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dikshant0520/
gemma-3-4b-it-pure-gold-baseline3-lora

Name: gemma-3-4b-it-pure-gold-baseline3-lora
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Gemma 3 4B IT - Pure Gold Baseline 3 LoRA

LoRA adapter for google/gemma-3-4b-it, fine-tuned on 2,000 gold-labelled driving-scene VQA examples. The adapter uses the language-model projection layers while leaving the vision tower frozen.

Training

Best checkpoint: step 240
Epochs: 2
LoRA rank/alpha/dropout: 16 / 32 / 0.10
Learning rate: 1e-4
Effective batch size: 15 across three GPUs
Best validation loss: 0.49810

Evaluation

On the shared 5,000-example evaluation set, mean LingoScore was 0.43315, median was 0.26127, and 32.24% of predictions scored at least 0.8.

Inference

Accept the Gemma license before downloading the base model. See inference.py --help. The input CSV requires question_id and question; the image parquet must contain the selected join column and an images column.

python inference.py --adapter dikshant0520/gemma-3-4b-it-pure-gold-baseline3-lora --input-csv evaluation.csv --image-parquet images.parquet --output-csv predictions.csv