---
library_name: transformers
base_model: DistilHuBERT
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: HuBERT-Genre-Clf-finetuned-gtzan
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: GTZAN
      type: marsyas/gtzan
      config: all
      split: train
      args: all
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.92
---

<!-- 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. -->

# HuBERT-Genre-Clf-finetuned-gtzan

This model is a fine-tuned version of [DistilHuBERT](https://huggingface.co/DistilHuBERT) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3339
- Accuracy: 0.92

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1135        | 1.0   | 113  | 0.3252          | 0.93     |
| 0.0176        | 2.0   | 226  | 0.3014          | 0.94     |
| 0.0026        | 3.0   | 339  | 0.3110          | 0.95     |
| 0.0015        | 4.0   | 452  | 0.4329          | 0.93     |
| 0.0013        | 5.0   | 565  | 0.3339          | 0.92     |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0