metadata
library_name: transformers
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- marsyas/gtzan
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-gtzan
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: GTZAN
type: marsyas/gtzan
config: all
split: train
args: all
metrics:
- name: Accuracy
type: accuracy
value: 0.75
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: 1.0738
- Accuracy: 0.75
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: 1e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Use OptimizerNames.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: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2801 | 1.0 | 90 | 2.2580 | 0.22 |
| 2.0967 | 2.0 | 180 | 2.0571 | 0.57 |
| 1.8888 | 3.0 | 270 | 1.8279 | 0.52 |
| 1.6488 | 4.0 | 360 | 1.6454 | 0.59 |
| 1.5574 | 5.0 | 450 | 1.4917 | 0.64 |
| 1.4041 | 6.0 | 540 | 1.3953 | 0.71 |
| 1.427 | 7.0 | 630 | 1.3156 | 0.74 |
| 1.2886 | 8.0 | 720 | 1.2510 | 0.76 |
| 1.1965 | 9.0 | 810 | 1.2120 | 0.75 |
| 1.1772 | 10.0 | 900 | 1.1493 | 0.75 |
| 1.1492 | 11.0 | 990 | 1.1436 | 0.74 |
| 1.1419 | 12.0 | 1080 | 1.1106 | 0.74 |
| 1.0549 | 13.0 | 1170 | 1.0867 | 0.74 |
| 1.2573 | 14.0 | 1260 | 1.0797 | 0.73 |
| 1.0615 | 15.0 | 1350 | 1.0738 | 0.75 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0