oknashar-bert

This model is a fine-tuned version of mosaicml/mosaic-bert-base on the wikipedia dataset. It achieves the following results on the evaluation set:

• eval_loss: 7.6172
• eval_runtime: 68.6888
• eval_samples_per_second: 22.813
• eval_steps_per_second: 0.364
• epoch: 2.84
• step: 500

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: 10
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 80
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Framework versions

• Transformers 4.18.0
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.12.1