metadata
license: bsd-3-clause
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ast_9-finetuned-ICBHI
results: []
ast_9-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: 0.8548
- Accuracy: 0.6572
- Sensitivity: 0.4183
- Specificity: 0.8710
- Score: 0.6446
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 |
|---|---|---|---|---|---|---|---|
| 0.9335 | 1.0 | 258 | 0.9986 | 0.5986 | 0.5318 | 0.6582 | 0.5950 |
| 0.8392 | 2.0 | 517 | 0.8548 | 0.6572 | 0.4183 | 0.8710 | 0.6446 |
| 0.6187 | 3.0 | 776 | 0.8978 | 0.6554 | 0.4797 | 0.8126 | 0.6461 |
| 0.2052 | 4.0 | 1035 | 1.1767 | 0.6533 | 0.4536 | 0.8318 | 0.6427 |
| 0.1132 | 4.99 | 1290 | 1.4218 | 0.6525 | 0.5004 | 0.7886 | 0.6445 |
Framework versions
- Transformers 4.29.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3