baseline-roberta_pre_layer_norm-model
Model description
Base Model Architecture: Roberta Pre-Layer Norm
Training and evaluation data
BabyLM Dataset (CoNLL 2023 Workshop)
Training procedure
Masked language modeling
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100000
- training_steps: 400000
Framework versions
- Transformers 4.26.1
- Pytorch 1.12.0+cu113
- Datasets 2.10.0
- Tokenizers 0.13.2