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--- |
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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-tiny.en |
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tags: |
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- generated_from_trainer |
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datasets: |
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- Dev372/Medical_STT_Dataset_1.1 |
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metrics: |
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- wer |
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model-index: |
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- name: English Whisper Model |
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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: Medical |
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type: Dev372/Medical_STT_Dataset_1.1 |
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args: 'split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 6.554753584375714 |
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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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# English Whisper Model |
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This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the Medical dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1509 |
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- Wer: 6.5548 |
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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: 18 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 1500 |
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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 | |
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|:-------------:|:------:|:----:|:---------------:|:-------:| |
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| 1.3263 | 0.2825 | 100 | 1.1474 | 12.0219 | |
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| 0.8292 | 0.5650 | 200 | 0.8086 | 9.9840 | |
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| 0.5971 | 0.8475 | 300 | 0.5736 | 9.0597 | |
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| 0.2888 | 1.1299 | 400 | 0.3038 | 8.2465 | |
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| 0.172 | 1.4124 | 500 | 0.2112 | 7.5835 | |
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| 0.1499 | 1.6949 | 600 | 0.1839 | 7.0773 | |
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| 0.1347 | 1.9774 | 700 | 0.1693 | 6.6691 | |
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| 0.0977 | 2.2599 | 800 | 0.1650 | 6.7834 | |
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| 0.0966 | 2.5424 | 900 | 0.1578 | 7.0381 | |
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| 0.0877 | 2.8249 | 1000 | 0.1542 | 6.6462 | |
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| 0.0587 | 3.1073 | 1100 | 0.1539 | 6.5090 | |
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| 0.0642 | 3.3898 | 1200 | 0.1531 | 6.5646 | |
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| 0.0597 | 3.6723 | 1300 | 0.1518 | 6.5090 | |
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| 0.0754 | 3.9548 | 1400 | 0.1511 | 6.5254 | |
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| 0.0506 | 4.2373 | 1500 | 0.1509 | 6.5548 | |
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### Framework versions |
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- Transformers 4.43.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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