|
--- |
|
license: apache-2.0 |
|
base_model: ntu-spml/distilhubert |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- marsyas/gtzan |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: distilhubert-finetuned-gtzan |
|
results: |
|
- task: |
|
name: Audio Classification |
|
type: audio-classification |
|
dataset: |
|
name: GTZAN |
|
type: marsyas/gtzan |
|
config: all |
|
split: train |
|
args: all |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.86 |
|
--- |
|
|
|
<!-- 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-gtzan |
|
|
|
This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8236 |
|
- Accuracy: 0.86 |
|
|
|
## 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: 4 |
|
- eval_batch_size: 4 |
|
- 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: 12 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.4322 | 1.0 | 225 | 1.2094 | 0.7 | |
|
| 0.8987 | 2.0 | 450 | 1.0620 | 0.63 | |
|
| 0.1897 | 3.0 | 675 | 0.6543 | 0.79 | |
|
| 0.7499 | 4.0 | 900 | 0.5746 | 0.84 | |
|
| 0.0585 | 5.0 | 1125 | 0.6851 | 0.82 | |
|
| 0.0127 | 6.0 | 1350 | 0.7394 | 0.82 | |
|
| 0.0119 | 7.0 | 1575 | 1.0074 | 0.81 | |
|
| 0.0037 | 8.0 | 1800 | 0.8042 | 0.85 | |
|
| 0.0027 | 9.0 | 2025 | 0.8673 | 0.84 | |
|
| 0.0018 | 10.0 | 2250 | 0.9179 | 0.85 | |
|
| 0.0016 | 11.0 | 2475 | 0.8380 | 0.86 | |
|
| 0.0016 | 12.0 | 2700 | 0.8236 | 0.86 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.0.dev0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.15.0 |
|
|
