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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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datasets: |
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- superb |
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metrics: |
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- accuracy |
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model-index: |
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- name: distilhubert-ft-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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# distilhubert-ft-keyword-spotting |
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the superb dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1163 |
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- Accuracy: 0.9706 |
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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: 3e-05 |
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- train_batch_size: 256 |
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- eval_batch_size: 32 |
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- seed: 0 |
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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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| 0.8176 | 1.0 | 200 | 0.7718 | 0.8116 | |
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| 0.2364 | 2.0 | 400 | 0.2107 | 0.9662 | |
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| 0.1198 | 3.0 | 600 | 0.1374 | 0.9678 | |
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| 0.0891 | 4.0 | 800 | 0.1163 | 0.9706 | |
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| 0.085 | 5.0 | 1000 | 0.1180 | 0.9690 | |
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### Framework versions |
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- Transformers 4.12.0.dev0 |
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- Pytorch 1.9.1+cu111 |
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- Datasets 1.14.0 |
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- Tokenizers 0.10.3 |
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