---
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: 0.88
---

<!-- 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: 0.6028
- Accuracy: 0.88

## 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: 3e-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: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0751        | 1.0   | 113  | 2.0343          | 0.6      |
| 1.5734        | 2.0   | 226  | 1.6338          | 0.58     |
| 1.3801        | 3.0   | 339  | 1.2674          | 0.7      |
| 1.0384        | 4.0   | 452  | 1.1376          | 0.68     |
| 0.973         | 5.0   | 565  | 0.9849          | 0.73     |
| 1.0033        | 6.0   | 678  | 0.7686          | 0.76     |
| 0.6347        | 7.0   | 791  | 0.5909          | 0.87     |
| 0.6537        | 8.0   | 904  | 0.9489          | 0.75     |
| 0.359         | 9.0   | 1017 | 0.7478          | 0.81     |
| 0.2268        | 10.0  | 1130 | 0.6247          | 0.84     |
| 0.2674        | 11.0  | 1243 | 0.6437          | 0.84     |
| 0.2237        | 12.0  | 1356 | 0.7997          | 0.81     |
| 0.1418        | 13.0  | 1469 | 0.7738          | 0.84     |
| 0.1201        | 14.0  | 1582 | 0.5696          | 0.87     |
| 0.019         | 15.0  | 1695 | 0.8173          | 0.84     |
| 0.0175        | 16.0  | 1808 | 0.6395          | 0.88     |
| 0.16          | 17.0  | 1921 | 0.6062          | 0.87     |
| 0.0137        | 18.0  | 2034 | 0.5422          | 0.9      |
| 0.0127        | 19.0  | 2147 | 0.6421          | 0.88     |
| 0.0129        | 20.0  | 2260 | 0.6028          | 0.88     |


### Framework versions

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