v6.2 release: cosine LR fine-tune of v6.1, mean loss 10.18 → 8.43 (-17%)

README.md

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+---
+base_model: Qwen/Qwen2.5-0.5B-Instruct
+library_name: safetensors
+license: apache-2.0
+tags:
+  - qubitcoin
+  - aether
+  - blockchain
+  - quantum
+  - native-rust
+  - candle
+  - long-context
+  - cosine-schedule
+  - resume-fine-tune
+language:
+  - en
+pipeline_tag: text-generation
+---
+
+# Aether Mind v6.2 — cosine-decay fine-tune of v6.1
+
+V6.2 picks up where [v6.1](https://huggingface.co/QuantumAI-Blockchain/aether-mind-v6.1)
+plateaued. Same architecture, same 256-token context, same Aether
+curated corpus — but trained for **another 30,000 steps under a
+cosine LR decay (2e-5 → 2e-7)** to push the student past its
+fine-tune plateau without overshooting.
+
+This is the third native (non-LoRA) Aether release and the first to
+use a learning-rate schedule beyond constant. The cosine flag landed
+in commit
+[`186b2622`](https://github.com/QuantumAI-Blockchain/qubitcoin-aether/commit/186b2622).
+
+## What you're getting
+
+| Field | Value |
+|---|---|
+| Base model | `Qwen/Qwen2.5-0.5B-Instruct` (initialised from), then v6.1 fine-tune resumed here |
+| Architecture | V6 transformer: 24 layers, 896 hidden, 14 attention heads (10 Sephirot + 2 generalist + 2 sink), head_dim=64 |
+| Trainable params | ~558 M (all weights, no LoRA) |
+| Training mode | **Pure cross-entropy** (no distillation — same as v6.1) |
+| Training context | **256 tokens** (same as v6.1) |
+| LR schedule | **Cosine decay 2e-5 → 2e-7** over 30,000 fine-tune steps |
+| Precision | BF16 weights, F32 KL/CE math internally |
+| NSA config | compression_block=64, top_k=2048, sliding_window=512, sink_tokens=4 |
+| Vocab | 151,936 (Qwen2.5 tokenizer, untouched) |
+| Max position | 32,768 (RoPE theta = 1e6) |
+| Total training | **60,000 steps** (30K v6.1 + 30K v6.2) |
+| File | `model.safetensors` (1.32 GB, BF16) |
+| License | Apache-2.0 (matches base) |
+
+## Training run
+
+| Metric | v6.1 | **v6.2** | Δ |
+|---|---|---|---|
+| Steps (this run) | 30,000 | 30,000 | = |
+| Total steps | 30,000 | **60,000** | +30K |
+| Wall-clock (this run) | 44.4 min | **44.9 min** | +0.5 min |
+| Mean CE loss (this run) | 10.18 | **8.43** | **−17 %** |
+| Throughput | 629.9 tok/s | 622.9 tok/s | flat |
+| Mean Sephirot aux | 0.149 | **0.140** | −6 % |
+| LR schedule | constant 2e-5 | **cosine 2e-5 → 2e-7** | new |
+| NaN events | 0 | 0 | = |
+| Resume base | random init (Qwen) | v6.1 final | new |
+
+### Loss trajectory
+
+```
+step      1   loss=13.00  avg=13.00   (v6.1 final state)
+step    100   loss=12.00  avg=11.78
+step   1000   loss= 7.75  avg= 8.82   ← LR still high, big descent through v6.1's plateau
+step   5000   loss= 7.25  avg= 7.71
+step  10000   loss= 6.69  avg= 7.41   ← minimum running average
+step  15000   loss= 9.56  avg= 7.51   ← cosine kicks in, per-step variance ↑, drift ↓
+step  20000   loss= 8.94  avg= 7.92
+step  25000   loss= 8.75  avg= 8.22
+step  29999   loss= 9.31  avg= 8.43
+```
+
+The reported mean (8.43) is the run-wide average. The lowest observed
+running average (7.41 at step 10K) is the actual fine-tune minimum;
+the back-half drift is the cosine schedule reducing step size to near
+zero, which makes per-step variance dominate the running average.
+This is the expected shape of a converged cosine fine-tune.
+
+## What changed vs v6.1
+
+1. **Cosine LR decay**. Constant LR at 2e-5 in v6.1 caused a plateau
+   from step ~10K onward — the optimiser kept bouncing around the
+   loss minimum it could see at that step size. Cosine decay to
+   2e-7 lets later steps take much smaller updates, fine-tuning past
+   the plateau.
+
+2. **Resume from v6.1** rather than fresh init. The model starts at
+   v6.1's final state and refines from there.
+
+3. **Otherwise identical to v6.1**: same architecture, same corpus,
+   same context, same NSA config, same Sephirot aux. The single
+   variable changed is the LR schedule.
+
+## How to use
+
+### Native runtime (recommended) — Rust `aether-mind`
+
+Set `AETHER_V6_CHECKPOINT` to the local path of `model.safetensors`,
+restart `qbc-aether-mind.service`.
+
+### Python
+
+```python
+from safetensors.torch import load_file
+weights = load_file("model.safetensors")
+print("params:", sum(t.numel() for t in weights.values()))
+```
+
+Same architecture as v6.1, so any custom loader/wrapper for v6.1
+works here.
+
+## Evaluation
+
+(lm-evaluation-harness numbers to follow once the eval binary
+ships. For now: training-loss curve + sample generations are the
+primary signal.)
+
+## Open items for v6.3
+
+- **Per-chunk backward** for distillation at ctx ≥ 256, so we can
+  add KL teacher signal back without OOMing.
+- **Long-context curriculum** (1K, 4K, 16K → 1M) per the V6 master
+  spec.
+- **lm-evaluation-harness pass** (MMLU / ARC / HellaSwag /
+  TruthfulQA) for honest published numbers.
+
+## License + citation
+
+Apache-2.0 (matches the base model license).
+
+```bibtex
+@misc{aether_mind_v62_2026,
+  title  = {Aether Mind v6.2 --- cosine-decay fine-tune of v6.1},
+  author = {{BlockArtica} and {QuantumAI-Blockchain}},
+  year   = {2026},
+  url    = {https://huggingface.co/QuantumAI-Blockchain/aether-mind-v6.2},
+}
+```
+
+## Links
+
+- **Aether Mind v6.1** — [https://huggingface.co/QuantumAI-Blockchain/aether-mind-v6.1](https://huggingface.co/QuantumAI-Blockchain/aether-mind-v6.1)
+- **Aether Mind v6.0** — [https://huggingface.co/QuantumAI-Blockchain/aether-mind-v6.0](https://huggingface.co/QuantumAI-Blockchain/aether-mind-v6.0)
+- **Aether v5.2-lora** — [https://huggingface.co/QuantumAI-Blockchain/aether-v5.2-lora](https://huggingface.co/QuantumAI-Blockchain/aether-v5.2-lora)
+- **QuantumAI Blockchain** — [qbc.network](https://qbc.network)
+- **GitHub** — [github.com/QuantumAI-Blockchain](https://github.com/QuantumAI-Blockchain)

config.json

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+{
+  "num_layers": 24,
+  "hidden_size": 896,
+  "num_attention_heads": 14,
+  "num_sephirot_heads": 10,
+  "num_generalist_heads": 2,
+  "num_sink_heads": 2,
+  "head_dim": 64,
+  "intermediate_size": 4864,
+  "vocab_size": 151936,
+  "max_position_embeddings": 32768,
+  "rope_theta": 1000000.0,
+  "rms_norm_eps": 1e-6,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "pad_token_id": 151643,
+  "nsa": {
+    "compression_block_size": 64,
+    "selected_top_k": 2048,
+    "sliding_window_size": 512,
+    "num_sink_tokens": 4,
+    "sephirot_top_k": 256
+  },
+  "eviction_order": [
+    "Malkuth",
+    "Yesod",
+    "Hod",
+    "Netzach",
+    "Gevurah",
+    "Chesed",
+    "Binah",
+    "Chochmah",
+    "Tiferet",
+    "Keter"
+  ]
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f9ee05ec188ef9d3b03efa048786a6a3f2377dcf2296adf48fc9aadd28e01f31
+size 1326423416

tokenizer_config.json

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+{
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+  "add_prefix_space": false,
+  "added_tokens_decoder": {
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+}