bert-base-uncased-coqa

This model is a fine-tuned version of bert-base-uncased on the coqa 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: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.06
• num_epochs: 10.0

Training results

Framework versions

• Transformers 4.21.3
• Pytorch 1.7.1
• Datasets 1.18.3
• Tokenizers 0.11.6