---
library_name: transformers
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: 0.7866666666666666
---

<!-- 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: 1.2095
- Accuracy: 0.7867

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0746        | 1.0   | 107  | 1.9697          | 0.46     |
| 1.5843        | 2.0   | 214  | 1.5908          | 0.5067   |
| 1.5982        | 3.0   | 321  | 1.4385          | 0.58     |
| 1.2855        | 4.0   | 428  | 1.3906          | 0.5467   |
| 1.0562        | 5.0   | 535  | 1.0173          | 0.7      |
| 0.8919        | 6.0   | 642  | 0.9564          | 0.6733   |
| 0.7214        | 7.0   | 749  | 0.8906          | 0.7467   |
| 0.7624        | 8.0   | 856  | 0.9580          | 0.7467   |
| 0.3619        | 9.0   | 963  | 1.0685          | 0.7733   |
| 0.3814        | 10.0  | 1070 | 1.1847          | 0.7467   |
| 0.4371        | 11.0  | 1177 | 0.9630          | 0.7867   |
| 0.3186        | 12.0  | 1284 | 0.9635          | 0.82     |
| 0.1474        | 13.0  | 1391 | 1.0021          | 0.8333   |
| 0.0918        | 14.0  | 1498 | 1.4497          | 0.7533   |
| 0.0592        | 15.0  | 1605 | 1.2592          | 0.7733   |
| 0.0084        | 16.0  | 1712 | 1.2656          | 0.7867   |
| 0.0216        | 17.0  | 1819 | 1.2095          | 0.7867   |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0