---
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: 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

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: 0.7770
- 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 11

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0152        | 1.0   | 112  | 1.9017          | 0.52     |
| 1.6232        | 2.0   | 225  | 1.5400          | 0.53     |
| 1.2989        | 3.0   | 337  | 1.1494          | 0.65     |
| 1.2035        | 4.0   | 450  | 1.1189          | 0.69     |
| 0.6804        | 5.0   | 562  | 0.8873          | 0.69     |
| 0.7305        | 6.0   | 675  | 0.7527          | 0.81     |
| 0.4738        | 7.0   | 787  | 0.6880          | 0.78     |
| 0.2824        | 8.0   | 900  | 0.7893          | 0.73     |
| 0.3863        | 9.0   | 1012 | 0.5786          | 0.85     |
| 0.4061        | 10.0  | 1125 | 0.7070          | 0.81     |
| 0.1302        | 11.0  | 1237 | 0.5829          | 0.88     |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3