---
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: 0.81
---

<!-- 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: 0.7472
- Accuracy: 0.81

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 2.2042        | 1.0   | 112  | 0.27     | 2.1274          |
| 1.7875        | 2.0   | 225  | 0.51     | 1.6840          |
| 1.4927        | 3.0   | 337  | 0.57     | 1.3809          |
| 1.2344        | 4.0   | 450  | 0.64     | 1.2021          |
| 1.2579        | 5.0   | 562  | 0.62     | 1.1646          |
| 0.9661        | 6.0   | 675  | 0.65     | 1.0412          |
| 1.0119        | 7.0   | 787  | 0.74     | 0.8671          |
| 0.8629        | 8.0   | 900  | 0.66     | 0.9364          |
| 0.607         | 9.0   | 1012 | 0.75     | 0.8867          |
| 0.5699        | 10.0  | 1125 | 0.78     | 0.7432          |
| 0.5128        | 11.0  | 1237 | 0.76     | 0.8212          |
| 0.4203        | 12.0  | 1350 | 0.77     | 0.8128          |
| 0.348         | 13.0  | 1462 | 0.81     | 0.7472          |
| 0.3869        | 14.0  | 1575 | 0.8      | 0.7456          |
| 0.2129        | 14.93 | 1680 | 0.79     | 0.7243          |


### Framework versions

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