|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- marsyas/gtzan |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: distil-ast-audioset-finetuned-gtzan |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# distil-ast-audioset-finetuned-gtzan |
|
|
|
This model is a fine-tuned version of [bookbot/distil-ast-audioset](https://huggingface.co/bookbot/distil-ast-audioset) on the GTZAN dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3866 |
|
- Accuracy: 0.9 |
|
|
|
## 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: 1e-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 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
|
|:-------------:|:-----:|:----:|:--------:|:---------------:| |
|
| 0.7945 | 1.0 | 113 | 0.76 | 0.8481 | |
|
| 0.4836 | 2.0 | 226 | 0.79 | 0.5647 | |
|
| 0.2434 | 3.0 | 339 | 0.8 | 0.6345 | |
|
| 0.2721 | 4.0 | 452 | 0.91 | 0.3684 | |
|
| 0.0459 | 5.0 | 565 | 0.9 | 0.3387 | |
|
| 0.0485 | 6.0 | 678 | 0.87 | 0.3720 | |
|
| 0.0337 | 7.0 | 791 | 0.9 | 0.3439 | |
|
| 0.0206 | 8.0 | 904 | 0.89 | 0.3630 | |
|
| 0.1043 | 9.0 | 1017 | 0.89 | 0.3682 | |
|
| 0.0146 | 10.0 | 1130 | 0.89 | 0.3552 | |
|
| 0.0109 | 11.0 | 1243 | 0.4141 | 0.87 | |
|
| 0.001 | 12.0 | 1356 | 0.4266 | 0.88 | |
|
| 0.0006 | 13.0 | 1469 | 0.4001 | 0.91 | |
|
| 0.0006 | 14.0 | 1582 | 0.3884 | 0.9 | |
|
| 0.0008 | 15.0 | 1695 | 0.3881 | 0.91 | |
|
| 0.0005 | 16.0 | 1808 | 0.3796 | 0.9 | |
|
| 0.0005 | 17.0 | 1921 | 0.3865 | 0.9 | |
|
| 0.0005 | 18.0 | 2034 | 0.3861 | 0.9 | |
|
| 0.0003 | 19.0 | 2147 | 0.3879 | 0.9 | |
|
| 0.0005 | 20.0 | 2260 | 0.3866 | 0.9 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.28.0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.4 |
|
- Tokenizers 0.13.3 |
|
|
