bert-base-cased-wikitext2-test-mlm

This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 7.125

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: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: IPU
• gradient_accumulation_steps: 64
• total_train_batch_size: 256
• total_eval_batch_size: 20
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 10
• training precision: Mixed Precision

Training results

Framework versions

• Transformers 4.20.0
• Pytorch 1.10.0+rocm4.2
• Datasets 2.3.2
• Tokenizers 0.12.1