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--- |
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license: apache-2.0 |
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base_model: ntu-spml/distilhubert |
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tags: |
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- generated_from_trainer |
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datasets: |
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- audiofolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: heartbeat-detection |
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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: audiofolder |
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type: audiofolder |
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config: default |
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split: train[:90] |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9629629629629629 |
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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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# heartbeat-detection |
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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4766 |
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- Accuracy: 0.9630 |
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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-06 |
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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: 0.01 |
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- num_epochs: 16 |
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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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| 1.6241 | 1.0 | 8 | 1.6177 | 0.0 | |
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| 1.6057 | 2.0 | 16 | 1.5995 | 0.0 | |
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| 1.5872 | 3.0 | 24 | 1.5829 | 0.0370 | |
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| 1.5703 | 4.0 | 32 | 1.5674 | 0.0741 | |
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| 1.5557 | 5.0 | 40 | 1.5532 | 0.2593 | |
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| 1.5415 | 6.0 | 48 | 1.5401 | 0.4815 | |
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| 1.5285 | 7.0 | 56 | 1.5282 | 0.7037 | |
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| 1.5172 | 8.0 | 64 | 1.5175 | 0.7778 | |
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| 1.5074 | 9.0 | 72 | 1.5080 | 0.8519 | |
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| 1.4975 | 10.0 | 80 | 1.4998 | 0.8519 | |
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| 1.4906 | 11.0 | 88 | 1.4928 | 0.9259 | |
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| 1.4844 | 12.0 | 96 | 1.4870 | 0.9259 | |
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| 1.4788 | 13.0 | 104 | 1.4825 | 0.9630 | |
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| 1.4744 | 14.0 | 112 | 1.4793 | 0.9630 | |
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| 1.4718 | 15.0 | 120 | 1.4773 | 0.9630 | |
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| 1.4704 | 16.0 | 128 | 1.4766 | 0.9630 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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