---
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: 0.8
---

<!-- 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: 0.7670
- Accuracy: 0.8

## 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
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0554        | 1.0   | 100  | 2.0109          | 0.465    |
| 1.5036        | 2.0   | 200  | 1.5547          | 0.53     |
| 1.348         | 3.0   | 300  | 1.2558          | 0.685    |
| 1.1877        | 4.0   | 400  | 1.1226          | 0.7      |
| 0.8857        | 5.0   | 500  | 0.9978          | 0.76     |
| 0.6167        | 6.0   | 600  | 0.9513          | 0.755    |
| 0.5439        | 7.0   | 700  | 0.8185          | 0.78     |
| 0.5015        | 8.0   | 800  | 0.7880          | 0.815    |
| 0.2221        | 9.0   | 900  | 0.7777          | 0.8      |
| 0.3112        | 10.0  | 1000 | 0.7670          | 0.8      |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1