superb_ks_42

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

  • Loss: -11.4695
  • Accuracy: 0.6209
  • Test Accuracy: 0.6209
  • Df Accuracy: 0.1405
  • Unlearn Overall Accuracy: 0.7402
  • Unlearn Time: 1016.6969

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: 5e-05
  • train_batch_size: 32
  • eval_batch_size: 8
  • seed: 42
  • 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

Training results

Training Loss Epoch Step Validation Loss Accuracy Overall Accuracy Unlearn Overall Accuracy Time
No log 1.0 160 -11.4695 0.1405 0.7402 0.7402 -1
No log 2.0 320 -36.0682 0.1405 0.7402 0.7402 -1
No log 3.0 480 -68.5442 0.1405 0.7402 0.7402 -1
No log 4.0 640 -104.9075 0.1405 0.7402 0.7402 -1
No log 5.0 800 -141.7108 0.1405 0.7402 0.7402 -1
No log 6.0 960 -175.9303 0.1405 0.7402 0.7402 -1
-173.4065 7.0 1120 -205.3526 0.1405 0.7402 0.7402 -1
-173.4065 8.0 1280 -228.1186 0.1405 0.7402 0.7402 -1
-173.4065 9.0 1440 -242.3865 0.1405 0.7402 0.7402 -1
-173.4065 10.0 1600 -247.2785 0.1405 0.7402 0.7402 -1

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.2+cu118
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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Dataset used to train jialicheng/unlearn_speech_commands_wav2vec2-large_neggrad_10_42

Evaluation results