|
--- |
|
license: bsd-3-clause |
|
base_model: MIT/ast-finetuned-audioset-10-10-0.4593 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- marsyas/gtzan |
|
metrics: |
|
- accuracy |
|
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: 0.92 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/soundofai/huggingface-audio-course/runs/nfwkhlry) |
|
# 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: 0.3597 |
|
- Accuracy: 0.92 |
|
|
|
## 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: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 8 |
|
- 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 | |
|
|:-------------:|:-------:|:----:|:---------------:|:--------:| |
|
| 0.5671 | 0.9956 | 112 | 0.5463 | 0.85 | |
|
| 0.7083 | 2.0 | 225 | 0.6822 | 0.78 | |
|
| 0.2257 | 2.9956 | 337 | 0.5415 | 0.85 | |
|
| 0.028 | 4.0 | 450 | 0.5070 | 0.9 | |
|
| 0.0526 | 4.9956 | 562 | 0.8882 | 0.82 | |
|
| 0.0628 | 6.0 | 675 | 0.9979 | 0.79 | |
|
| 0.0025 | 6.9956 | 787 | 0.5942 | 0.88 | |
|
| 0.0005 | 8.0 | 900 | 0.6327 | 0.9 | |
|
| 0.0005 | 8.9956 | 1012 | 0.4033 | 0.9 | |
|
| 0.0009 | 10.0 | 1125 | 0.4190 | 0.88 | |
|
| 0.0001 | 10.9956 | 1237 | 0.3672 | 0.93 | |
|
| 0.0001 | 12.0 | 1350 | 0.3615 | 0.91 | |
|
| 0.0001 | 12.9956 | 1462 | 0.3631 | 0.92 | |
|
| 0.0001 | 14.0 | 1575 | 0.3597 | 0.92 | |
|
| 0.0001 | 14.9956 | 1687 | 0.3604 | 0.92 | |
|
| 0.0 | 16.0 | 1800 | 0.3589 | 0.92 | |
|
| 0.0 | 16.9956 | 1912 | 0.3597 | 0.92 | |
|
| 0.0434 | 18.0 | 2025 | 0.3590 | 0.92 | |
|
| 0.0 | 18.9956 | 2137 | 0.3594 | 0.92 | |
|
| 0.0 | 19.9111 | 2240 | 0.3597 | 0.92 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.0.dev0 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.19.1 |
|
|
