imdatta0

imdatta0

qwen3-4b-swegym-moto-kl02-multitrain-grpo-b04-lr1e6-s12-adapter

Dedicated Endpoints

Run this model inference on single tenant GPU with unmatched speed and reliability at scale.

Learn more
Container

Run this model inference with full control and performance in your environment.

Learn more

Get help setting up a custom Dedicated Endpoints.

Talk with our engineer to get a quote for reserved GPU instances with discounts.

README

Qwen3-4B SWE-Gym Moto KL02 Multi-Train GRPO Probe Adapter

LoRA adapter checkpoint from the short multi-file-train GRPO probe.

Local run: 20260604_231110_swegym_q4b-kl02-multitrain-grpo-b04-lr1e6-s12_389b336

Source checkpoint: checkpoints/best_holdout

This run started from the Qwen3-4B KL02 adapter and trained for 12 GRPO steps on the generated multi-file train split with beta 0.04 and learning rate 1e-6. The held-out baseline at step 0 and periodic step 12 eval were both greedy 8/35 with mean reward 0.4234, so best_holdout is the step-0 best checkpoint selected by the run.

This checkpoint is preserved for reproducibility, not as a new best model.

Model provider

imdatta0

imdatta0

Model tree

Base

unsloth/Qwen3-4B-Instruct-2507

Adapter

this model

Modalities

Input

Text

Output

Text

Pricing

Dedicated Endpoints

View details

Supported Functionality

Model APIs

Dedicated Endpoints

Container

More information

Explore FriendliAI today