Edit model card

wav2vec2-large-ft-fake-detection

This model is a fine-tuned version of facebook/wav2vec2-large on the alexandreacff/kaggle-fake-detection dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6694
  • Accuracy: 0.7103

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
0.6274 0.9851 33 0.6254 0.6206
0.4961 2.0 67 0.9477 0.6159
0.3391 2.9851 100 0.9273 0.6411
0.2857 4.0 134 0.6611 0.6617
0.3186 4.9851 167 0.7654 0.6215
0.2483 6.0 201 0.9395 0.6224
0.239 6.9851 234 0.8367 0.6542
0.2049 8.0 268 0.7709 0.6860
0.224 8.9851 301 0.6694 0.7103
0.2279 9.8507 330 0.7867 0.6822

Framework versions

  • Transformers 4.41.0.dev0
  • Pytorch 2.1.0a0+32f93b1
  • Datasets 2.19.1
  • Tokenizers 0.19.1
Downloads last month
23
Safetensors
Model size
316M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for alexandreacff/wav2vec2-large-ft-fake-detection

Finetuned
(17)
this model