README.md

metadata

license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
  - generated_from_trainer
datasets:
  - augmented_bass_sounds
metrics:
  - accuracy
model-index:
  - name: distilhubert-bass9
    results:
      - task:
          name: Audio Classification
          type: audio-classification
        dataset:
          name: TheDuyx/augmented_bass_sounds
          type: augmented_bass_sounds
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9994121105232217

distilhubert-bass9

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

• Loss: 0.0024
• 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: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 5
• total_train_batch_size: 80
• 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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0433	1.0	382	0.0492	0.9877
0.0022	2.0	765	0.0061	0.9982
0.0013	2.99	1146	0.0024	0.9994

Framework versions

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