---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- danavery/urbansound8K
metrics:
- accuracy
- f1
model-index:
- name: wav2vec2-finetuned-urbansound8k
  results:
  - task:
      name: Audio Classification
      type: audio-classification
    dataset:
      name: URBAN-SOUND8K
      type: danavery/urbansound8K
      args: audio-classification
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9650829994275901
    - name: F1
      type: f1
      value: 0.965058831730144
---

<!-- 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-finetuned-urbansound8k

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the URBAN-SOUND8K dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2672
- Accuracy: 0.9651
- F1: 0.9651

## 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: 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: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.6296        | 1.0   | 1747  | 0.9168          | 0.7098   | 0.6543 |
| 0.3658        | 2.0   | 3494  | 0.4589          | 0.8798   | 0.8788 |
| 0.108         | 3.0   | 5241  | 0.4362          | 0.9107   | 0.9102 |
| 0.3019        | 4.0   | 6988  | 0.4455          | 0.9216   | 0.9215 |
| 0.0019        | 5.0   | 8735  | 0.3645          | 0.9433   | 0.9433 |
| 0.0014        | 6.0   | 10482 | 0.3780          | 0.9416   | 0.9417 |
| 0.1803        | 7.0   | 12229 | 0.3196          | 0.9519   | 0.9519 |
| 0.0004        | 8.0   | 13976 | 0.2672          | 0.9651   | 0.9651 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1