|
--- |
|
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: 0.87 |
|
--- |
|
|
|
<!-- 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: 0.9031 |
|
- Accuracy: 0.87 |
|
|
|
## 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: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 2.1931 | 1.0 | 113 | 2.0840 | 0.39 | |
|
| 1.5734 | 2.0 | 226 | 1.4764 | 0.53 | |
|
| 1.2619 | 3.0 | 339 | 1.1045 | 0.68 | |
|
| 1.0427 | 4.0 | 452 | 1.0008 | 0.74 | |
|
| 0.7065 | 5.0 | 565 | 0.7131 | 0.83 | |
|
| 0.4206 | 6.0 | 678 | 0.6687 | 0.8 | |
|
| 0.5466 | 7.0 | 791 | 0.5807 | 0.83 | |
|
| 0.1232 | 8.0 | 904 | 0.6143 | 0.83 | |
|
| 0.2593 | 9.0 | 1017 | 0.6080 | 0.89 | |
|
| 0.0496 | 10.0 | 1130 | 0.7360 | 0.84 | |
|
| 0.0127 | 11.0 | 1243 | 0.7648 | 0.85 | |
|
| 0.0993 | 12.0 | 1356 | 0.8416 | 0.85 | |
|
| 0.0068 | 13.0 | 1469 | 0.7966 | 0.85 | |
|
| 0.0054 | 14.0 | 1582 | 0.8122 | 0.86 | |
|
| 0.0044 | 15.0 | 1695 | 0.8788 | 0.87 | |
|
| 0.0037 | 16.0 | 1808 | 0.8760 | 0.87 | |
|
| 0.0892 | 17.0 | 1921 | 0.8911 | 0.87 | |
|
| 0.0032 | 18.0 | 2034 | 0.9083 | 0.86 | |
|
| 0.0029 | 19.0 | 2147 | 0.9172 | 0.86 | |
|
| 0.0037 | 20.0 | 2260 | 0.9031 | 0.87 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.32.0.dev0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.4 |
|
- Tokenizers 0.13.3 |
|
|
