metadata
library_name: transformers
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-roughness
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: audiofolder
type: audiofolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.5824175824175825
distilhubert-finetuned-roughness
This model is a fine-tuned version of ntu-spml/distilhubert on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.8437
- Accuracy: 0.5824
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
- optimizer: Use 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6586 | 1.0 | 47 | 0.6817 | 0.5165 |
| 0.5605 | 2.0 | 94 | 0.6754 | 0.6154 |
| 0.5651 | 3.0 | 141 | 0.6738 | 0.6813 |
| 0.4983 | 4.0 | 188 | 0.6875 | 0.6484 |
| 0.3993 | 5.0 | 235 | 0.7058 | 0.6374 |
| 0.4897 | 6.0 | 282 | 0.7701 | 0.6264 |
| 0.3277 | 7.0 | 329 | 0.7521 | 0.6374 |
| 0.2516 | 8.0 | 376 | 0.8220 | 0.6264 |
| 0.1733 | 9.0 | 423 | 0.8176 | 0.6264 |
| 0.1744 | 10.0 | 470 | 0.8437 | 0.5824 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.0