distilbert_lda_50_v1_qnli

This model is a fine-tuned version of gokulsrinivasagan/distilbert_lda_50_v1 on the GLUE QNLI dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4075
  • Accuracy: 0.8212

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: 256
  • eval_batch_size: 256
  • seed: 10
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.5532 1.0 410 0.5177 0.7628
0.4263 2.0 820 0.4075 0.8212
0.3371 3.0 1230 0.4169 0.8133
0.2505 4.0 1640 0.4766 0.8116
0.18 5.0 2050 0.6080 0.7941
0.1275 6.0 2460 0.6769 0.8120
0.0953 7.0 2870 0.6988 0.7974

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.2.1+cu118
  • Datasets 2.17.0
  • Tokenizers 0.20.3
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Dataset used to train gokulsrinivasagan/distilbert_lda_50_v1_qnli

Evaluation results