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QNLI

This model is a fine-tuned version of google-t5/t5-base on the GLUE QNLI dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2215
  • Accuracy: 0.9282

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.2856 1.0 1637 0.2216 0.9149
0.2258 2.0 3274 0.2060 0.9220
0.1791 3.0 4911 0.2038 0.9277
0.1476 4.0 6548 0.2215 0.9282
0.1263 5.0 8185 0.2301 0.9279

Framework versions

  • Transformers 4.43.3
  • Pytorch 1.11.0+cu113
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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Base model

google-t5/t5-base
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Dataset used to train du33169/t5-base-finetuned-GLUE-QNLI

Evaluation results