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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-small |
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tags: |
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- asr-fyp |
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- generated_from_trainer |
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datasets: |
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- AshtonLKY/Whisper_ASR_ATC |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper_ASR_ATC |
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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: AshtonLKY/augmented_audio |
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type: AshtonLKY/Whisper_ASR_ATC |
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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: 10.259091588129461 |
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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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# Whisper_ASR_ATC |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the AshtonLKY/augmented_audio dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0171 |
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- Wer: 10.2591 |
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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: 16 |
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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: 10000 |
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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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| 0.2282 | 0.3 | 1000 | 0.2253 | 49.5224 | |
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| 0.1461 | 0.6 | 2000 | 0.1456 | 42.3271 | |
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| 0.1052 | 0.89 | 3000 | 0.1061 | 10.8325 | |
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| 0.0698 | 1.19 | 4000 | 0.0708 | 13.8258 | |
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| 0.043 | 1.49 | 5000 | 0.0537 | 11.0072 | |
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| 0.0407 | 1.79 | 6000 | 0.0383 | 10.9401 | |
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| 0.019 | 2.08 | 7000 | 0.0349 | 15.2078 | |
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| 0.0323 | 2.38 | 8000 | 0.0268 | 11.4068 | |
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| 0.0164 | 2.68 | 9000 | 0.0236 | 12.3902 | |
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| 0.0153 | 2.98 | 10000 | 0.0171 | 10.2591 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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