metadata
license: apache-2.0
base_model: ntu-spml/distilhubert
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-accents
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: 0.2708333333333333
distilhubert-finetuned-accents
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: 1.9466
- Accuracy: 0.2708
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.8
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.48 | 1.0 | 48 | 2.4777 | 0.1042 |
| 2.473 | 2.0 | 96 | 2.4604 | 0.1562 |
| 2.4772 | 3.0 | 144 | 2.4282 | 0.1042 |
| 2.3678 | 4.0 | 192 | 2.4007 | 0.1042 |
| 2.324 | 5.0 | 240 | 2.3261 | 0.2083 |
| 2.2489 | 6.0 | 288 | 2.2360 | 0.1771 |
| 1.9909 | 7.0 | 336 | 2.1544 | 0.1875 |
| 1.9903 | 8.0 | 384 | 2.0937 | 0.1875 |
| 2.0668 | 9.0 | 432 | 2.0222 | 0.2083 |
| 1.8473 | 10.0 | 480 | 2.0298 | 0.1875 |
| 1.8068 | 11.0 | 528 | 1.9965 | 0.25 |
| 1.699 | 12.0 | 576 | 1.9466 | 0.2708 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0