|
---
|
|
license: apache-2.0
|
|
base_model: ntu-spml/distilhubert
|
|
tags:
|
|
- generated_from_trainer
|
|
datasets:
|
|
- narad/ravdess
|
|
metrics:
|
|
- accuracy
|
|
model-index:
|
|
- name: distilhubert-finetuned-ravdess
|
|
results:
|
|
- task:
|
|
name: Audio Classification
|
|
type: audio-classification
|
|
dataset:
|
|
name: RAVDESS
|
|
type: narad/ravdess
|
|
config: all
|
|
split: train
|
|
args: all
|
|
metrics:
|
|
- name: Accuracy
|
|
type: accuracy
|
|
value: 0.8194444444444444
|
|
---
|
|
|
|
<!-- 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-ravdess
|
|
|
|
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the RAVDESS dataset.
|
|
It achieves the following results on the evaluation set:
|
|
- Loss: 0.6720
|
|
- Accuracy: 0.8194
|
|
|
|
## 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
|
|
- mixed_precision_training: Native AMP
|
|
|
|
### Training results
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|
|
|
| 1.795 | 1.0 | 162 | 1.8129 | 0.25 |
|
|
| 1.1416 | 2.0 | 324 | 1.2499 | 0.5278 |
|
|
| 1.1677 | 3.0 | 486 | 0.9141 | 0.6875 |
|
|
| 0.5474 | 4.0 | 648 | 0.7662 | 0.75 |
|
|
| 0.4129 | 5.0 | 810 | 0.6744 | 0.7569 |
|
|
| 0.2396 | 6.0 | 972 | 0.6781 | 0.7986 |
|
|
| 0.0626 | 7.0 | 1134 | 0.7809 | 0.75 |
|
|
| 0.1198 | 8.0 | 1296 | 0.6404 | 0.8194 |
|
|
| 0.0187 | 9.0 | 1458 | 0.6750 | 0.8264 |
|
|
| 0.012 | 10.0 | 1620 | 0.6720 | 0.8194 |
|
|
|
|
|
|
### Framework versions
|
|
|
|
- Transformers 4.42.4
|
|
- Pytorch 2.3.1
|
|
- Datasets 2.19.1
|
|
- Tokenizers 0.19.1
|
|
|
