---
license: apache-2.0
base_model: saketag73/classification_facebook_wav2vec2-base-finetuned-gtzan-2
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
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.805
---

<!-- 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 [saketag73/classification_facebook_wav2vec2-base-finetuned-gtzan-2](https://huggingface.co/saketag73/classification_facebook_wav2vec2-base-finetuned-gtzan-2) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7271
- Accuracy: 0.805

## 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
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0116        | 1.0   | 25   | 1.0805          | 0.715    |
| 0.7603        | 2.0   | 50   | 1.0321          | 0.76     |
| 0.6462        | 3.0   | 75   | 0.8840          | 0.775    |
| 0.5343        | 4.0   | 100  | 0.8303          | 0.78     |
| 0.4705        | 5.0   | 125  | 0.9837          | 0.72     |
| 0.3806        | 6.0   | 150  | 0.8099          | 0.79     |
| 0.3126        | 7.0   | 175  | 0.7897          | 0.79     |
| 0.2727        | 8.0   | 200  | 0.6896          | 0.81     |
| 0.2301        | 9.0   | 225  | 0.7518          | 0.81     |
| 0.2138        | 10.0  | 250  | 0.7271          | 0.805    |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2