| --- |
| license: apache-2.0 |
| base_model: ntu-spml/distilhubert |
| tags: |
| - generated_from_trainer |
| datasets: |
| - audiofolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: heartbeat-detection-8 |
| results: |
| - task: |
| name: Audio Classification |
| type: audio-classification |
| dataset: |
| name: audiofolder |
| type: audiofolder |
| config: default |
| split: train[:90] |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 1.0 |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # heartbeat-detection-8 |
|
|
| This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0001 |
| - Accuracy: 1.0 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 0.001 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 4 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 1.0906 | 1.0 | 4 | 0.0892 | 1.0 | |
| | 0.0365 | 2.0 | 8 | 0.0010 | 1.0 | |
| | 0.0006 | 3.0 | 12 | 0.0001 | 1.0 | |
| | 0.0001 | 4.0 | 16 | 0.0001 | 1.0 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.39.3 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
| |
