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-strain
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: 0.8021978021978022
distilhubert-finetuned-strain
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: 0.8113
- Accuracy: 0.8022
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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6067 | 1.0 | 92 | 0.5729 | 0.7473 |
| 0.6384 | 2.0 | 184 | 0.5746 | 0.7692 |
| 0.522 | 3.0 | 276 | 0.5744 | 0.7582 |
| 0.4009 | 4.0 | 368 | 0.6686 | 0.7473 |
| 0.1977 | 5.0 | 460 | 0.5451 | 0.7802 |
| 0.4943 | 6.0 | 552 | 0.6118 | 0.7802 |
| 0.2251 | 7.0 | 644 | 0.5647 | 0.7912 |
| 0.0488 | 8.0 | 736 | 0.6797 | 0.8352 |
| 0.2085 | 9.0 | 828 | 0.8064 | 0.7912 |
| 0.1512 | 10.0 | 920 | 0.8113 | 0.8022 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0