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hBERTv2_new_pretrain_48_ver2_stsb

This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_48 on the GLUE STSB dataset. It achieves the following results on the evaluation set:

  • Loss: 2.0659
  • Pearson: 0.3927
  • Spearmanr: 0.3829
  • Combined Score: 0.3878

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: 64
  • eval_batch_size: 64
  • seed: 10
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Pearson Spearmanr Combined Score
2.3158 1.0 90 2.7785 0.1355 0.1181 0.1268
2.0193 2.0 180 2.6566 0.1954 0.2050 0.2002
1.7471 3.0 270 2.5202 0.2578 0.2647 0.2612
1.5032 4.0 360 3.0601 0.2605 0.2732 0.2668
1.1825 5.0 450 2.3378 0.3150 0.3180 0.3165
0.8788 6.0 540 2.3657 0.3437 0.3421 0.3429
0.6987 7.0 630 2.0659 0.3927 0.3829 0.3878
0.5879 8.0 720 2.6712 0.3631 0.3636 0.3634
0.4865 9.0 810 2.3066 0.3665 0.3625 0.3645
0.4233 10.0 900 2.2781 0.3753 0.3695 0.3724
0.3628 11.0 990 2.4672 0.3848 0.3758 0.3803
0.3113 12.0 1080 2.4339 0.3873 0.3809 0.3841

Framework versions

  • Transformers 4.34.0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.14.5
  • Tokenizers 0.14.1
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Dataset used to train gokuls/hBERTv2_new_pretrain_48_ver2_stsb

Evaluation results