---
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
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.76
---

<!-- 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: 1.1430
- Accuracy: 0.76

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2574        | 1.0   | 25   | 2.1793          | 0.445    |
| 1.9361        | 2.0   | 50   | 1.8937          | 0.475    |
| 1.7211        | 3.0   | 75   | 1.7034          | 0.54     |
| 1.5003        | 4.0   | 100  | 1.5038          | 0.63     |
| 1.3653        | 5.0   | 125  | 1.3770          | 0.7      |
| 1.2614        | 6.0   | 150  | 1.3169          | 0.69     |
| 1.1654        | 7.0   | 175  | 1.2444          | 0.725    |
| 1.0837        | 8.0   | 200  | 1.1828          | 0.755    |
| 1.0409        | 9.0   | 225  | 1.1549          | 0.755    |
| 1.0147        | 10.0  | 250  | 1.1430          | 0.76     |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2