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baseline-roberta_pre_layer_norm-model
cambridge-climb/baseline-roberta_pre_layer_norm-model
baseline-roberta_pre_layer_norm-model is a fill-mask model from cambridge-climb. Use it when you need the model to fill a missing word. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Fill-Mask
- Library
- transformers
- License
- mit
- Model type
- roberta-prelayernorm
- Access
- Public
- Created
- Jul 6, 2023
- Updated
- Oct 11, 2023
- SHA
- 012a5797
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Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
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
- Task
- Fill-Mask
- Library
- transformers
- Type
- roberta-prelayernorm
- License
- mit
- Languages
- en
- Created
- Jul 6, 2023
- Updated
- Oct 11, 2023