t5-end2end-questions-generation

This model is a fine-tuned version of t5-base on the squad_modified_for_t5_qg dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5678

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: 0.0001
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 7

Training results

Training Loss Epoch Step Validation Loss
2.584 0.34 100 1.9108
1.9664 0.68 200 1.7275
1.842 1.02 300 1.6641
1.7417 1.35 400 1.6368
1.713 1.69 500 1.6219
1.6899 2.03 600 1.6046
1.6302 2.37 700 1.5961
1.6259 2.71 800 1.5946
1.6107 3.05 900 1.5879
1.5689 3.39 1000 1.5865
1.5688 3.73 1100 1.5722
1.5519 4.06 1200 1.5792
1.5343 4.4 1300 1.5737
1.5214 4.74 1400 1.5745
1.5169 5.08 1500 1.5736
1.4954 5.42 1600 1.5730
1.4827 5.76 1700 1.5680
1.5015 6.1 1800 1.5701
1.4769 6.44 1900 1.5732
1.4765 6.77 2000 1.5678

Framework versions

  • Transformers 4.27.4
  • Pytorch 1.13.1+cu116
  • Datasets 2.11.0
  • Tokenizers 0.13.2
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Dataset used to train pranjalsurana/t5-end2end-questions-generation