---
library_name: transformers
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-heart-sounds
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7911585365853658
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/vldmrl-org/HeartDiseaseDetector/runs/gcep0ula)
# ast-finetuned-audioset-10-10-0.4593-heart-sounds

This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6725
- Accuracy: 0.7912

## 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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.1202        | 1.0    | 83   | 1.0917          | 0.5518   |
| 1.0098        | 2.0    | 166  | 0.9641          | 0.6235   |
| 0.9037        | 3.0    | 249  | 0.8746          | 0.6829   |
| 0.7681        | 4.0    | 332  | 0.8081          | 0.7241   |
| 0.7312        | 5.0    | 415  | 0.7589          | 0.7470   |
| 0.6984        | 6.0    | 498  | 0.7239          | 0.7698   |
| 0.6762        | 7.0    | 581  | 0.6986          | 0.7759   |
| 0.6821        | 8.0    | 664  | 0.6819          | 0.7896   |
| 0.6249        | 9.0    | 747  | 0.6725          | 0.7912   |
| 0.6694        | 9.8875 | 820  | 0.6699          | 0.7912   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1
- Datasets 2.19.1
- Tokenizers 0.21.0