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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- generated_from_trainer |
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datasets: |
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- speech_commands |
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metrics: |
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- accuracy |
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model-index: |
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- name: whisper-tiny-finetuned-no-go-kws |
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results: |
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- task: |
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name: Audio Classification |
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type: audio-classification |
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dataset: |
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name: Speech Commands[no, go] |
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type: speech_commands |
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config: v0.02 |
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split: test |
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args: v0.02 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.990086741016109 |
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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-tiny-finetuned-no-go-kws |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Speech Commands[no, go] dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0842 |
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- Accuracy: 0.9901 |
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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: 5e-05 |
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- train_batch_size: 8 |
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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_ratio: 0.1 |
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- num_epochs: 10 |
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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 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.33 | 1.0 | 780 | 0.0272 | 0.9938 | |
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| 0.0002 | 2.0 | 1560 | 0.0420 | 0.9876 | |
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| 0.0001 | 3.0 | 2340 | 0.0487 | 0.9913 | |
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| 0.0011 | 4.0 | 3120 | 0.0789 | 0.9802 | |
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| 0.0001 | 5.0 | 3900 | 0.0915 | 0.9851 | |
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| 0.0014 | 6.0 | 4680 | 0.1017 | 0.9839 | |
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| 0.0 | 7.0 | 5460 | 0.0993 | 0.9888 | |
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| 0.0 | 8.0 | 6240 | 0.0694 | 0.9913 | |
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| 0.0 | 9.0 | 7020 | 0.0760 | 0.9926 | |
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| 0.0 | 10.0 | 7800 | 0.0842 | 0.9901 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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