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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_0_check_training |
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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_0_check_training |
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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: 6.0845332094751505 |
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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: 0.1019 |
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- Wer: 6.0845 |
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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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| 1.8606 | 1.0101 | 100 | 1.6059 | 9.1965 | |
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| 1.0954 | 2.0202 | 200 | 1.0513 | 6.2935 | |
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| 0.6627 | 3.0303 | 300 | 0.6161 | 6.6187 | |
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| 0.1747 | 4.0404 | 400 | 0.1527 | 4.2034 | |
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| 0.0554 | 5.0505 | 500 | 0.0924 | 5.3182 | |
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| 0.028 | 6.0606 | 600 | 0.0819 | 4.0641 | |
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| 0.0132 | 7.0707 | 700 | 0.0835 | 5.6897 | |
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| 0.0085 | 8.0808 | 800 | 0.0913 | 5.5504 | |
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| 0.0056 | 9.0909 | 900 | 0.0932 | 5.8059 | |
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| 0.0043 | 10.1010 | 1000 | 0.0982 | 5.8059 | |
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| 0.0023 | 11.1111 | 1100 | 0.0990 | 5.8755 | |
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| 0.0016 | 12.1212 | 1200 | 0.1005 | 6.0149 | |
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| 0.0015 | 13.1313 | 1300 | 0.1015 | 6.0613 | |
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| 0.0016 | 14.1414 | 1400 | 0.1017 | 6.0613 | |
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| 0.0015 | 15.1515 | 1500 | 0.1019 | 6.0845 | |
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### Framework versions |
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- Transformers 4.42.4 |
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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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