{"version":1,"type":"story","url":"https://digestai.news/story/aws-shows-how-to-train-qwen3-vl-8b-with-skyrl-on-sagemaker-hyperpod","json":"https://digestai.news/story/aws-shows-how-to-train-qwen3-vl-8b-with-skyrl-on-sagemaker-hyperpod.json","markdown":"https://digestai.news/story/aws-shows-how-to-train-qwen3-vl-8b-with-skyrl-on-sagemaker-hyperpod.md","slug":"aws-shows-how-to-train-qwen3-vl-8b-with-skyrl-on-sagemaker-hyperpod","headline":"AWS shows how to train Qwen3-VL-8B with SkyRL on SageMaker HyperPod","summary":"AWS’s Machine Learning Blog demonstrated how to use **SkyRL**, an open-source reinforcement learning framework, to train **Qwen3-VL-8B**, a vision-language model, on **Amazon SageMaker HyperPod**. The setup improved the model’s maze-solving accuracy from **43.75%** to **96.875%** using **Group Relative Policy Optimization (GRPO)**. The blog outlines a step-by-step workflow, including container setup, cluster launch, job submission, and monitoring via **Ray Dashboard** and **Amazon Managed Grafana** dashboards.\n\nThe process leverages **HyperPod’s** cluster resiliency—automatically replacing failed nodes and restoring training from checkpoints—to avoid lost progress. **Amazon FSx for Lustre** provides shared storage for model weights and evaluation outputs. The blog also details deploying the trained **LoRA adapter** for inference using **Ray Serve**, enabling dynamic loading of adapters per request. The entire workflow is designed for reproducibility, with pre-built container images and hyperparameter tuning guidance.","keyPoints":["SkyRL improved Qwen3-VL-8B’s maze-solving accuracy from 43.75% to 96.875% using GRPO on SageMaker HyperPod","HyperPod’s cluster resiliency and FSx shared storage enable uninterrupted training and checkpoint recovery","Deployed adapters via Ray Serve support dynamic LoRA loading for inference, compatible with OpenAI API clients"],"whyItMatters":"This tutorial shows how to scale multimodal RL training on cloud infrastructure, reducing compute waste and downtime. It’s a practical guide for researchers deploying vision-language models with reinforcement learning, leveraging AWS’s managed services for resilience and efficiency.","category":{"slug":"research","name":"Research","url":"https://digestai.news/category/research"},"entities":{"companies":["AWS","Amazon SageMaker","Amazon EKS","Amazon FSx","Amazon S3","Ray"],"models":["Qwen3-VL-8B","SkyRL","VisGym"],"people":[]},"firstPublishedAt":"2026-09-25T16:18:07Z","updatedAt":"2026-09-25T16:18:07Z","sourceCount":1,"hasPrimarySource":true,"sources":[{"outlet":"AWS Machine Learning Blog","title":"Accelerate multimodal RL training with SkyRL on Amazon SageMaker HyperPod","url":"https://aws.amazon.com/blogs/machine-learning/accelerate-multimodal-rl-training-with-skyrl-on-amazon-sagemaker-hyperpod","publishedAt":"2026-09-25T16:18:07Z","type":"primary","primary":true,"lead":true}],"sourceNotes":null,"discussions":[],"thread":{"title":"AWS Expands SageMaker AI Capabilities","url":"https://digestai.news/thread/aws-adds-whisperx-to-sagemaker-for-speaker-labeled-audio-transcription","storyCount":3},"cite":{"text":"Digest AI, \"AWS shows how to train Qwen3-VL-8B with SkyRL on SageMaker HyperPod\", 25 September 2026, https://digestai.news/story/aws-shows-how-to-train-qwen3-vl-8b-with-skyrl-on-sagemaker-hyperpod","publisher":"Digest AI","title":"AWS shows how to train Qwen3-VL-8B with SkyRL on SageMaker HyperPod","datePublished":"2026-09-25T16:18:07Z","url":"https://digestai.news/story/aws-shows-how-to-train-qwen3-vl-8b-with-skyrl-on-sagemaker-hyperpod"},"generatedBy":"Written by Digest AI's editorial model from the linked sources; the sources are the record.","license":"Headlines, digests and key points are written by Digest AI and may be quoted with a link to the story page. Linked articles belong to their publishers. Terms: https://digestai.news/terms#reuse"}