---
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- augmented_bass_sounds
metrics:
- accuracy
model-index:
- name: distilhubert-bass9
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: TheDuyx/augmented_bass_sounds
      type: augmented_bass_sounds
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9994121105232217
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# distilhubert-bass9

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: 0.0024
- Accuracy: 0.9994

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 80
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0433        | 1.0   | 382  | 0.0492          | 0.9877   |
| 0.0022        | 2.0   | 765  | 0.0061          | 0.9982   |
| 0.0013        | 2.99  | 1146 | 0.0024          | 0.9994   |


### Framework versions

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