distilhubert-bass-classifier9

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

• Loss: 0.0042
• Accuracy: 0.9994

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: 0.0005
• train_batch_size: 128
• eval_batch_size: 128
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0525	1.0	240	0.1287	0.9797
0.0	2.0	480	0.0163	0.9982
0.0001	3.0	720	0.0042	0.9994

Framework versions

• Transformers 4.39.2
• Pytorch 2.2.2
• Datasets 2.18.0
• Tokenizers 0.15.2