distilbert_rand_20_v2

This model is a fine-tuned version of on the Hartunka/processed_wikitext-103-raw-v1-rand-20_v2 dataset. It achieves the following results on the evaluation set:

  • Loss: 9.1981
  • Accuracy: 0.1533

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: 0.0001
  • train_batch_size: 96
  • eval_batch_size: 96
  • seed: 10
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 10000
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss Accuracy
9.0191 4.1982 10000 9.1692 0.1506
8.4686 8.3963 20000 9.4612 0.1513
7.4003 12.5945 30000 10.9042 0.1537
6.6138 16.7926 40000 12.2324 0.1513
6.312 20.9908 50000 12.8140 0.1511

Framework versions

  • Transformers 4.50.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.21.1
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Evaluation results

  • Accuracy on Hartunka/processed_wikitext-103-raw-v1-rand-20_v2
    self-reported
    0.153