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41554 blogs · [ { "id": "01a0875b-af90-713a-8dc0-1ae3aaa16452", "title": "WW-PGD: Projected Gradient Descent optimizer", "url": "https://calculatedcontent.com/2025/12/13/ww-pgd-projected-gradient-descent-optimizer/", "published_at": "2025-12-13T17:09:51+00:00" }, { "id": "01a0875b-af90-713a-8dc0-1ae3ab89eb18", "title": "WeightWatcher, HTSR theory, and the Renormalization Group", "url": "https://calculatedcontent.com/2024/12/24/weightwatcher-htsr-theory-and-the-renormalization-group/", "published_at": "2024-12-24T23:37:05+00:00" }, { "id": "01a0875b-af90-713a-8dc0-1ae3ac3eb309", "title": "Fine-Tuned Llama3.2: Bad Instructions ?", "url": "https://calculatedcontent.com/2024/10/07/fine-tuned-llama3-2-bad-instructions/", "published_at": "2024-10-08T00:44:37+00:00" }, { "id": "01a0875b-af90-713a-8dc0-1ae3ac84f3c2", "title": "What’s instructive about Instruct Fine-Tuning: a weightwatcher analysis", "url": "https://calculatedcontent.com/2024/10/07/whats-instructive-about-instruct-fine-tuning-a-weightwatcher-analysis/", "published_at": "2024-10-07T19:08:21+00:00" }, { "id": "01a0875b-af90-713a-8dc0-1ae3ad5426e4", "title": "Describing Double Descent with WeightWatcher", "url": "https://calculatedcontent.com/2024/03/01/describing-double-descent-with-weightwatcher/", "published_at": "2024-03-01T08:37:45+00:00" }, { "id": "01a0875b-af90-713a-8dc0-1ae3ae0c9eab", "title": "SVDSmoothing LLM Layers with WeightWatcher", "url": "https://calculatedcontent.com/2024/02/12/svdsmothing-llm-layers-with-weightwatcher/", "published_at": "2024-02-13T07:07:11+00:00" }, { "id": "01a0875b-af90-713a-8dc0-1ae3ae8d6fdd", "title": "Evaluating LLMs with WeightWatcher Part III: The Magic of Mistral, a Story of Dragon Kings", "url": "https://calculatedcontent.com/2024/01/29/evaluating-llms-with-weightwatcher-part-iii-the-magic-of-mistral-a-story-of-dragon-kings/", "published_at": "2024-01-30T06:48:27+00:00" }, { "id": "01a0875b-af90-713a-8dc0-1ae3af4b4263", "title": "Evaluating Fine-Tuned LLMs with WeightWatcher Part II: PEFT / LoRa Models", "url": "https://calculatedcontent.com/2024/01/27/evaluating-fine-tuned-llms-with-weightwatcher-part-ii-peft-lora-models/", "published_at": "2024-01-28T07:06:50+00:00" }, { "id": "01a0875b-af90-713a-8dc0-1ae3af7da056", "title": "Evaluating Fine-Tuned LLMs with WeightWatcher", "url": "https://calculatedcontent.com/2024/01/23/evaluating-fine-tuned-llms-with-weightwatcher/", "published_at": "2024-01-24T07:49:05+00:00" }, { "id": "01a0875b-af90-713a-8dc0-1ae3b0725556", "title": "WeightWatcher new feature: fix_fingers=’clip_xmax’", "url": "https://calculatedcontent.com/2023/03/21/weightwatcher-advanced-features-fix_fingers/", "published_at": "2023-03-21T22:03:54+00:00" } ] posts
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2025
WW-PGD: Projected Gradient Descent optimizer
original ↗
13 Dec 2025
2024
WeightWatcher, HTSR theory, and the Renormalization Group
original ↗
24 Dec 2024
Fine-Tuned Llama3.2: Bad Instructions ?
original ↗
8 Oct 2024
What’s instructive about Instruct Fine-Tuning: a weightwatcher analysis
original ↗
7 Oct 2024
Describing Double Descent with WeightWatcher
original ↗
1 Mar 2024
SVDSmoothing LLM Layers with WeightWatcher
original ↗
13 Feb 2024
Evaluating LLMs with WeightWatcher Part III: The Magic of Mistral, a Story of Dragon Kings
original ↗
30 Jan 2024
Evaluating Fine-Tuned LLMs with WeightWatcher Part II: PEFT / LoRa Models
original ↗
28 Jan 2024
Evaluating Fine-Tuned LLMs with WeightWatcher
original ↗
24 Jan 2024
2023
WeightWatcher new feature: fix_fingers=’clip_xmax’
original ↗
21 Mar 2023