---
license: apache-2.0
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: 0.83
---

<!-- 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: 0.7926
- Accuracy: 0.83

## 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: 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0468        | 1.0   | 113  | 2.0109          | 0.41     |
| 1.6902        | 2.0   | 226  | 1.6493          | 0.5      |
| 1.0179        | 3.0   | 339  | 1.4098          | 0.59     |
| 1.1239        | 4.0   | 452  | 1.1319          | 0.67     |
| 0.7065        | 5.0   | 565  | 0.9650          | 0.73     |
| 0.546         | 6.0   | 678  | 0.9210          | 0.75     |
| 0.535         | 7.0   | 791  | 0.7329          | 0.81     |
| 0.3793        | 8.0   | 904  | 0.5348          | 0.86     |
| 0.6647        | 9.0   | 1017 | 0.6605          | 0.84     |
| 0.3996        | 10.0  | 1130 | 0.7797          | 0.83     |
| 0.432         | 11.0  | 1243 | 0.7763          | 0.83     |
| 0.0538        | 12.0  | 1356 | 0.7716          | 0.84     |
| 0.0858        | 13.0  | 1469 | 0.7953          | 0.82     |
| 0.3906        | 14.0  | 1582 | 0.7821          | 0.84     |
| 0.2496        | 15.0  | 1695 | 0.9718          | 0.83     |
| 0.13          | 16.0  | 1808 | 0.7773          | 0.85     |
| 0.1103        | 17.0  | 1921 | 0.6670          | 0.88     |
| 0.1443        | 18.0  | 2034 | 0.8843          | 0.84     |
| 0.0083        | 19.0  | 2147 | 0.7977          | 0.84     |
| 0.0086        | 20.0  | 2260 | 0.7926          | 0.83     |


### Framework versions

- Transformers 4.31.0.dev0
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.3