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rob-base-superqa2

This model is a fine-tuned version of roberta-base on the None dataset.

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: 32
  • eval_batch_size: 32
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 256
  • total_eval_batch_size: 256
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 2.0

Training results

Framework versions

  • Transformers 4.21.1
  • Pytorch 1.11.0a0+gita4c10ee
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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Datasets used to train nbroad/rob-base-superqa2

Evaluation results