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Efficient Mlm M0.40 801010
E
Efficient Mlm M0.40 801010
Developed by princeton-nlp
This model studies the effectiveness of masking 15% content in masked language modeling, employing pre-layer normalization techniques not currently supported by HuggingFace.
Downloads 119
Release Time : 4/22/2022
Model Overview
This model focuses on masked language modeling tasks, exploring the impact of masking ratios on model performance, and implements pre-layer normalization techniques.
Model Features
Pre-layer normalization technique
Employs pre-layer normalization techniques not currently supported by HuggingFace, potentially improving model training stability
Masking ratio research
Specifically investigates the effectiveness of 15% masking ratio in masked language modeling
Model Capabilities
Masked language modeling
Text representation learning
Use Cases
Natural Language Processing
Pre-trained language model
Can serve as a foundational pre-trained model for other NLP tasks
Language understanding research
Used to study the impact of different masking ratios on language understanding
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