---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: HamzaSidhu786/distilhubert-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: 0.83
---

<!-- 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. -->

# HamzaSidhu786/distilhubert-finetuned-gtzan

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8269
- Accuracy: 0.83

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1788        | 1.0   | 57   | 2.0907          | 0.39     |
| 1.6561        | 2.0   | 114  | 1.5747          | 0.62     |
| 1.3464        | 3.0   | 171  | 1.4279          | 0.57     |
| 1.1727        | 4.0   | 228  | 1.1862          | 0.68     |
| 0.9399        | 5.0   | 285  | 1.0572          | 0.66     |
| 0.931         | 6.0   | 342  | 1.1268          | 0.66     |
| 0.7375        | 7.0   | 399  | 0.8744          | 0.77     |
| 0.5798        | 8.0   | 456  | 0.8596          | 0.78     |
| 0.5668        | 9.0   | 513  | 0.8253          | 0.76     |
| 0.4972        | 10.0  | 570  | 0.8273          | 0.76     |
| 0.2375        | 11.0  | 627  | 0.8192          | 0.76     |
| 0.1913        | 12.0  | 684  | 0.7618          | 0.83     |
| 0.2132        | 13.0  | 741  | 0.8249          | 0.82     |
| 0.0823        | 14.0  | 798  | 0.8962          | 0.81     |
| 0.0444        | 15.0  | 855  | 0.9376          | 0.78     |
| 0.0375        | 16.0  | 912  | 0.8609          | 0.81     |
| 0.0298        | 17.0  | 969  | 0.8741          | 0.83     |
| 0.0808        | 18.0  | 1026 | 0.8911          | 0.84     |
| 0.0453        | 19.0  | 1083 | 0.8756          | 0.84     |
| 0.0229        | 20.0  | 1140 | 0.8269          | 0.83     |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1