|
--- |
|
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 |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# distilhubert-finetuned-accents |
|
|
|
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the audiofolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.0748 |
|
- Accuracy: 0.2708 |
|
|
|
## Model description |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.7 |
|
- num_epochs: 14 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 2.4778 | 1.0 | 48 | 2.4807 | 0.0938 | |
|
| 2.4779 | 2.0 | 96 | 2.4651 | 0.1042 | |
|
| 2.4751 | 3.0 | 144 | 2.4365 | 0.1042 | |
|
| 2.3777 | 4.0 | 192 | 2.4187 | 0.1042 | |
|
| 2.3786 | 5.0 | 240 | 2.4050 | 0.1458 | |
|
| 2.3754 | 6.0 | 288 | 2.3446 | 0.1458 | |
|
| 2.1556 | 7.0 | 336 | 2.2284 | 0.2083 | |
|
| 2.1062 | 8.0 | 384 | 2.1533 | 0.2188 | |
|
| 2.0081 | 9.0 | 432 | 2.0765 | 0.2292 | |
|
| 1.813 | 10.0 | 480 | 2.0671 | 0.2083 | |
|
| 1.74 | 11.0 | 528 | 1.9977 | 0.3021 | |
|
| 1.4795 | 12.0 | 576 | 2.0588 | 0.2396 | |
|
| 1.298 | 13.0 | 624 | 2.0652 | 0.3021 | |
|
| 1.2578 | 14.0 | 672 | 2.0748 | 0.2708 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.0 |
|
|
