---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: heartbeat-detection
  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

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: 1.4420
- 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: 1e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6017        | 1.0   | 8    | 1.5921          | 0.1481   |
| 1.582         | 2.0   | 16   | 1.5723          | 0.4444   |
| 1.5626        | 3.0   | 24   | 1.5543          | 0.7778   |
| 1.5442        | 4.0   | 32   | 1.5375          | 0.8148   |
| 1.5278        | 5.0   | 40   | 1.5220          | 0.8889   |
| 1.512         | 6.0   | 48   | 1.5077          | 0.9259   |
| 1.4977        | 7.0   | 56   | 1.4947          | 0.9259   |
| 1.4872        | 8.0   | 64   | 1.4832          | 0.9630   |
| 1.4741        | 9.0   | 72   | 1.4729          | 0.9630   |
| 1.4657        | 10.0  | 80   | 1.4640          | 0.9630   |
| 1.457         | 11.0  | 88   | 1.4564          | 1.0      |
| 1.4504        | 12.0  | 96   | 1.4502          | 1.0      |
| 1.4445        | 13.0  | 104  | 1.4454          | 1.0      |
| 1.4393        | 14.0  | 112  | 1.4420          | 1.0      |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2