| --- |
| language: |
| - en |
| license: apache-2.0 |
| base_model: openai/whisper-tiny.en |
| tags: |
| - generated_from_trainer |
| datasets: |
| - Dev372/Medical_STT_Dataset_1.1 |
| metrics: |
| - wer |
| model-index: |
| - name: English Whisper Model |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Medical |
| type: Dev372/Medical_STT_Dataset_1.1 |
| args: 'split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 6.5482216924132075 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # English Whisper Model |
|
|
| This model is a fine-tuned version of [openai/whisper-tiny.en](https://huggingface.co/openai/whisper-tiny.en) on the Medical dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1566 |
| - Wer: 6.5482 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 1e-05 |
| - train_batch_size: 18 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - training_steps: 1100 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Wer | |
| |:-------------:|:------:|:----:|:---------------:|:-------:| |
| | 1.8857 | 0.1554 | 55 | 1.6694 | 13.1520 | |
| | 1.3264 | 0.3107 | 110 | 1.0577 | 11.8358 | |
| | 0.9159 | 0.4661 | 165 | 0.8809 | 10.3857 | |
| | 0.8292 | 0.6215 | 220 | 0.7654 | 9.8893 | |
| | 0.641 | 0.7768 | 275 | 0.6364 | 9.2557 | |
| | 0.5445 | 0.9322 | 330 | 0.4931 | 8.6417 | |
| | 0.4072 | 1.0876 | 385 | 0.3397 | 8.2759 | |
| | 0.2378 | 1.2429 | 440 | 0.2414 | 8.1322 | |
| | 0.2109 | 1.3983 | 495 | 0.2116 | 7.6684 | |
| | 0.1641 | 1.5537 | 550 | 0.1940 | 7.6423 | |
| | 0.1498 | 1.7090 | 605 | 0.1819 | 7.1198 | |
| | 0.1445 | 1.8644 | 660 | 0.1752 | 6.8095 | |
| | 0.1349 | 2.0198 | 715 | 0.1679 | 6.7181 | |
| | 0.1032 | 2.1751 | 770 | 0.1661 | 6.7344 | |
| | 0.0898 | 2.3305 | 825 | 0.1632 | 6.8291 | |
| | 0.1032 | 2.4859 | 880 | 0.1606 | 6.7278 | |
| | 0.0845 | 2.6412 | 935 | 0.1592 | 6.7083 | |
| | 0.0958 | 2.7966 | 990 | 0.1578 | 6.5743 | |
| | 0.097 | 2.9520 | 1045 | 0.1570 | 6.5515 | |
| | 0.0689 | 3.1073 | 1100 | 0.1566 | 6.5482 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.43.2 |
| - Pytorch 2.1.2 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
