Basemodel: roBERTa

Configs: Vocab size: 10,000 Hidden size: 512 Max position embeddings: 512 Number of layers: 2 Number of heads: 4 Window size: 256 Intermediate-size: 1024

Results:

Task: glue Score: 57.91 Confidence Interval: [56.98, 58.87]
Task: blimp Score: 58.40 Confidence Interval: [57.37, 59.23]

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Dataset used to train AISE-TUDelft/Custom-Activations-BERT-ReLU

Collection including AISE-TUDelft/Custom-Activations-BERT-ReLU

BRP Tiny-Transformers

Collection

Models for the 2024-Q4 BSc. Research Project: "Architectural Decisions for Language Modelling with Small Transformers". • 13 items • Updated Mar 2 • 1