---
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: 0.87
---

<!-- 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-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: 0.5916
- 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 1.9043        | 1.0   | 113  | 0.46     | 1.8057          |
| 1.2603        | 2.0   | 226  | 0.58     | 1.3549          |
| 1.1442        | 3.0   | 339  | 0.68     | 1.0001          |
| 0.6053        | 4.0   | 452  | 0.68     | 0.9841          |
| 0.5621        | 5.0   | 565  | 0.69     | 0.9519          |
| 0.541         | 6.0   | 678  | 0.79     | 0.6576          |
| 0.3868        | 7.0   | 791  | 0.86     | 0.4867          |
| 0.1518        | 8.0   | 904  | 0.84     | 0.5443          |
| 0.1699        | 9.0   | 1017 | 0.91     | 0.4024          |
| 0.0798        | 10.0  | 1130 | 0.5878   | 0.86            |
| 0.1869        | 11.0  | 1243 | 0.6483   | 0.86            |
| 0.1439        | 12.0  | 1356 | 0.5916   | 0.87            |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0