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add_BERT_no_pretrain_stsb

This model is a fine-tuned version of on the GLUE STSB dataset. It achieves the following results on the evaluation set:

  • Loss: 2.3307
  • Pearson: 0.0719
  • Spearmanr: 0.0575
  • Combined Score: 0.0647

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: 4e-05
  • train_batch_size: 128
  • eval_batch_size: 128
  • seed: 10
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Pearson Spearmanr Combined Score
2.4937 1.0 45 2.6373 0.0410 0.0287 0.0348
2.22 2.0 90 2.4288 0.0740 0.0586 0.0663
2.1554 3.0 135 2.3869 0.0609 0.0498 0.0554
2.0556 4.0 180 2.5740 0.0800 0.0717 0.0759
2.0221 5.0 225 2.4656 0.0849 0.0654 0.0752
2.0403 6.0 270 2.3307 0.0719 0.0575 0.0647
2.1732 7.0 315 2.5174 0.0699 0.0584 0.0641
2.0399 8.0 360 2.5648 0.0718 0.0605 0.0662
2.0765 9.0 405 2.3373 0.0621 0.0491 0.0556
2.0538 10.0 450 2.6402 0.0463 0.0431 0.0447
2.0147 11.0 495 2.4727 0.0540 0.0471 0.0506

Framework versions

  • Transformers 4.30.2
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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Dataset used to train gokuls/add_BERT_no_pretrain_stsb

Evaluation results