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metadata
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: SeizureClassifier_Wav2Vec_B_43828665
    results: []

SeizureClassifier_Wav2Vec_B_43828665

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0355
  • Accuracy: 0.9950

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
1.1208 0.99 44 0.9389 0.8441
0.6807 1.99 88 0.5630 0.8911
0.3684 2.98 132 0.3547 0.9332
0.2786 4.0 177 0.2168 0.9678
0.1849 4.99 221 0.2235 0.9530
0.1888 5.99 265 0.1294 0.9802
0.1201 6.98 309 0.1461 0.9703
0.1017 8.0 354 0.1188 0.9777
0.0972 8.99 398 0.1194 0.9752
0.0819 9.99 442 0.0872 0.9851
0.0518 10.98 486 0.0550 0.9851
0.0604 12.0 531 0.0327 0.9975
0.0267 12.99 575 0.0542 0.9926
0.019 13.99 619 0.0354 0.9926
0.0167 14.92 660 0.0355 0.9950

Framework versions

  • Transformers 4.36.2
  • Pytorch 2.1.2+cu118
  • Datasets 2.16.1
  • Tokenizers 0.15.0