0919 | 7.1468 | 7.1445 | |
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| 1.4007 | 58.1404 | 5000 | 1.8018 | 9.9527 | 5.3966 | 5.3943 | |
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| 1.4145 | 63.9591 | 5500 | 1.8229 | 10.2342 | 5.5079 | 5.5056 | |
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| 1.4142 | 69.7719 | 6000 | 1.8371 | 10.3468 | 5.5566 | 5.5543 | |
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| 1.414 | 75.5848 | 6500 | 1.8430 | 10.3580 | 5.5682 | 5.5659 | |
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| 1.3998 | 81.3977 | 7000 | 1.8494 | 10.3805 | 5.5867 | 5.5844 | |
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| 1.3997 | 87.2105 | 7500 | 1.8516 | 10.3918 | 5.5960 | 5.5937 | |
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| 1.3997 | 93.0234 | 8000 | 1.8521 | 10.3918 | 5.5937 | 5.5914 | |
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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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