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

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	0.7148
Best epoch	6
Trainable parameters	887,042
Total parameters	125,534,212

Method

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

Load

from peft import PeftModel
from transformers import AutoModelForSequenceClassification
base = AutoModelForSequenceClassification.from_pretrained("roberta-base", num_labels=2)
model = PeftModel.from_pretrained(base, "Anirudh7003/roberta-base-rte-lora")

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