---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- gtzan
metrics:
- accuracy
model-index:
- name: wav2vec2-base-finetuned-gtzan2
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: gtzan
      type: 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-gtzan2

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: 0.5863
- 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9228        | 1.0   | 113  | 1.9482          | 0.29     |
| 1.2404        | 2.0   | 226  | 1.3398          | 0.65     |
| 1.165         | 3.0   | 339  | 1.2144          | 0.6      |
| 0.5972        | 4.0   | 452  | 0.8099          | 0.78     |
| 0.5696        | 5.0   | 565  | 0.8099          | 0.75     |
| 0.6076        | 6.0   | 678  | 0.5800          | 0.82     |
| 0.4794        | 7.0   | 791  | 0.6297          | 0.83     |
| 0.2065        | 8.0   | 904  | 0.5690          | 0.88     |
| 0.1131        | 9.0   | 1017 | 0.5689          | 0.89     |
| 0.0642        | 10.0  | 1130 | 0.5863          | 0.87     |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.1