---
license: apache-2.0
base_model: facebook/hubert-large-ls960-ft
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: hubert-large-ls960-ft-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: 0.75
---

<!-- 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. -->

# hubert-large-ls960-ft-finetuned-gtzan

This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the GTZAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8290
- Accuracy: 0.75

## 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: 5
- eval_batch_size: 5
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 10
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1489        | 1.0   | 90   | 2.1400          | 0.24     |
| 1.6277        | 2.0   | 180  | 1.6670          | 0.46     |
| 1.5479        | 3.0   | 270  | 1.4687          | 0.47     |
| 1.1795        | 4.0   | 360  | 1.3815          | 0.56     |
| 1.1491        | 5.0   | 450  | 1.0969          | 0.63     |
| 0.8421        | 6.0   | 540  | 1.0707          | 0.65     |
| 1.1917        | 7.0   | 630  | 0.8761          | 0.71     |
| 0.7243        | 8.0   | 720  | 0.8741          | 0.72     |
| 0.6959        | 9.0   | 810  | 0.8417          | 0.76     |
| 0.6921        | 10.0  | 900  | 0.8290          | 0.75     |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1