|
--- |
|
license: apache-2.0 |
|
base_model: facebook/hubert-base-ls960 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- marsyas/gtzan |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: hubert-base-ls960-v2-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. --> |
|
|
|
# hubert-base-ls960-v2-finetuned-gtzan |
|
|
|
This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the GTZAN dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6560 |
|
- 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: 10 |
|
- eval_batch_size: 10 |
|
- 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 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 2.1778 | 1.0 | 90 | 2.1185 | 0.42 | |
|
| 1.7477 | 2.0 | 180 | 1.6950 | 0.5 | |
|
| 1.6626 | 3.0 | 270 | 1.4481 | 0.49 | |
|
| 1.0488 | 4.0 | 360 | 1.2952 | 0.56 | |
|
| 0.9819 | 5.0 | 450 | 1.0239 | 0.63 | |
|
| 0.8553 | 6.0 | 540 | 0.8149 | 0.75 | |
|
| 0.9188 | 7.0 | 630 | 0.9471 | 0.73 | |
|
| 0.5563 | 8.0 | 720 | 0.7414 | 0.77 | |
|
| 0.6793 | 9.0 | 810 | 0.7851 | 0.78 | |
|
| 0.5282 | 10.0 | 900 | 0.6163 | 0.8 | |
|
| 0.3895 | 11.0 | 990 | 0.6667 | 0.82 | |
|
| 0.3037 | 12.0 | 1080 | 0.6157 | 0.84 | |
|
| 0.1647 | 13.0 | 1170 | 0.6485 | 0.83 | |
|
| 0.3331 | 14.0 | 1260 | 0.5609 | 0.86 | |
|
| 0.1695 | 15.0 | 1350 | 0.6393 | 0.84 | |
|
| 0.0968 | 16.0 | 1440 | 0.7537 | 0.83 | |
|
| 0.1928 | 17.0 | 1530 | 0.7043 | 0.86 | |
|
| 0.1281 | 18.0 | 1620 | 0.6077 | 0.89 | |
|
| 0.0482 | 19.0 | 1710 | 0.7178 | 0.86 | |
|
| 0.1215 | 20.0 | 1800 | 0.6560 | 0.86 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.4 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
