File size: 2,169 Bytes
a066691 22c5ea2 a066691 22c5ea2 a066691 22c5ea2 a066691 1fd7726 a066691 1fd7726 a066691 1fd7726 a066691 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 |
---
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
|