---
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: 0.84
---

<!-- 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: 1.0690
- Accuracy: 0.84

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0298        | 1.0   | 113  | 1.9942          | 0.42     |
| 1.6308        | 2.0   | 226  | 1.7948          | 0.45     |
| 1.4047        | 3.0   | 339  | 1.6728          | 0.4      |
| 1.0438        | 4.0   | 452  | 1.2557          | 0.63     |
| 1.0471        | 5.0   | 565  | 1.0976          | 0.66     |
| 0.8658        | 6.0   | 678  | 0.9722          | 0.64     |
| 0.7625        | 7.0   | 791  | 0.7211          | 0.79     |
| 0.6197        | 8.0   | 904  | 0.9618          | 0.71     |
| 0.2382        | 9.0   | 1017 | 0.5927          | 0.85     |
| 0.275         | 10.0  | 1130 | 0.9532          | 0.75     |
| 0.2681        | 11.0  | 1243 | 1.1366          | 0.76     |
| 0.2315        | 12.0  | 1356 | 1.1621          | 0.79     |
| 0.0142        | 13.0  | 1469 | 0.9571          | 0.84     |
| 0.0151        | 14.0  | 1582 | 0.9650          | 0.84     |
| 0.1348        | 15.0  | 1695 | 1.2902          | 0.8      |
| 0.0082        | 16.0  | 1808 | 1.0652          | 0.83     |
| 0.0054        | 17.0  | 1921 | 0.9985          | 0.83     |
| 0.0049        | 18.0  | 2034 | 1.0041          | 0.85     |
| 0.0052        | 19.0  | 2147 | 1.0800          | 0.85     |
| 0.0044        | 20.0  | 2260 | 1.0690          | 0.84     |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2