---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/wav2vec2-base-100k-voxpopuli
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-100k-voxpopuli-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-100k-voxpopuli-finetuned-gtzan

This model is a fine-tuned version of [facebook/wav2vec2-base-100k-voxpopuli](https://huggingface.co/facebook/wav2vec2-base-100k-voxpopuli) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9034
- 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1924        | 1.0   | 225  | 2.1487          | 0.27     |
| 1.8417        | 2.0   | 450  | 1.8767          | 0.38     |
| 1.6017        | 3.0   | 675  | 1.5778          | 0.51     |
| 1.3497        | 4.0   | 900  | 1.4785          | 0.4      |
| 1.2631        | 5.0   | 1125 | 1.3103          | 0.58     |
| 0.8172        | 6.0   | 1350 | 1.1736          | 0.63     |
| 1.1657        | 7.0   | 1575 | 0.9690          | 0.74     |
| 1.1711        | 8.0   | 1800 | 1.3609          | 0.63     |
| 0.5033        | 9.0   | 2025 | 0.7300          | 0.83     |
| 0.4104        | 10.0  | 2250 | 0.9866          | 0.72     |
| 0.318         | 11.0  | 2475 | 0.8159          | 0.81     |
| 0.1074        | 12.0  | 2700 | 0.8024          | 0.85     |
| 0.093         | 13.0  | 2925 | 0.8285          | 0.85     |
| 0.7407        | 14.0  | 3150 | 0.8591          | 0.87     |
| 0.027         | 15.0  | 3375 | 0.9574          | 0.84     |
| 0.4564        | 16.0  | 3600 | 0.9762          | 0.85     |
| 0.0198        | 17.0  | 3825 | 0.9204          | 0.85     |
| 0.5467        | 18.0  | 4050 | 0.8703          | 0.87     |
| 0.2644        | 19.0  | 4275 | 0.8855          | 0.87     |
| 0.013         | 20.0  | 4500 | 0.9034          | 0.87     |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1