wav2vec2-finetuned-urbansound8k

This model is a fine-tuned version of 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
Downloads last month
4
Safetensors
Model size
94.6M params
Tensor type
F32
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for rishabhsabnavis/noise-pollution-model

Finetuned
(812)
this model

Dataset used to train rishabhsabnavis/noise-pollution-model

Evaluation results