---
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-bs-16
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: GTZAN
      type: marsyas/gtzan
      config: default
      split: train
      args: default
    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-bs-16

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: 0.5497
- 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: 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0557        | 1.0   | 57   | 1.9783          | 0.34     |
| 1.6173        | 2.0   | 114  | 1.6407          | 0.55     |
| 1.3884        | 3.0   | 171  | 1.2228          | 0.65     |
| 1.1082        | 4.0   | 228  | 1.0989          | 0.7      |
| 0.9112        | 5.0   | 285  | 0.8724          | 0.8      |
| 0.7985        | 6.0   | 342  | 0.8715          | 0.76     |
| 0.5456        | 7.0   | 399  | 0.6832          | 0.82     |
| 0.4842        | 8.0   | 456  | 0.6566          | 0.85     |
| 0.3419        | 9.0   | 513  | 0.6485          | 0.84     |
| 0.5821        | 10.0  | 570  | 0.5636          | 0.85     |
| 0.2112        | 11.0  | 627  | 0.4572          | 0.89     |
| 0.2005        | 12.0  | 684  | 0.5405          | 0.87     |
| 0.1314        | 13.0  | 741  | 0.4695          | 0.9      |
| 0.0866        | 14.0  | 798  | 0.5545          | 0.88     |
| 0.0594        | 15.0  | 855  | 0.5497          | 0.88     |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3