| --- |
| library_name: transformers |
| license: bsd-3-clause |
| base_model: MIT/ast-finetuned-audioset-10-10-0.4593 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: ast_classifier |
| 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. --> |
|
|
| # ast_classifier |
| |
| 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 None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.5481 |
| - Accuracy: 0.7269 |
| - Precision: 0.6416 |
| - Recall: 0.9728 |
| - F1: 0.7732 |
| |
| ## 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: 32 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 5 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.4304 | 1.0 | 172 | 0.3436 | 0.8563 | 0.8231 | 0.8913 | 0.8558 | |
| | 0.2198 | 2.0 | 344 | 1.0337 | 0.6684 | 0.5922 | 0.9864 | 0.7401 | |
| | 0.1219 | 3.0 | 516 | 0.5469 | 0.8069 | 0.7180 | 0.9823 | 0.8296 | |
| | 0.0818 | 4.0 | 688 | 1.2336 | 0.7295 | 0.6455 | 0.9647 | 0.7734 | |
| | 0.0317 | 5.0 | 860 | 1.5481 | 0.7269 | 0.6416 | 0.9728 | 0.7732 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.57.2 |
| - Pytorch 2.9.0+cu126 |
| - Datasets 3.6.0 |
| - Tokenizers 0.22.1 |
|
|
