---
library_name: transformers
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
datasets:
- UrbanSounds/UrbanSoundsNew
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-finetuned-urbansound
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: urbansound
      type: UrbanSounds/UrbanSoundsNew
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6086956521739131
---

<!-- 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-base-ls960-finetuned-urbansound

This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co./facebook/hubert-base-ls960) on the urbansound dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1907
- Accuracy: 0.6087

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.133         | 1.0   | 50   | 2.1532          | 0.2609   |
| 2.0878        | 2.0   | 100  | 2.0094          | 0.3478   |
| 1.8873        | 3.0   | 150  | 1.8741          | 0.2609   |
| 1.6437        | 4.0   | 200  | 1.5861          | 0.4783   |
| 1.5457        | 5.0   | 250  | 1.4944          | 0.4783   |
| 1.181         | 6.0   | 300  | 1.4003          | 0.5217   |
| 1.2324        | 7.0   | 350  | 1.2538          | 0.5217   |
| 0.9965        | 8.0   | 400  | 1.1745          | 0.5217   |
| 1.26          | 9.0   | 450  | 1.1725          | 0.6087   |
| 1.0922        | 10.0  | 500  | 1.1907          | 0.6087   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0