metadata
library_name: transformers
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
datasets:
- kim2024military
metrics:
- accuracy
model-index:
- name: ast-finetuned-audioset-10-10-0.4593-finetuned-MAD
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: MAD
type: kim2024military
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9344262295081968
ast-finetuned-audioset-10-10-0.4593-finetuned-MAD
This model is a fine-tuned version of MIT/ast-finetuned-audioset-10-10-0.4593 on the MAD dataset. It achieves the following results on the evaluation set:
- Loss: 1.0444
- Accuracy: 0.9344
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|---|---|---|---|---|
| 0.2166 | 1.0 | 402 | 0.5008 | 0.8959 |
| 0.4771 | 2.0 | 804 | 0.7085 | 0.9257 |
| 0.1525 | 3.0 | 1206 | 0.9449 | 0.9373 |
| 0.1688 | 4.0 | 1608 | 1.1073 | 0.9219 |
| 0.1975 | 5.0 | 2010 | 1.2495 | 0.9209 |
| 0.0 | 6.0 | 2412 | 1.0608 | 0.9306 |
| 0.0 | 7.0 | 2814 | 1.0338 | 0.9344 |
| 0.0 | 8.0 | 3216 | 1.0192 | 0.9373 |
| 0.0 | 9.0 | 3618 | 1.0345 | 0.9344 |
| 0.0 | 10.0 | 4020 | 1.0444 | 0.9344 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3