---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- augmented_bass_sounds
metrics:
- accuracy
model-index:
- name: distilhubert-bass5
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: TheDuyx/augmented_bass_sounds
      type: augmented_bass_sounds
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9991181657848325
---

<!-- 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-bass5

This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the TheDuyx/augmented_bass_sounds dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0088
- Accuracy: 0.9991

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 192
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.138         | 1.0   | 159  | 0.1198          | 0.9827   |
| 0.0307        | 2.0   | 319  | 0.0194          | 0.9976   |
| 0.0101        | 2.99  | 477  | 0.0088          | 0.9991   |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.15.2