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-grade_no_blc
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: 0.6702127659574468
distilhubert-finetuned-grade_no_blc
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: 1.0439
- Accuracy: 0.6702
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 |
|---|---|---|---|---|
| 0.5828 | 1.0 | 117 | 0.6066 | 0.5957 |
| 0.4849 | 2.0 | 234 | 0.6302 | 0.6489 |
| 0.4787 | 3.0 | 351 | 0.6495 | 0.7021 |
| 0.8155 | 4.0 | 468 | 0.7747 | 0.6596 |
| 0.6115 | 5.0 | 585 | 0.7488 | 0.6383 |
| 0.5887 | 6.0 | 702 | 0.8279 | 0.6702 |
| 0.3955 | 7.0 | 819 | 0.9350 | 0.6277 |
| 0.2676 | 8.0 | 936 | 0.8922 | 0.6702 |
| 0.4663 | 9.0 | 1053 | 0.9672 | 0.6596 |
| 0.1649 | 10.0 | 1170 | 1.0439 | 0.6702 |
Framework versions
- Transformers 4.50.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.0