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wavLM-base-Deepfake_V2 – AI Model by DavidCombei | AlphaNeural AI
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DavidCombei
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wavLM-base-Deepfake_V2
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transformers
pytorch
wavlm
audio-classification
generated_from_trainer
2408.07414
endpoints_compatible
us
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wavLM-base-UTCN
This model is a fine-tuned version of
microsoft/wavLM-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0234
Accuracy: 0.9962
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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.0603
1.0
435
0.0307
0.9928
0.009
2.0
870
0.0201
0.9962
0.0109
3.0
1305
0.0176
0.9972
0.001
4.0
1740
0.0246
0.9950
0.0013
5.0
2175
0.0234
0.9962
Framework versions
Transformers 4.30.0
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.13.3
arxiv.org/abs/2408.07414
