|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: SeizureClassifier_Wav2Vec_43243498 |
|
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_Wav2Vec_43243498 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0520 |
|
- Accuracy: 0.9901 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 1.1121 | 0.99 | 44 | 0.9842 | 0.8144 | |
|
| 0.6303 | 1.99 | 88 | 0.5874 | 0.8861 | |
|
| 0.4605 | 2.98 | 132 | 0.3826 | 0.9406 | |
|
| 0.323 | 4.0 | 177 | 0.2791 | 0.9530 | |
|
| 0.2435 | 4.99 | 221 | 0.3828 | 0.8688 | |
|
| 0.2354 | 5.99 | 265 | 0.1321 | 0.9752 | |
|
| 0.2491 | 6.98 | 309 | 0.1552 | 0.9653 | |
|
| 0.1116 | 8.0 | 354 | 0.1540 | 0.9579 | |
|
| 0.0934 | 8.99 | 398 | 0.1053 | 0.9827 | |
|
| 0.0774 | 9.99 | 442 | 0.1016 | 0.9777 | |
|
| 0.0553 | 10.98 | 486 | 0.1856 | 0.9530 | |
|
| 0.0368 | 12.0 | 531 | 0.1151 | 0.9728 | |
|
| 0.017 | 12.99 | 575 | 0.0516 | 0.9876 | |
|
| 0.0153 | 13.99 | 619 | 0.0540 | 0.9901 | |
|
| 0.0144 | 14.92 | 660 | 0.0520 | 0.9901 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.2 |
|
- Pytorch 2.1.2+cu118 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.0 |
|
|
