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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: 6.286946013912929 |
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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: 0.1269 |
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- Wer: 6.2869 |
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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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| 1.2361 | 0.2825 | 100 | 1.0425 | 10.4870 | |
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| 0.6631 | 0.5650 | 200 | 0.6451 | 9.4908 | |
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| 0.419 | 0.8475 | 300 | 0.3854 | 8.5535 | |
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| 0.1538 | 1.1299 | 400 | 0.1895 | 7.2635 | |
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| 0.1234 | 1.4124 | 500 | 0.1644 | 6.8454 | |
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| 0.1134 | 1.6949 | 600 | 0.1470 | 6.6201 | |
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| 0.1071 | 1.9774 | 700 | 0.1358 | 6.0289 | |
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| 0.0721 | 2.2599 | 800 | 0.1329 | 6.1302 | |
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| 0.0693 | 2.5424 | 900 | 0.1299 | 6.3065 | |
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| 0.0635 | 2.8249 | 1000 | 0.1275 | 6.5025 | |
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| 0.0441 | 3.1073 | 1100 | 0.1269 | 6.2869 | |
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### Framework versions |
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- Transformers 4.43.3 |
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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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