bibert-v0.1

This model was fine-tuned from bert-base-uncased on the Hebrew Bible verses. It was trained to perfrom fill-mask of randomly masked words. It achieved loss of 1.32 after 4700 training iterations.

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1
• Datasets 2.14.4
• Tokenizers 0.13.3