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---
license: bsd-3-clause
base_model: MIT/ast-finetuned-audioset-10-10-0.4593
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: SeizureClassifier_AST_B_43829950
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. -->
# SeizureClassifier_AST_B_43829950
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: 0.0063
- Accuracy: 1.0
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.269 | 0.99 | 44 | 1.1676 | 0.8564 |
| 0.7525 | 1.99 | 88 | 0.5446 | 0.9777 |
| 0.3005 | 2.98 | 132 | 0.2273 | 0.9876 |
| 0.185 | 4.0 | 177 | 0.1556 | 0.9653 |
| 0.0935 | 4.99 | 221 | 0.0798 | 0.9901 |
| 0.0545 | 5.99 | 265 | 0.0313 | 0.9950 |
| 0.0416 | 6.98 | 309 | 0.0278 | 0.9950 |
| 0.0264 | 8.0 | 354 | 0.0682 | 0.9851 |
| 0.0109 | 8.99 | 398 | 0.0311 | 0.9950 |
| 0.0104 | 9.99 | 442 | 0.0085 | 1.0 |
| 0.0083 | 10.98 | 486 | 0.0143 | 0.9975 |
| 0.0067 | 12.0 | 531 | 0.0070 | 1.0 |
| 0.0063 | 12.99 | 575 | 0.0066 | 1.0 |
| 0.006 | 13.99 | 619 | 0.0064 | 1.0 |
| 0.0059 | 14.92 | 660 | 0.0063 | 1.0 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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