tiny_bert_rand_100_v1

This model is a fine-tuned version of on the Hartunka/processed_wikitext-103-raw-v1-rand-100 dataset. It achieves the following results on the evaluation set:

  • Loss: 10.8937
  • Accuracy: 0.1525

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
10.6718 4.1982 10000 10.8780 0.1503
10.0246 8.3963 20000 11.1520 0.1526
9.1704 12.5945 30000 11.7405 0.1529
8.1839 16.7926 40000 12.5604 0.1506
7.439 20.9908 50000 13.6428 0.1509

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-100
    self-reported
    0.153