Ph Audio Classification V1

🚀 ph-audio-classification-v1

This is a fine - tuned audio classification model based on the ntu-spml/distilhubert model, achieving excellent results on the audiofolder dataset.

🚀 Quick Start

This model is a fine-tuned version of ntu-spml/distilhubert on the audiofolder dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.3404
• eval_accuracy: 1.0
• eval_runtime: 0.8233
• eval_samples_per_second: 8.503
• eval_steps_per_second: 1.215
• epoch: 1.0
• step: 4

📚 Documentation

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use 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: 20
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.46.3
• Pytorch 2.4.0+cu124
• Datasets 3.1.0
• Tokenizers 0.20.3

📄 License

This project is licensed under the Apache-2.0 license.