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mobilebert_add_GLUE_Experiment_logit_kd_pretrain_mrpc

This model is a fine-tuned version of gokuls/mobilebert_add_pre-training-complete on the GLUE MRPC dataset. It achieves the following results on the evaluation set:

  • Loss: nan
  • Accuracy: 0.3162
  • F1: 0.0
  • Combined Score: 0.1581

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: 5e-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 F1 Combined Score
0.0 1.0 29 nan 0.3162 0.0 0.1581
0.0 2.0 58 nan 0.3162 0.0 0.1581
0.0 3.0 87 nan 0.3162 0.0 0.1581
0.0 4.0 116 nan 0.3162 0.0 0.1581
0.0 5.0 145 nan 0.3162 0.0 0.1581
0.0 6.0 174 nan 0.3162 0.0 0.1581

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.9.0
  • Tokenizers 0.13.2
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Dataset used to train gokuls/mobilebert_add_GLUE_Experiment_logit_kd_pretrain_mrpc

Evaluation results