---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- arrow
metrics:
- accuracy
model-index:
- name: eeem069_heart_murmur_classification
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: arrow
      type: arrow
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8221153846153846
---

<!-- 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. -->

# eeem069_heart_murmur_classification

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the arrow dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5614
- Accuracy: 0.8221

## 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: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0582        | 0.92  | 9    | 0.8806          | 0.8045   |
| 0.804         | 1.95  | 19   | 0.6482          | 0.8045   |
| 0.6425        | 2.97  | 29   | 0.6061          | 0.8045   |
| 0.6025        | 4.0   | 39   | 0.5924          | 0.8045   |
| 0.5865        | 4.92  | 48   | 0.5879          | 0.8045   |
| 0.6228        | 5.95  | 58   | 0.5834          | 0.8045   |
| 0.5676        | 6.97  | 68   | 0.5840          | 0.8045   |
| 0.5856        | 8.0   | 78   | 0.5890          | 0.8045   |
| 0.5946        | 8.92  | 87   | 0.5785          | 0.8045   |
| 0.586         | 9.95  | 97   | 0.5726          | 0.8045   |
| 0.5846        | 10.97 | 107  | 0.5723          | 0.8045   |
| 0.5545        | 12.0  | 117  | 0.5707          | 0.8237   |
| 0.5569        | 12.92 | 126  | 0.5846          | 0.8141   |
| 0.5997        | 13.95 | 136  | 0.5649          | 0.8173   |
| 0.5404        | 14.97 | 146  | 0.5625          | 0.8221   |
| 0.5438        | 16.0  | 156  | 0.5641          | 0.8189   |
| 0.5294        | 16.92 | 165  | 0.5633          | 0.8221   |
| 0.5196        | 17.95 | 175  | 0.5613          | 0.8205   |
| 0.5369        | 18.46 | 180  | 0.5614          | 0.8221   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2