metadata
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- augmented_bass_sounds
metrics:
- accuracy
model-index:
- name: distilhubert-bass5
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: TheDuyx/augmented_bass_sounds
type: augmented_bass_sounds
metrics:
- name: Accuracy
type: accuracy
value: 0.9991181657848325
distilhubert-bass5
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: 0.0088
- Accuracy: 0.9991
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 192
- 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 |
---|---|---|---|---|
0.138 | 1.0 | 159 | 0.1198 | 0.9827 |
0.0307 | 2.0 | 319 | 0.0194 | 0.9976 |
0.0101 | 2.99 | 477 | 0.0088 | 0.9991 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.2
- Datasets 2.18.0
- Tokenizers 0.15.2