|
--- |
|
license: apache-2.0 |
|
base_model: ntu-spml/distilhubert |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- EdwardLin2023/AESDD |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: distilhubert-finetuned-AESDD |
|
results: |
|
- task: |
|
name: Audio Classification |
|
type: audio-classification |
|
dataset: |
|
name: aesdd |
|
type: aesdd |
|
config: AESDD |
|
split: train |
|
args: AESDD |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9016393442622951 |
|
--- |
|
|
|
<!-- 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-AESDD |
|
|
|
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the aesdd dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4389 |
|
- Accuracy: 0.9016 |
|
|
|
## 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: 0.1 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.1249 | 1.0 | 68 | 1.1905 | 0.5082 | |
|
| 0.7441 | 2.0 | 136 | 0.8850 | 0.6721 | |
|
| 0.5941 | 3.0 | 204 | 0.6579 | 0.8361 | |
|
| 0.4349 | 4.0 | 272 | 0.9638 | 0.6721 | |
|
| 0.2612 | 5.0 | 340 | 0.5081 | 0.8689 | |
|
| 0.1883 | 6.0 | 408 | 0.6223 | 0.8197 | |
|
| 0.0978 | 7.0 | 476 | 0.4671 | 0.8689 | |
|
| 0.0425 | 8.0 | 544 | 0.4338 | 0.8852 | |
|
| 0.0264 | 9.0 | 612 | 0.4488 | 0.8525 | |
|
| 0.0219 | 10.0 | 680 | 0.4389 | 0.9016 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.31.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.2 |
|
- Tokenizers 0.13.3 |
