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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: 6.5482216924132075 |
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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: 0.1566 |
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- Wer: 6.5482 |
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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: 1100 |
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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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| 1.8857 | 0.1554 | 55 | 1.6694 | 13.1520 | |
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| 1.3264 | 0.3107 | 110 | 1.0577 | 11.8358 | |
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| 0.9159 | 0.4661 | 165 | 0.8809 | 10.3857 | |
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| 0.8292 | 0.6215 | 220 | 0.7654 | 9.8893 | |
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| 0.641 | 0.7768 | 275 | 0.6364 | 9.2557 | |
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| 0.5445 | 0.9322 | 330 | 0.4931 | 8.6417 | |
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| 0.4072 | 1.0876 | 385 | 0.3397 | 8.2759 | |
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| 0.2378 | 1.2429 | 440 | 0.2414 | 8.1322 | |
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| 0.2109 | 1.3983 | 495 | 0.2116 | 7.6684 | |
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| 0.1641 | 1.5537 | 550 | 0.1940 | 7.6423 | |
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| 0.1498 | 1.7090 | 605 | 0.1819 | 7.1198 | |
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| 0.1445 | 1.8644 | 660 | 0.1752 | 6.8095 | |
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| 0.1349 | 2.0198 | 715 | 0.1679 | 6.7181 | |
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| 0.1032 | 2.1751 | 770 | 0.1661 | 6.7344 | |
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| 0.0898 | 2.3305 | 825 | 0.1632 | 6.8291 | |
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| 0.1032 | 2.4859 | 880 | 0.1606 | 6.7278 | |
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| 0.0845 | 2.6412 | 935 | 0.1592 | 6.7083 | |
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| 0.0958 | 2.7966 | 990 | 0.1578 | 6.5743 | |
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| 0.097 | 2.9520 | 1045 | 0.1570 | 6.5515 | |
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| 0.0689 | 3.1073 | 1100 | 0.1566 | 6.5482 | |
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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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