---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-cry-detector
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: audiofolder
      type: audiofolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9830508474576272
---

<!-- 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. -->

# distilhubert-finetuned-cry-detector

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: 0.0703
- Accuracy: 0.9831

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 123
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 11   | 0.1909          | 0.9435   |
| No log        | 2.0   | 22   | 0.1998          | 0.9322   |
| No log        | 3.0   | 33   | 0.0904          | 0.9718   |
| No log        | 4.0   | 44   | 0.1063          | 0.9661   |
| No log        | 5.0   | 55   | 0.0770          | 0.9774   |
| No log        | 6.0   | 66   | 0.0832          | 0.9774   |
| No log        | 7.0   | 77   | 0.0658          | 0.9774   |
| No log        | 8.0   | 88   | 0.0681          | 0.9831   |
| No log        | 9.0   | 99   | 0.0701          | 0.9831   |
| No log        | 10.0  | 110  | 0.0703          | 0.9831   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.1+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1