|
--- |
|
license: mit |
|
datasets: |
|
- omarmomen/babylm_10M |
|
language: |
|
- en |
|
metrics: |
|
- perplexity |
|
library_name: transformers |
|
--- |
|
# Model Card for omarmomen/structroberta_s2_final |
|
|
|
This model is part of the experiments in the published paper at the BabyLM workshop in CoNLL 2023. |
|
The paper titled "Increasing The Performance of Cognitively Inspired Data-Efficient Language Models via Implicit Structure Building" (https://aclanthology.org/2023.conll-babylm.29/) |
|
|
|
<strong>omarmomen/structroberta_s2_final</strong> is a modification on the Roberta Model to incorporate syntactic inductive bias using an unsupervised parsing mechanism. |
|
|
|
This model variant places the parser network after 4 attention blocks. |
|
|
|
The model is pretrained on the BabyLM 10M dataset using a custom pretrained RobertaTokenizer (https://huggingface.co/omarmomen/babylm_tokenizer_32k). |
|
|
|
https://arxiv.org/abs/2310.20589 |
