---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-960h-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: 0.87
---

<!-- 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-960h-finetuned-gtzan

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5055
- Accuracy: 0.87

## 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: 16
- eval_batch_size: 16
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2648        | 1.0   | 57   | 2.2400          | 0.15     |
| 2.167         | 2.0   | 114  | 2.1032          | 0.17     |
| 1.8573        | 3.0   | 171  | 1.7658          | 0.32     |
| 1.5347        | 4.0   | 228  | 1.6620          | 0.45     |
| 1.6134        | 5.0   | 285  | 1.5017          | 0.49     |
| 1.2903        | 6.0   | 342  | 1.4639          | 0.49     |
| 1.29          | 7.0   | 399  | 1.1893          | 0.66     |
| 1.1094        | 8.0   | 456  | 1.1425          | 0.67     |
| 1.1023        | 9.0   | 513  | 1.0173          | 0.72     |
| 0.9244        | 10.0  | 570  | 0.9069          | 0.79     |
| 0.7764        | 11.0  | 627  | 0.9314          | 0.74     |
| 0.6899        | 12.0  | 684  | 0.7919          | 0.78     |
| 0.6033        | 13.0  | 741  | 0.7145          | 0.8      |
| 0.4834        | 14.0  | 798  | 0.8896          | 0.76     |
| 0.4409        | 15.0  | 855  | 0.7083          | 0.82     |
| 0.3653        | 16.0  | 912  | 0.5633          | 0.83     |
| 0.3986        | 17.0  | 969  | 0.5475          | 0.89     |
| 0.2725        | 18.0  | 1026 | 0.5044          | 0.87     |
| 0.3569        | 19.0  | 1083 | 0.5044          | 0.85     |
| 0.2089        | 20.0  | 1140 | 0.5055          | 0.87     |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2