add_BERT_48_stsb

This model is a fine-tuned version of gokuls/add_bert_12_layer_model_complete_training_new_48 on the GLUE STSB dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7022
  • Pearson: 0.5286
  • Spearmanr: 0.5238
  • Combined Score: 0.5262

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
2.3047 1.0 45 2.9668 0.0943 0.0857 0.0900
2.1213 2.0 90 2.5339 0.1279 0.0928 0.1104
1.9666 3.0 135 2.2189 0.2727 0.2634 0.2681
1.636 4.0 180 2.6526 0.3479 0.3438 0.3459
1.1382 5.0 225 2.1790 0.4250 0.4209 0.4229
0.7856 6.0 270 2.3985 0.4820 0.5071 0.4946
0.5806 7.0 315 1.7992 0.5140 0.5093 0.5117
0.4372 8.0 360 1.7022 0.5286 0.5238 0.5262
0.3305 9.0 405 2.1792 0.5342 0.5367 0.5355
0.2799 10.0 450 1.7458 0.5254 0.5218 0.5236
0.2292 11.0 495 1.8574 0.5459 0.5466 0.5462
0.1945 12.0 540 1.7717 0.5571 0.5572 0.5571
0.1809 13.0 585 2.2290 0.5158 0.5209 0.5184

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_48_stsb

Evaluation results