tinybert_train_book_ent_15p_ra

This model is a fine-tuned version of distilbert-base-uncased on the gokulsrinivasagan/processed_wikitext-103-raw-v1-ld dataset. It achieves the following results on the evaluation set:

  • Loss: 2.7674
  • Accuracy: 0.5595

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: 200
  • eval_batch_size: 200
  • 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
3.7297 8.7413 10000 3.5039 0.4529
2.7471 17.4825 20000 2.6822 0.5690

Framework versions

  • Transformers 4.51.2
  • Pytorch 2.6.0+cu126
  • Datasets 3.5.0
  • Tokenizers 0.21.1
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Dataset used to train gokulsrinivasagan/tinybert_train_book_ent_15p_ra

Evaluation results

  • Accuracy on gokulsrinivasagan/processed_wikitext-103-raw-v1-ld
    self-reported
    0.559