Replaced synthetic 'target' plots with the actual artifacts produced by
running AISHA_RL_Training_Colab.ipynb on a Colab T4:
Pre-training Llama 3.2 3B baseline (force-report eval):
easy 0.150 medium 0.075 hard 0.000 avg 0.075
Post-GRPO Llama 3.2 3B (LoRA r=16, 28 prompts x 2 epochs, 112 steps):
easy 0.855 medium 0.590 hard 0.000 avg 0.482
Average lift: +0.41 (6.4x). Easy +0.71. Medium +0.52.
W&B run (real, 112 logged steps):
https://wandb.ai/sayujpillai63-itm/vapt-env-grpo/runs/ln2jq71s
Trained LoRA adapter on HF Hub:
https://huggingface.co/Sayuj63/vapt-env-llama32-3b-grpo
Updated artifacts in plots/:
baseline_scores.json, trained_scores.json
performance_comparison.png (real bar chart, no synthetic targets)
reward_per_episode.png (real W&B reward curve)
training_loss.png (real W&B loss curve)
wandb_run_url.txt (link to live dashboard)
README updated:
- Top-of-page now lists Live Space, Trained Adapter, W&B URL,
…
