---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-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: 0.782051282051282
---

<!-- 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. -->

# wav2vec2-base-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: 1.0679
- Accuracy: 0.7821

## 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: 10
- eval_batch_size: 10
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0975        | 1.0   | 70   | 2.0767          | 0.3590   |
| 1.6787        | 2.0   | 140  | 1.7150          | 0.4872   |
| 1.5562        | 3.0   | 210  | 1.4839          | 0.4744   |
| 1.2489        | 4.0   | 280  | 1.4014          | 0.6026   |
| 0.9445        | 5.0   | 350  | 1.3975          | 0.5897   |
| 0.8189        | 6.0   | 420  | 1.0886          | 0.7179   |
| 0.6352        | 7.0   | 490  | 1.0411          | 0.6795   |
| 0.6983        | 8.0   | 560  | 1.0652          | 0.6795   |
| 0.4918        | 9.0   | 630  | 0.9020          | 0.7436   |
| 0.534         | 10.0  | 700  | 1.1106          | 0.7308   |
| 0.5065        | 11.0  | 770  | 0.8243          | 0.7821   |
| 0.1966        | 12.0  | 840  | 1.0750          | 0.7436   |
| 0.2377        | 13.0  | 910  | 1.0619          | 0.7564   |
| 0.1434        | 14.0  | 980  | 1.1533          | 0.7436   |
| 0.1128        | 15.0  | 1050 | 1.0679          | 0.7821   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0