metadata
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: []
ast_classifier
This model is a fine-tuned version of 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