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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- generated_from_trainer |
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datasets: |
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- PolyAI/minds14 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-tiny-en-US |
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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: PolyAI/minds14 |
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type: PolyAI/minds14 |
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config: en-US |
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split: train[450:] |
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args: en-US |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.34946871310507677 |
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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-tiny-en-US |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7334 |
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- Wer Ortho: 0.3701 |
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- Wer: 0.3495 |
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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: 48 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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: 20 |
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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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| 2.5445 | 1.0 | 10 | 2.4472 | 0.5379 | 0.3985 | |
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| 2.0492 | 2.0 | 20 | 1.8586 | 0.5287 | 0.3973 | |
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| 1.3657 | 3.0 | 30 | 1.1065 | 0.4867 | 0.4038 | |
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| 0.6326 | 4.0 | 40 | 0.5885 | 0.4769 | 0.4115 | |
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| 0.3984 | 5.0 | 50 | 0.5155 | 0.4399 | 0.3861 | |
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| 0.2907 | 6.0 | 60 | 0.4921 | 0.3849 | 0.3347 | |
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| 0.236 | 7.0 | 70 | 0.4864 | 0.3886 | 0.3459 | |
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| 0.14 | 8.0 | 80 | 0.4936 | 0.3677 | 0.3264 | |
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| 0.106 | 9.0 | 90 | 0.5082 | 0.3917 | 0.3518 | |
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| 0.0837 | 10.0 | 100 | 0.5316 | 0.3819 | 0.3347 | |
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| 0.0458 | 11.0 | 110 | 0.5475 | 0.3899 | 0.3489 | |
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| 0.0201 | 12.0 | 120 | 0.5706 | 0.3893 | 0.3536 | |
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| 0.0099 | 13.0 | 130 | 0.5851 | 0.3831 | 0.3495 | |
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| 0.0067 | 14.0 | 140 | 0.6010 | 0.3769 | 0.3489 | |
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| 0.0036 | 15.0 | 150 | 0.6196 | 0.3819 | 0.3506 | |
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| 0.0021 | 16.0 | 160 | 0.6377 | 0.3782 | 0.3530 | |
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| 0.0013 | 17.0 | 170 | 0.6539 | 0.3708 | 0.3453 | |
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| 0.0006 | 18.0 | 180 | 0.6831 | 0.3720 | 0.3506 | |
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| 0.0004 | 19.0 | 190 | 0.7018 | 0.3732 | 0.3512 | |
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| 0.0003 | 20.0 | 200 | 0.7334 | 0.3701 | 0.3495 | |
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### Framework versions |
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- Transformers 4.46.1 |
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- Pytorch 2.3.1 |
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- Datasets 3.0.2 |
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- Tokenizers 0.20.1 |
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