---
license: apache-2.0
base_model: sanchit-gandhi/distilhubert-finetuned-gtzan-5-epochs
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan-5-epochs-finetuned-gtzan-QUIZ
  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: 0.82
---

<!-- 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-gtzan-5-epochs-finetuned-gtzan-QUIZ

This model is a fine-tuned version of [sanchit-gandhi/distilhubert-finetuned-gtzan-5-epochs](https://huggingface.co/sanchit-gandhi/distilhubert-finetuned-gtzan-5-epochs) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6130
- Accuracy: 0.82

## 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: 9e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.2256        | 0.9956 | 14   | 0.9755          | 0.68     |
| 0.9523        | 1.9911 | 28   | 0.8490          | 0.75     |
| 0.6907        | 2.9867 | 42   | 0.7725          | 0.78     |
| 0.5448        | 3.9822 | 56   | 0.6968          | 0.81     |
| 0.4604        | 4.9778 | 70   | 0.6409          | 0.81     |
| 0.4355        | 5.9733 | 84   | 0.6271          | 0.81     |
| 0.375         | 6.9689 | 98   | 0.6130          | 0.82     |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1