---
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: 0.6933
- 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1735        | 0.99  | 56   | 2.1378          | 0.24     |
| 1.7104        | 2.0   | 113  | 1.7187          | 0.52     |
| 1.3864        | 2.99  | 169  | 1.5629          | 0.53     |
| 1.1797        | 4.0   | 226  | 1.4349          | 0.62     |
| 1.0675        | 4.99  | 282  | 1.0705          | 0.74     |
| 0.9568        | 6.0   | 339  | 1.0412          | 0.74     |
| 0.7465        | 6.99  | 395  | 0.8219          | 0.84     |
| 0.6917        | 8.0   | 452  | 0.8743          | 0.78     |
| 0.4634        | 8.99  | 508  | 0.8266          | 0.81     |
| 0.4757        | 10.0  | 565  | 0.7233          | 0.86     |
| 0.4341        | 10.99 | 621  | 0.8024          | 0.81     |
| 0.3802        | 11.89 | 672  | 0.6933          | 0.84     |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.0
- Datasets 2.18.0
- Tokenizers 0.15.2