Training run anchor_G16_20K
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Training run anchor_G16_20K has 590 facts recorded in Dontopedia across 99 references, with 56 live disagreements.
Mostly:has total steps(17), rdf:type(17), total steps(12)
Maturity scale
raw canonical shape-checked rule-derived certifiedHas Total Stepsin disputehasTotalSteps
Rdf:typein disputerdf:type
- Process[73]all time · 41
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- Machine Learning Training[80]all time · 127
- Process[81]all time · 161
- Process[82]all time · 158
- Training Run[83]all time · 165
- Model Run[85]all time · 209
- Machine Learning Training[86]all time · 242
- Process[88]all time · 251
Total Stepsin disputetotalSteps
Inbound mentions (75)
Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.
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Other facts (543)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
| Predicate | Value | Ref |
|---|---|---|
| Has Sequence Length | 1024 | [34] |
| Has Sequence Length | 2048 | [47] |
| Has Sequence Length | 512 | [48] |
| Has Sequence Length | 8192 | [58] |
| Has Sequence Length | 2048 | [86] |
| Has Sequence Length | 128 | [95] |
| Has Batch Size | 4 | [34] |
| Has Batch Size | 16 | [40] |
| Has Batch Size | 8 | [47] |
| Has Batch Size | 64 | [48] |
| Has Batch Size | 64 | [58] |
| Has Batch Size | 8 | [86] |
| Has Step | 4000 | [51] |
| Has Step | 25/1245 | [56] |
| Has Step | 1000 | [68] |
| Has Step | 100 | [85] |
| Has Step | 200 | [85] |
| Has Step | 300 | [85] |
| Has Learning Rate | 0.0001 | [40] |
| Has Learning Rate | 3e-04 | [47] |
| Has Learning Rate | 0.0000129 | [82] |
| Has Learning Rate | 0.0001 | [86] |
| Has Learning Rate | 0.0005 | [95] |
| Has Metric Value | 9.3 | [90] |
| Has Metric Value | 55.7 | [90] |
| Has Metric Value | 61 | [90] |
| Has Metric Value | 64.4 | [90] |
| Has Metric Value | 67.8 | [90] |
| Has Bpb Value | 3.583 | [90] |
| Has Bpb Value | 3.328 | [90] |
| Has Bpb Value | 3.183 | [90] |
| Has Bpb Value | 3.096 | [90] |
| Has Bpb Value | 3.05 | [90] |
| Has Warmup Steps | 500 | [40] |
| Has Warmup Steps | 500 | [47] |
| Has Warmup Steps | 50 | [58] |
| Has Warmup Steps | 300 | [86] |
| Has Loss | 1.494 | [48] |
| Has Loss | 4.9122 | [56] |
| Has Loss | 0.3609 | [63] |
| Has Loss | 0.9332 | [68] |
| Time Elapsed | 32s | [85] |
| Time Elapsed | 64s | [85] |
| Time Elapsed | 97s | [85] |
| Time Elapsed | 1.7 | [88] |
| Presupposes Ongoing | Language Model | [10] |
| Presupposes Ongoing | Training Run | [22] |
| Presupposes Ongoing | null | [52] |
| Has Best Loss | 1.5656 | [15] |
| Has Best Loss | 6.04 | [75] |
| Has Best Loss | 3.6777 | [76] |
| Is Complete | 50,000/50,000 iters | [15] |
| Is Complete | true | [38] |
| Is Complete | Yes | [61] |
| Has Elapsed Time | ~2.5 hours | [18] |
| Has Elapsed Time | 268s | [33] |
| Has Elapsed Time | 303s | [33] |
| Is Ongoing | At Step 6000 | [23] |
| Is Ongoing | Training | [28] |
| Is Ongoing | true | [47] |
| Has Ppl at Step | 2216.6 | [33] |
| Has Ppl at Step | 2789.1 | [33] |
| Has Ppl at Step | 2732.6 | [33] |
| Has Tok Per S | 12074 | [33] |
| Has Tok Per S | 12062 | [33] |
| Has Tok Per S | 13611 | [63] |
| Has Lite Phase | false | [40] |
| Has Lite Phase | false | [47] |
| Has Lite Phase | false | [86] |
| Tokens Per Second | 98782 | [48] |
| Tokens Per Second | 13027 | [85] |
| Tokens Per Second | 13186 | [85] |
| Has Lr | 0.0000943 | [48] |
| Has Lr | 0.0000916 | [51] |
| Has Lr | 9.00e-05 | [63] |
| Batch Size | 64 | [50] |
| Batch Size | 4 | [80] |
| Batch Size | 64 | [92] |
| Sequence Length | 256 | [50] |
| Sequence Length | 2048 | [80] |
| Sequence Length | 256 | [92] |
| Has Bpb | 2.444 | [51] |
| Has Bpb | 0.521 | [63] |
| Has Bpb | 1.3463 | [68] |
| Loss at Step | 11.6429 | [85] |
| Loss at Step | 11.7602 | [85] |
| Loss at Step | 11.5419 | [85] |
| Ppl at Step | 113884.2 | [85] |
| Ppl at Step | 128058.6 | [85] |
| Ppl at Step | 102939.2 | [85] |
| Sys R at Step | 0.345 | [85] |
| Sys R at Step | 0.331 | [85] |
| Sys R at Step | 0.348 | [85] |
| Has Modality | Text Modality | [86] |
| Has Modality | Image Modality | [86] |
| Has Modality | Audio Modality | [86] |
| Lacks Observation of | 35K-step cliff | [97] |
| Lacks Observation of | gnorm explosion | [97] |
| Lacks Observation of | catastrophic forgetting | [97] |
| Has Final Val Loss | 3.7805 | [3] |
Timeline
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References (99)
ctx:discord/blah/general/part-119ctx:discord/blah/random/part-37ctx:discord/blah/safiersemantics/part-72ctx:discord/blah/training-and-evals/part-17ctx:discord/blah/training-and-evals/part-34ctx:discord/blah/unturf/part-67ctx:discord/blah/vidya/part-4ctx:discord/blah/vidya/part-3ctx:discord/blah/watt-activation/part-9ctx:discord/blah/watt-activation/part-21ctx:discord/blah/watt-activation/part-32ctx:discord/blah/watt-activation/part-39ctx:discord/blah/watt-activation/part-35ctx:discord/blah/watt-activation/part-44ctx:discord/blah/watt-activation/part-33ctx:discord/blah/watt-activation/part-58ctx:discord/blah/watt-activation/part-94ctx:discord/blah/watt-activation/part-91ctx:discord/blah/watt-activation/part-98ctx:discord/blah/watt-activation/part-95ctx:discord/blah/watt-activation/part-125ctx:discord/blah/watt-activation/part-127ctx:discord/blah/watt-activation/part-130ctx:discord/blah/watt-activation/part-133ctx:discord/blah/watt-activation/part-136ctx:discord/blah/watt-activation/part-140ctx:discord/blah/watt-activation/part-150ctx:discord/blah/watt-activation/part-155ctx:discord/blah/watt-activation/part-169ctx:discord/blah/watt-activation/part-201ctx:discord/blah/watt-activation/part-210ctx:discord/blah/watt-activation/part-202ctx:discord/blah/watt-activation/part-212ctx:discord/blah/watt-activation/part-211ctx:discord/blah/watt-activation/part-217ctx:discord/blah/watt-activation/part-230ctx:discord/blah/watt-activation/part-244ctx:discord/blah/watt-activation/part-239ctx:discord/blah/watt-activation/part-231ctx:discord/blah/watt-activation/part-238ctx:discord/blah/watt-activation/part-252ctx:discord/blah/watt-activation/part-253ctx:discord/blah/watt-activation/part-247ctx:discord/blah/watt-activation/part-264ctx:discord/blah/watt-activation/part-267ctx:discord/blah/watt-activation/part-326ctx:discord/blah/watt-activation/part-331ctx:discord/blah/watt-activation/part-336ctx:discord/blah/watt-activation/part-373ctx:discord/blah/watt-activation/part-372ctx:discord/blah/watt-activation/part-378ctx:discord/blah/watt-activation/part-377ctx:discord/blah/watt-activation/part-396ctx:discord/blah/watt-activation/part-397ctx:discord/blah/watt-activation/part-398ctx:discord/blah/watt-activation/part-417ctx:discord/blah/watt-activation/part-421ctx:discord/blah/watt-activation/part-419ctx:discord/blah/watt-activation/part-462ctx:discord/blah/watt-activation/part-645ctx:discord/blah/watt-activation/part-660ctx:discord/blah/watt-activation/part-662ctx:discord/blah/watt-activation/part-661ctx:discord/blah/watt-activation/part-687ctx:discord/blah/watt-activation/part-702ctx:discord/blah/watt-activation/part-703ctx:discord/blah/watt-activation/part-705ctx:discord/blah/watt-activation/part-706ctx:discord/blah/watt-activation/part-714ctx:discord/blah/watt-activation/part-37ctx:discord/blah/watt-activation/part-86ctx:discord/blah/watt-activation/part-215ctx:discord/blah/training-and-evals/41- full texttraining-and-evals-41text/plain3 KB
doc:agent/training-and-evals-41/95b41334-d198-4a88-be0d-bc22c528e602Show excerpt
[2026-03-16 21:05] foxhop.: ● 23.6GB — that's tight on the 4090 (24GB). Batch 16 might OOM. Let me check with batch 8: ● Bash(python3 -c " n_embd=1536; n_layer=16; block_size=1024; total=467466240…) ⎿ batch= 4: 11.5 GB OK ba…
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doc:agent/vidya-10/636e1043-0585-44b0-86c4-ecbe60c83f00Show excerpt
[2026-03-20 11:25] foxhop.: awesome new video card with 12G & over 3k cuda cores! [2026-03-20 11:25] foxhop.: ? [2026-03-20 11:27] foxhop.: "We're building the disk." [2026-03-20 11:28] foxhop.: this screams GPT switch all "the" toward "a" …
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doc:agent/watt-activation-44/35af5294-4efe-43b8-a39d-23df23087144Show excerpt
[2026-03-07 05:32] xenonfun: ``` Not good. The loss trajectory tells a clear story: ┌────────┬─────────────────────────┐ │ Iters │ Avg Loss │ ├────────┼─────────────────────────┤ │ 0-2K │ 6.56 (learning) │…
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doc:agent/watt-activation-87/21549fe5-2355-4b51-9d7e-42d9fb1af8c0Show excerpt
[2026-03-07 21:54] xenonfun: ``` iter 8000/10000 | loss=4.2647 | PPL=71.1 | lr=6.16e-05 | 2.2 it/s (9.1K tok/s) | mem=1848MB peak=20665MB Saved checkpoint: ./akan_gpt2_checkpoints/checkpoint_iter_8000.npz iter 8500/10000 | loss=4.2438…
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doc:agent/watt-activation-91/61aeb5f1-b837-4123-a6c4-b76d719d0b25Show excerpt
[2026-03-08 00:46] xenonfun: ``` Looks good. Now let me calculate the exact iterations and launch: - 133M tokens / 4096 = 32,471 iters per epoch - 2 epochs = 64,942 total iters - Already done: 10,000 - Remaining: 54,942 iters (rou…
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doc:agent/watt-activation-126/dddfc295-807c-4943-b01a-f4f0a977c17eShow excerpt
[2026-03-09 04:03] xenonfun: ### What context count we do at this scale? ⏺ From the measurements we have, memory scales roughly linearly with total tokens in the batch: - BS=4, seq=1024 → 4,096 tokens → ~40 GB - BS=8, seq=1024 → 8,192 …
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doc:agent/watt-activation-125/078b0573-153a-47f9-81de-fbf8dd1915e3Show excerpt
[2026-03-09 03:33] xenonfun: ❯ we want to do 2K seq tho ⏺ Doubling seq doubles the activation memory. BS=8, seq=2048 = same logit tensor size as BS=16, seq=1024 — which hit 85GB. We need to re-check BS. BS=4, seq=2048 = 8,192 tokens/bat…
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doc:agent/watt-activation-127/aedb2d68-0e0d-4e54-ace8-64c39f6403e3Show excerpt
[2026-03-09 04:13] xenonfun: [resume] loading step_002000... resumed at step 2000, data_pos=16,392,000 [train] 16,670 steps | BS=4 SEQ=2048 | LR=1e-04 warmup=500 save every 2000 | val every 2000 | log every 100 checkpoint…
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doc:agent/watt-activation-161/b2429cd0-9f7a-4b1b-847e-3785f26f96b4Show excerpt
[2026-03-09 18:10] xenonfun: ``` Prompt: 'The most important discovery in science was' temp=0.8 top_k=40 stop=<|endoftext|> (100257) [compiled] ──────────────────────────────────────────────────────────── The most important discovery in…
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doc:agent/watt-activation-158/746cbfb1-750c-4df5-ae90-78f0235bc1e9Show excerpt
[2026-03-09 16:27] xenonfun: ⏺ For batch prefill, each attention class's forward() currently runs _gated_cumsum over the full sequence and returns output — but throws away the final recurrent state. The step() method maintains that state …
ctx:discord/blah/watt-activation/165- full textwatt-activation-165text/plain3 KB
doc:agent/watt-activation-165/c02ae72f-c534-45a9-adc3-f12c4275a06bShow excerpt
[2026-03-09 19:01] xenonfun: ``` Mode: qa temp=0.8 top_k=40 stop=<|endoftext|> (100257) [compiled] Instruction: 'What is photosynthesis?' ──────────────────────────────────────────────────────────── What is photosynthesis? The followin…
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doc:agent/watt-activation-189/ee6e7700-8f8f-458c-bd97-cd00204ffe29Show excerpt
[2026-03-10 03:42] xenonfun: ``` What the fix looks like: Coupling κ_g is a scalar per group. Its gradient through the sync step is tractable: at first order, Δcoupling_g ∝ -(∂loss/∂spectra_synced) · (mean_spec_g - spectra_g) — the reado…
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doc:agent/watt-activation-209/d7eabcf9-d506-432f-9a2c-b25cf5ef8ccdShow excerpt
[2026-03-11 03:51] xenonfun: ```# coupling (K) and adjacency are structural constants — not updated. 598 + # v2: update harmonic_coeffs (G×H learned frequency weights) 599 + # v3: update mode_amplitudes (k scalars,…
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doc:agent/watt-activation-242/e65441d2-9807-493e-a096-3ab8edf76fd5Show excerpt
[2026-03-12 04:42] xenonfun: (files: Screenshot_2026-03-12_at_12.41.55_AM.png) [2026-03-12 04:49] xenonfun: `http://phase-pipeline.xenon.fun.local:8000/dashboard` it sets routes like this but if I refresh browser page those don't resolve b…
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doc:agent/watt-activation-246/e98a7e00-4e3f-4e35-bccb-faff629fa820Show excerpt
[2026-03-12 07:06] xenonfun: ```[03:04:05] step 2000/12432 16.1% txt=4.411(82ppl) img=0.000 aud=2.025 r=0.375 lr=4.79e-05 150ms 69,028tok/s [T:1000 I:0 A:1000] eta=26min VAL step 2000 loss=4.4035 ppl=81.7 * best [03:04:29] …
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doc:agent/watt-activation-251/0d79165d-ca43-48df-b924-6b76b157d1a5Show excerpt
[2026-03-12 13:11] xenonfun: ✅ Phase 0 confirmed working — r_global rises monotonically from 0.07 → 0.96 across 16 steps on the production multimodal checkpoint. The architecture supports iterative generation. This is the green light to p…
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doc:agent/watt-activation-264/555cd9a1-321c-4f18-8f17-7bef422894a1Show excerpt
[2026-03-13 05:30] xenonfun: ``` I wrote the full plan in docs/claude/plans/tokenizerless_phase_stream_plan.md. Core recommendation from the plan: - do not do pure one-byte-per-step modeling first - build a tokenizerless byte_patch…
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doc:agent/watt-activation-352/f9fe3319-d5f4-4e70-b415-d397928b4c05Show excerpt
[2026-03-17 06:32] xenonfun: ``` 44 +├── antenna.py # AntennaHarmonicBlock + AntennaLM: field-mediated byte LM 45 +├── antenna_probes.py # Diagnostic probes: impulse, memory, coupling, leakage, boundary 46 +├── an…
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doc:agent/watt-activation-371/9ac097b4-3d34-4fad-bc53-d4097529d8abShow excerpt
[2026-03-18 17:41] xenonfun: ``` ❯ how expensive are probes? ⏺ Let me check what the probes actually do at the --probe-every 2000 interval. ⏺ Searched for 1 pattern (ctrl+o to expand) ⏺ At --probe-every 2000, each probe step runs: 1. …
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doc:agent/watt-activation-370/319ffc75-f6e3-490e-bf32-ddb97e36692cShow excerpt
[2026-03-18 17:29] xenonfun: ⏺ Here's the status: Implementation complete and pushed: - AnchorBind module in harmonic_mlx/antenna.py — 32 soft anchors on S^{d_bind-1}, softmax assignment, residual fusion - Wired into AntennaHarmonicB…
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[2026-03-18 19:30] xenonfun: ``` checkpoint dir: checkpoints/ham_G16_20K ──────────────────────────────────────────────────────────────────────── step 200/20000 1.0% BPB=4.149 r=0.228 SNR=-12.7dB C=0.7b lr=9.95e-05 80,154tok/s …
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[2026-03-19 04:31] xenonfun: ``` Mode: byte-level temp=0.7 max_tokens=300 Prompt: 'The quick brown fox ' ──────────────────────────────────────────────────────────── The quick brown fox ris pis se te at ti odinrbar 0bouone…
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[2026-03-21 23:19] xenonfun: ``` === BPE-8K: cache growth 200→2000 === Loaded 20480128 bytes from /Users/ms/MS/HarmonicMLX/data/fineweb_edu_bpe8k.npy KickModel ANALYTICAL training: 30000 steps, seq_len=128, lr=0.0005, momentum=0.9…
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[2026-04-19 09:46] xenonfun: loaded 24999946 bytes from /Users/ms/MS/HarmonicRust/data/curriculum/domain_tinystories.bin step 0 loss=6.1092 bpb=8.814 gnorm=10.6885 lr=4.00e-6 9259 tok/s step 50 loss=2.8955 bpb=4.177 gnorm=2.2132…
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[2026-04-20 00:14] xenonfun: ``` ⏺ Run complete. Task #5 done. Final head-to-head: ┌────────────┬────────────┬─────────────────────────────┐ │ │ V1 rotadam │ V2 fixed │ ├────────────┼────────────┼────…
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[2026-04-23 19:13] xenonfun: ``` Register match: partial. - ✅ tinystories/narrative show real conditioning — "little bear", "mommy", "kitchen", "store", "pigs", simple-declarative register. Recognizable. - ❌ edu/science/dense_science/…
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[2026-05-01 02:47] xenonfun: It wants 150M or so so think the chatgpt-2 in 24hr is looking achievable. we do need to get more dataset here. [2026-05-01 02:50] lisamegawatts: mines downloading datasets and parsing now, added a 4096 option [2…
See also
- Training AI Unturf Com Dashboard
- Stock Market Ticker
- Experiments
- Checkpoint Bin Iter 12300
- Checkpoint Best Bin
- Planning Optimizations
- Ajaxdavis Training
- Sometimes
- Hung Training Run
- Training Step 2000
- Microgpt Scaled
- Training Steps
- Inference Section
- Gelation Signals
- Language Model
- Xenonfun
- Optimizations
- Iteration 54600
- Wikipedia Factoid
- Fine Tuned Version
- V7 Loss Territory
- True
- Kuramoto Model
- Raw V8k
- At 16000
- Adam
- At Iter 13000
- Iter 10000
- Loss
- Implied
- Epoch 1
- Step 2000
- Step 002000
- Reduce Loss
- Homebrew Llm Training
- At Step 6000
- Model
- Training Step 12100
- Epoch Completion
- Training Step 12000
- Validation Step 12000
- Training
- Lr Reduced
- Lr Reduced Phase
- Loss Trend
- Step 006000
- Instruction Data
- Loss Decrease
- Step 50
- Rotational Adamw
- Step 150
- Current Run
- Checkpoint
- 10k Steps
- Phase Metrics Sidecar
- Gpu
- Checkpoints Bpe8k Lohe Spherical
- Training Step 25
- Diffusion Params
- Basic to Legit
- Step 200
- Step 100
- Wirelm
- Earlier Testing
- Step 200 to Step 1200
- Checkpoints Ham G16 20k
- Codec
- Small Corpus
- Python Salon
- Option B Rotational Adamw
- Lohe Delta
- Yes
- Bpb Metric
- No Nan No Panic
- Done in 10 4h
- Best Training Bpb
- Final Stats Table
- Step 9000
- Bpb Loss Tok S
- Step 250
- Final
- Step 5000
- Step 180
- Llrd 0.8
- Process
- Shakespeare
- Ocaml 5 Domains
- Training Process
- Loss Table
- Final Model File
- Prefecter
- Gpu Stalling
- Training Run
- Machine Learning Training
- Cl100k
- Model Run
- Text Modality
- Image Modality
- Audio Modality
- Checkpoint Directory
- Kick Model
- Analytical
- Fineweb Edu Bpe8k.npy
- Omega Vector
- Training Done
- Event
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