---
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: 0.88
---

<!-- 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. -->

# 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: 0.5472
- 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: 5e-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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9984        | 1.0   | 113  | 1.9505          | 0.46     |
| 1.4188        | 2.0   | 226  | 1.5582          | 0.52     |
| 1.2867        | 3.0   | 339  | 1.1267          | 0.65     |
| 0.7716        | 4.0   | 452  | 0.9512          | 0.64     |
| 0.5553        | 5.0   | 565  | 0.9790          | 0.72     |
| 0.7491        | 6.0   | 678  | 0.7419          | 0.78     |
| 0.4399        | 7.0   | 791  | 0.5709          | 0.86     |
| 0.2489        | 8.0   | 904  | 0.6352          | 0.8      |
| 0.388         | 9.0   | 1017 | 0.5130          | 0.89     |
| 0.2066        | 10.0  | 1130 | 0.7185          | 0.86     |
| 0.1905        | 11.0  | 1243 | 0.5545          | 0.9      |
| 0.1312        | 12.0  | 1356 | 0.8126          | 0.85     |
| 0.0185        | 13.0  | 1469 | 0.4841          | 0.91     |
| 0.0154        | 14.0  | 1582 | 0.7167          | 0.86     |
| 0.0156        | 15.0  | 1695 | 0.5472          | 0.88     |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1