---
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: 0.84
---

<!-- 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-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: 1.0838
- 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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0777        | 1.0   | 8    | 0.9974          | 0.86     |
| 0.0276        | 2.0   | 16   | 1.1353          | 0.83     |
| 0.326         | 3.0   | 24   | 1.2362          | 0.81     |
| 0.123         | 4.0   | 32   | 1.1119          | 0.84     |
| 0.0225        | 5.0   | 40   | 1.1009          | 0.85     |
| 0.0776        | 6.0   | 48   | 1.0709          | 0.85     |
| 0.025         | 7.0   | 56   | 1.1126          | 0.84     |
| 0.0163        | 8.0   | 64   | 1.0823          | 0.84     |
| 0.0193        | 9.0   | 72   | 1.0818          | 0.84     |
| 0.0209        | 10.0  | 80   | 1.0838          | 0.84     |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.1