metadata
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
base_model: ntu-spml/distilhubert
model-index:
- name: distilhubert-finetuned-gtzan
results:
- task:
type: audio-classification
name: Audio Classification
dataset:
name: GTZAN
type: marsyas/gtzan
split: None
metrics:
- type: accuracy
value: 0.9319319319319319
name: Accuracy
distilhubert-finetuned-gtzan
This model is a fine-tuned version of ntu-spml/distilhubert on the GTZAN dataset. It achieves the following results on the evaluation set:
- Loss: 0.2387
- Accuracy: 0.9319
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: 0.001
- train_batch_size: 6
- eval_batch_size: 6
- 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: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.7644 | 1.0 | 167 | 1.7832 | 0.3554 |
| 1.2856 | 2.0 | 334 | 1.4226 | 0.4745 |
| 1.2123 | 3.0 | 501 | 1.0047 | 0.6737 |
| 0.6613 | 4.0 | 668 | 0.8091 | 0.6987 |
| 0.6442 | 5.0 | 835 | 0.6713 | 0.7858 |
| 0.7172 | 6.0 | 1002 | 0.5749 | 0.8238 |
| 0.5394 | 7.0 | 1169 | 0.5079 | 0.8408 |
| 0.3853 | 8.0 | 1336 | 0.4574 | 0.8539 |
| 0.5441 | 9.0 | 1503 | 0.3729 | 0.8869 |
| 0.5062 | 10.0 | 1670 | 0.3319 | 0.9009 |
| 0.3955 | 11.0 | 1837 | 0.3745 | 0.8849 |
| 0.3112 | 12.0 | 2004 | 0.2752 | 0.9289 |
| 0.2887 | 13.0 | 2171 | 0.2544 | 0.9289 |
| 0.2038 | 14.0 | 2338 | 0.2344 | 0.9329 |
| 0.2374 | 15.0 | 2505 | 0.2387 | 0.9319 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
Training procedure
Framework versions
- PEFT 0.6.2