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hBERTv1_new_pretrain_rte

This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new on the GLUE RTE dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6896
  • Accuracy: 0.5307

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 Accuracy
0.7407 1.0 20 0.7002 0.4729
0.7061 2.0 40 0.7245 0.4729
0.7102 3.0 60 0.6949 0.5271
0.703 4.0 80 0.6951 0.4729
0.7097 5.0 100 0.6974 0.4729
0.7006 6.0 120 0.7053 0.4729
0.6986 7.0 140 0.6896 0.5307
0.6935 8.0 160 0.7711 0.4729
0.6109 9.0 180 0.8443 0.4982
0.469 10.0 200 1.0369 0.5126
0.3028 11.0 220 1.1621 0.5235
0.2155 12.0 240 1.2096 0.5379

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_rte

Evaluation results