---
base_model: facebook/wav2vec2
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: facebook/wav2vec2-base-finetuned-gtzan
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: GTZAN
      type: marsyas/gtzan
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.4
---

<!-- 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. -->

# facebook/wav2vec2-base-finetuned-gtzan

This model is a fine-tuned version of [facebook/wav2vec2](https://huggingface.co/facebook/wav2vec2) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0140
- Accuracy: 0.4

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.96  | 6    | 2.2871          | 0.195    |
| 2.2933        | 1.92  | 12   | 2.2658          | 0.18     |
| 2.2933        | 2.88  | 18   | 2.2214          | 0.275    |
| 2.2388        | 4.0   | 25   | 2.1885          | 0.29     |
| 2.1455        | 4.96  | 31   | 2.1246          | 0.38     |
| 2.1455        | 5.92  | 37   | 2.1139          | 0.35     |
| 2.0823        | 6.88  | 43   | 2.0462          | 0.36     |
| 2.0279        | 8.0   | 50   | 2.0282          | 0.405    |
| 2.0279        | 8.96  | 56   | 2.0133          | 0.405    |
| 1.9928        | 9.6   | 60   | 2.0140          | 0.4      |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1