|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- audio-classification |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: wav2vec2-base-ft-fake-detection |
|
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. --> |
|
|
|
# wav2vec2-base-ft-fake-detection |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the alexandreacff/kaggle-fake-detection dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6261 |
|
- Accuracy: 0.6523 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 16 |
|
- seed: 0 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 10.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:| |
|
| 0.6253 | 0.9851 | 33 | 0.6261 | 0.6523 | |
|
| 0.4394 | 2.0 | 67 | 0.7140 | 0.5645 | |
|
| 0.3685 | 2.9851 | 100 | 0.7181 | 0.5850 | |
|
| 0.317 | 4.0 | 134 | 0.7291 | 0.6150 | |
|
| 0.3027 | 4.9851 | 167 | 0.7457 | 0.6159 | |
|
| 0.2672 | 6.0 | 201 | 0.7805 | 0.6243 | |
|
| 0.2711 | 6.9851 | 234 | 0.8113 | 0.6215 | |
|
| 0.2086 | 8.0 | 268 | 0.9130 | 0.5963 | |
|
| 0.2077 | 8.9851 | 301 | 0.9042 | 0.6168 | |
|
| 0.223 | 9.8507 | 330 | 0.8924 | 0.6178 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.0.dev0 |
|
- Pytorch 2.1.0a0+32f93b1 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|