{
  "id": 14794357,
  "title": "Why Axolotl Users On RunPod Lose Checkpoints Silently And How To Catch It Before Your Job Starts",
  "url": "https://urgent.news/2026/10/15/why-axolotl-users-on-runpod-lose-checkpoints-silently-and-how-to",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-10-15T21:25:39.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/franciscobooth/why-axolotl-users-on-runpod-lose-checkpoints-silently-and-how-to-catch-it-before-your-job-starts-3i5e"
  },
  "original_language": "en",
  "account": "Axolotl is a popular framework for fine-tuning machine learning models. However, issues can arise when running Axolotl on cloud GPU pods. A reporter discovered that on RunPod A40 pods, Axolotl checkpoints would silently fail due to insufficient disk space. The reporter set up a RunPod A40 with a 10GB network volume, installed ComputeFence and Axolotl 0.20.0, and ran computefence doctor to check system readiness. The output showed four warnings and two issues: no Accelerate configuration and a warning about low disk space on the /workspace volume. Despite the warnings, the GPU was functional. However, Axolotl's large dependency tree and checkpoint saving process could exceed the 20GB safe threshold, causing checkpoint saves to fail mid-run and losing trained weights. To prevent this, the reporter recommends either attaching a larger network volume or explicitly configuring checkpoints to save in the persistent volume using output_dir: /workspace/outputs. The disk check, computefence doctor, can be run before starting any Axolotl job to ensure system readiness.",
  "summary": "Axolotl is one of the cleanest fine-tuning frameworks available. The problem is not Axolotl. The problem is what happens to your checkpoints when you run it on a rented GPU pod. What I found running Axolotl on a real RunPod A40 Last night I spun up a RunPod A40 pod at $0.59 per hour with a 10GB network volume mounted at /workspace. I installed ComputeFence and then installed Axolotl 0.20.0.…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}