---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-gtzan
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: gtzan
      type: gtzan
      config: all
      split: train
      args: all
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.66
---

<!-- 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: 1.4561
- Accuracy: 0.66

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2458        | 0.99  | 28   | 2.0258          | 0.38     |
| 1.8945        | 1.98  | 56   | 1.7438          | 0.47     |
| 1.6668        | 2.97  | 84   | 1.5996          | 0.53     |
| 1.5431        | 4.0   | 113  | 1.4844          | 0.69     |
| 1.3861        | 4.96  | 140  | 1.4561          | 0.66     |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.13.3