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mobilebert_add_GLUE_Experiment_qnli_256

This model is a fine-tuned version of google/mobilebert-uncased on the GLUE QNLI dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6931
  • Accuracy: 0.5054

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
0.6933 1.0 819 0.6932 0.4946
0.6932 2.0 1638 0.6932 0.4946
0.6932 3.0 2457 0.6931 0.5054
0.6932 4.0 3276 0.6933 0.4946
0.6932 5.0 4095 0.6931 0.5054
0.6932 6.0 4914 0.6931 0.5054
0.6932 7.0 5733 0.6931 0.5054
0.6932 8.0 6552 0.6931 0.5054

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.8.0
  • Tokenizers 0.13.2
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Dataset used to train gokuls/mobilebert_add_GLUE_Experiment_qnli_256

Evaluation results