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add_BERT_24_stsb

This model is a fine-tuned version of gokuls/add_bert_12_layer_model_complete_training_new on the GLUE STSB dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4492
  • Pearson: 0.6090
  • Spearmanr: 0.6106
  • Combined Score: 0.6098

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
2.1466 1.0 45 2.2698 0.3930 0.3260 0.3595
1.4589 2.0 90 1.7726 0.5150 0.5141 0.5145
1.0006 3.0 135 1.4492 0.6090 0.6106 0.6098
0.6766 4.0 180 1.8200 0.5635 0.5672 0.5654
0.4849 5.0 225 2.1591 0.5213 0.5212 0.5213
0.3823 6.0 270 1.8541 0.5717 0.5716 0.5717
0.3158 7.0 315 1.8647 0.5777 0.5741 0.5759
0.2816 8.0 360 1.4985 0.6097 0.6083 0.6090

Framework versions

  • Transformers 4.30.2
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.13.0
  • Tokenizers 0.13.3
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Dataset used to train gokuls/add_BERT_24_stsb

Evaluation results