---
library_name: transformers
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- Hoonvolution/hoons_music_data
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-hoon_music
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: Hoons music data
      type: Hoonvolution/hoons_music_data
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.84375
---

<!-- 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-hoon_music

This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the Hoons music data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7307
- Accuracy: 0.8438

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6265        | 1.0   | 298  | 1.7652          | 0.3792   |
| 0.9028        | 2.0   | 596  | 1.0772          | 0.6479   |
| 0.3958        | 3.0   | 894  | 0.7857          | 0.7812   |
| 0.2335        | 4.0   | 1192 | 0.5601          | 0.8521   |
| 0.1384        | 5.0   | 1490 | 0.8042          | 0.8229   |
| 0.0517        | 6.0   | 1788 | 0.7031          | 0.85     |
| 0.0025        | 7.0   | 2086 | 0.7261          | 0.8479   |
| 0.0018        | 8.0   | 2384 | 0.7103          | 0.85     |
| 0.0015        | 9.0   | 2682 | 0.7329          | 0.8458   |
| 0.0015        | 10.0  | 2980 | 0.7307          | 0.8438   |


### Framework versions

- Transformers 4.45.0.dev0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1