RoBERTa-base fine-tuned on GLUE RTE (adapter)

This checkpoint is one learning experiment comparing Full Fine-Tuning, BitFit, adapters, and LoRA on GLUE Recognizing Textual Entailment (RTE). It uses seed 42 and selects the highest validation epoch.

Metric	Value
Best validation accuracy	0.5271
Best epoch	3
Trainable parameters	1,191,554
Total parameters	125,246,594

Method

adapter. See the project README for the exact shared training configuration. This is an educational experiment, not a benchmark-level performance claim.

Load

# See load_adapter.py in this repository.
from load_adapter import load_model
model, tokenizer = load_model(".")

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