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hBERTv1_new_pretrain_w_init__stsb

This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_wt_init on the GLUE STSB dataset. It achieves the following results on the evaluation set:

  • Loss: 2.2584
  • Pearson: 0.0949
  • Spearmanr: 0.0892
  • Combined Score: 0.0920

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
2.5056 1.0 45 2.2584 0.0949 0.0892 0.0920
2.1254 2.0 90 2.6871 0.1250 0.1231 0.1241
1.9839 3.0 135 2.2709 0.1790 0.1840 0.1815
1.6299 4.0 180 2.5115 0.2691 0.2797 0.2744
1.3155 5.0 225 2.4555 0.3453 0.3437 0.3445
0.9686 6.0 270 2.8004 0.4571 0.4406 0.4489

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/hBERTv1_new_pretrain_w_init__stsb

Evaluation results