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--- |
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license: apache-2.0 |
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tags: |
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- audio-classification |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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base_model: openai/whisper-small |
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model-index: |
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- name: whisper-small-keyword-spotting |
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results: [] |
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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-small-keyword-spotting |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the kw-spotting-fsc-sl-agv dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0183 |
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- Accuracy: 0.9998 |
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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: 0.001 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 0 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 5.0 |
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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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| 0.0268 | 1.0 | 318 | 0.0720 | 0.9685 | |
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| 0.0195 | 2.0 | 637 | 0.0183 | 0.9998 | |
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| 0.0111 | 3.0 | 956 | 0.2009 | 0.9168 | |
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| 0.0065 | 4.0 | 1275 | 0.2847 | 0.8544 | |
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| 0.0086 | 4.99 | 1590 | 0.1895 | 0.9168 | |
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### Framework versions |
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- Transformers 4.29.0.dev0 |
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- Pytorch 2.0.0 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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