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distilhubert-finetuned-superb-ks

This model is a fine-tuned version of ntu-spml/distilhubert on the superb dataset. It achieves the following results on the evaluation set:

  • eval_loss: 0.7530
  • eval_accuracy: 0.8809
  • eval_runtime: 49.792
  • eval_samples_per_second: 61.877
  • eval_steps_per_second: 7.752
  • epoch: 6.0
  • step: 38322

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: 8
  • 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
  • mixed_precision_training: Native AMP

Framework versions

  • Transformers 4.40.0.dev0
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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Dataset used to train halgoz/distilhubert-finetuned-superb-ks