---
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: 0.72
---

<!-- 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: 1.2556
- Accuracy: 0.72

## 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: 4
- total_train_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.2793        | 0.99  | 28   | 2.1814          | 0.28     |
| 1.9466        | 1.98  | 56   | 1.9110          | 0.41     |
| 1.7147        | 2.97  | 84   | 1.7353          | 0.47     |
| 1.5161        | 4.0   | 113  | 1.5839          | 0.53     |
| 1.3164        | 4.99  | 141  | 1.4552          | 0.62     |
| 1.2924        | 5.98  | 169  | 1.4023          | 0.68     |
| 1.1274        | 6.97  | 197  | 1.3962          | 0.65     |
| 1.0276        | 8.0   | 226  | 1.2685          | 0.74     |
| 0.967         | 8.99  | 254  | 1.2464          | 0.72     |
| 0.9227        | 9.91  | 280  | 1.2556          | 0.72     |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3