Update training/AgentDebuggerEnv_GRPO_Training.ipynb

Update: Added final imporvements for hackathon

Fix: batch%num_generations math

Cuda returns false fixed

COMPUTE_DRIVE fix

Fix: Removed BitsandBytes

Fix: Fixed again again

Fix: Fixed again

Fix: Fixing Again

Fix: Fixing

Fix: Trying to fix dependency issues

Fix: Fixed file

fix: serialize bug_metadata as JSON to fix pyarrow mixed-type error

fix: upgrade bitsandbytes>=0.49.0 (triton.ops), switch to Qwen2.5-Coder-3B

fix: torch at build time, remove mergekit (conflicts accelerate/peft/trl)

fix: empty requirements.txt, install training deps at runtime

fix: remove wandb - click conflict with gradio causes resolution-too-deep

chore: normalize dataset inputs and fix mergekit dependency for TRL 0.14.0

Auto-detect GPU: bfloat16+batch2+gen8 on A100, float16+batch1+gen4 on T4 — same script works on both

Reduce max_completion_length to 160 for T4 speed: target 1000 steps in <8hrs

Optimize for Kaggle P100: float16, batch=1, grad_accum=8, num_gen=4, max_completion=256, lora_r=8

Fix GRPOConfig: rename max_new_tokens to max_completion_length for trl==0.14.0

Align gradio version with Hugging Face Space builder2

Stabilize Space runtime: pin ML deps and disable runtime package drift

Pin torch to cu121 build + use model.device instead of hardcoded cuda string

Replace unsloth with bitsandbytes+peft: fixes CUDA driver incompatibility on HF A100

Reduce training to 500 steps with tightened curriculum for A10G budget

Fix eval device selection with CUDA-safe fallback

Optimize for A100 80GB: 8 generations, batch 4, lr 2e-5, dense logging

Restore full 1000-step training with original curriculum

Reduce training to 500 steps with tightened curriculum for A10G budget

Add Gradio training monitor and fix subprocess python path

Update: Started making changes for the hackathon