metadata
library_name: transformers
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- PQVD
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-grade
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: PQVD
type: PQVD
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.6703296703296703
distilhubert-finetuned-grade
This model is a fine-tuned version of ntu-spml/distilhubert on the PQVD dataset. It achieves the following results on the evaluation set:
- Loss: 1.7494
- Accuracy: 0.6703
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: 8
- eval_batch_size: 8
- 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: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6335 | 1.0 | 92 | 0.5993 | 0.6593 |
| 0.4618 | 2.0 | 184 | 0.6011 | 0.6703 |
| 0.3811 | 3.0 | 276 | 0.7119 | 0.5604 |
| 0.4686 | 4.0 | 368 | 0.7788 | 0.6593 |
| 0.2984 | 5.0 | 460 | 0.8130 | 0.6044 |
| 0.2004 | 6.0 | 552 | 0.8343 | 0.6484 |
| 0.3806 | 7.0 | 644 | 0.9339 | 0.6264 |
| 0.1813 | 8.0 | 736 | 1.1104 | 0.5055 |
| 0.1335 | 9.0 | 828 | 1.1915 | 0.6813 |
| 0.2548 | 10.0 | 920 | 1.2242 | 0.6703 |
| 0.5109 | 11.0 | 1012 | 1.4604 | 0.6923 |
| 0.155 | 12.0 | 1104 | 1.5649 | 0.6593 |
| 0.1678 | 13.0 | 1196 | 1.6666 | 0.6703 |
| 0.1302 | 14.0 | 1288 | 1.7023 | 0.6813 |
| 0.0068 | 15.0 | 1380 | 1.7494 | 0.6703 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0