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hBERTv2_new_pretrain_w_init__stsb

This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_wt_init on the GLUE STSB dataset. It achieves the following results on the evaluation set:

  • Loss: 2.0270
  • Pearson: 0.3743
  • Spearmanr: 0.3670
  • Combined Score: 0.3707

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
2.2654 1.0 45 2.4836 0.2041 0.1912 0.1976
1.9657 2.0 90 2.1138 0.2744 0.2547 0.2646
1.6665 3.0 135 2.2375 0.3087 0.3002 0.3044
1.3265 4.0 180 2.0270 0.3743 0.3670 0.3707
1.0731 5.0 225 2.3748 0.3294 0.3212 0.3253
0.7974 6.0 270 2.6753 0.3338 0.3353 0.3345
0.6738 7.0 315 2.5125 0.3590 0.3464 0.3527
0.5384 8.0 360 2.3740 0.3310 0.3211 0.3261
0.4589 9.0 405 2.3911 0.3709 0.3690 0.3699

Framework versions

  • Transformers 4.29.2
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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Dataset used to train gokuls/hBERTv2_new_pretrain_w_init__stsb

Evaluation results