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metadata
tags:
  - generated_from_trainer
model-index:
  - name: bert-pretrained-wikitext-2-raw-v1
    results: []

bert-pretrained-wikitext-2-raw-v1

This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 7.9307
  • Masked ml accuracy: 0.1485
  • Nsp accuracy: 0.7891

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: 16
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Masked ml accuracy Nsp accuracy
7.9726 1.0 564 7.5680 0.1142 0.5
7.5085 2.0 1128 7.4155 0.1329 0.5557
7.4112 3.0 1692 7.3729 0.1380 0.5675
7.3352 4.0 2256 7.2816 0.1398 0.6060
7.2823 5.0 2820 7.1709 0.1414 0.6884
7.1828 6.0 3384 7.1503 0.1417 0.7109
7.0796 7.0 3948 7.0909 0.1431 0.7430
6.8699 8.0 4512 7.1666 0.1422 0.7238
6.7819 9.0 5076 7.2507 0.1467 0.7345
6.7269 10.0 5640 7.2654 0.1447 0.7484
6.6701 11.0 6204 7.3642 0.1439 0.7784
6.613 12.0 6768 7.5089 0.1447 0.7677
6.5577 13.0 7332 7.7611 0.1469 0.7655
6.5197 14.0 7896 7.5984 0.1465 0.7827
6.4626 15.0 8460 7.6738 0.1449 0.8030
6.4026 16.0 9024 7.7009 0.1457 0.7869
6.3861 17.0 9588 7.7586 0.1503 0.7955
6.3779 18.0 10152 7.7792 0.1494 0.8019
6.357 19.0 10716 7.8532 0.1479 0.7966
6.3354 20.0 11280 7.9307 0.1485 0.7891

Framework versions

  • Transformers 4.33.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3