---
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-v2
  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: 0.87
---

<!-- 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-gtzan-v2

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: 0.5042
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.9411        | 1.0   | 113  | 1.8991          | 0.48     |
| 1.1479        | 2.0   | 226  | 1.4266          | 0.55     |
| 1.1104        | 3.0   | 339  | 0.9525          | 0.71     |
| 0.7571        | 4.0   | 452  | 1.1713          | 0.65     |
| 0.6203        | 5.0   | 565  | 0.8307          | 0.76     |
| 0.5817        | 6.0   | 678  | 0.6269          | 0.84     |
| 0.3863        | 7.0   | 791  | 0.5911          | 0.85     |
| 0.1104        | 8.0   | 904  | 0.5373          | 0.86     |
| 0.2236        | 9.0   | 1017 | 0.4841          | 0.88     |
| 0.0707        | 10.0  | 1130 | 0.5042          | 0.87     |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1