metadata
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ast_12-finetuned-ICBHI
results: []
ast_12-finetuned-ICBHI
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: 1.5461
- Accuracy: 0.5550
- Sensitivity: 0.3466
- Specificity: 0.7104
- Score: 0.5285
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Sensitivity | Specificity | Score |
|---|---|---|---|---|---|---|---|
| 0.7428 | 1.0 | 259 | 1.2162 | 0.5365 | 0.3840 | 0.6502 | 0.5171 |
| 0.7004 | 2.0 | 518 | 1.2543 | 0.5220 | 0.3364 | 0.6603 | 0.4984 |
| 0.584 | 3.0 | 777 | 1.2605 | 0.5191 | 0.3662 | 0.6331 | 0.4996 |
| 0.2524 | 4.0 | 1036 | 1.5461 | 0.5550 | 0.3466 | 0.7104 | 0.5285 |
| 0.0708 | 5.0 | 1295 | 1.9865 | 0.5387 | 0.3407 | 0.6863 | 0.5135 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3