|
--- |
|
license: bsd-3-clause |
|
base_model: MIT/ast-finetuned-audioset-10-10-0.4593 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- marsyas/gtzan |
|
metrics: |
|
- accuracy |
|
- f1 |
|
model-index: |
|
- name: ast-finetuned-audioset-10-10-0.4593-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: 0.89 |
|
- name: F1 |
|
type: f1 |
|
value: 0.89 |
|
pipeline_tag: audio-classification |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# ast-finetuned-audioset-10-10-0.4593-finetuned-gtzan |
|
|
|
This model is a fine-tuned version of [MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co./MIT/ast-finetuned-audioset-10-10-0.4593) on the GTZAN dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5658 |
|
- Accuracy: 0.87 |
|
- F1: 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: 2 |
|
- eval_batch_size: 2 |
|
- seed: 2024 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 16 |
|
- 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 | F1 | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:| |
|
| 0.8357 | 0.9956 | 56 | 0.6582 | 0.82 | 0.82 | |
|
| 0.4742 | 1.9911 | 112 | 0.6527 | 0.81 | 0.81 | |
|
| 0.3344 | 2.9867 | 168 | 0.9048 | 0.76 | 0.76 | |
|
| 0.0659 | 4.0 | 225 | 0.6998 | 0.84 | 0.8400 | |
|
| 0.0966 | 4.9956 | 281 | 0.6737 | 0.83 | 0.83 | |
|
| 0.0026 | 5.9911 | 337 | 0.5133 | 0.89 | 0.89 | |
|
| 0.0038 | 6.9867 | 393 | 0.5704 | 0.86 | 0.8600 | |
|
| 0.0005 | 8.0 | 450 | 0.5722 | 0.86 | 0.8600 | |
|
| 0.0003 | 8.9956 | 506 | 0.5632 | 0.87 | 0.87 | |
|
| 0.0003 | 9.9556 | 560 | 0.5658 | 0.87 | 0.87 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.4 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
