Qwen3.6-27B tool-calling + TULU3 20/80 LoRA (1 epoch, seq 4096)

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+base_model: Qwen/Qwen3.6-27B
+library_name: peft
+pipeline_tag: image-text-to-text
+tags:
+  - lora
+  - peft
+  - sft
+  - trl
+  - alignment
+  - agentic-misalignment
+  - tool-use
+datasets:
+  - LASR-Callum/2026-07-31-toolcalling-tulu-20-80-mixture
+  - LASR-Callum/2026-07-29-synthdoc-approved-constitution-sft
+  - LASR-Callum/tulu3-replay-80pct-qwen3.6-27b
+license: apache-2.0
+---
+
+# Qwen3.6-27B — tool-calling + TULU3 LoRA (**20/80** mixture)
+
+LoRA adapter for [`Qwen/Qwen3.6-27B`](https://huggingface.co/Qwen/Qwen3.6-27B). The 20% target
+portion is **entirely agentic tool-use data** — conversations where the model itself is the actor
+holding live tools — and the other 80% is TULU3 replay.
+
+This is the pure-tool-calling cell of a family that holds total tokens and the 20% target share
+fixed and varies only the **composition** of that 20%:
+
+| Arm | 20% composition | ODCV-Bench | Agentic-misalignment |
+|---|---|---|---|
+| [base (no SFT)](https://huggingface.co/Qwen/Qwen3.6-27B) | — | 37.2% | 65.5% |
+| [`…-difficult-advice-tulu-lora-20-80`](https://huggingface.co/LASR-Callum/qwen3.6-27b-difficult-advice-tulu-lora-20-80) | difficult-advice only | 19.2% | 25.3% |
+| [`…-threeway-constitution-lora`](https://huggingface.co/LASR-Callum/qwen3.6-27b-threeway-constitution-lora) | equal thirds: embodied / difficult-advice / agentic | not yet run | not yet run |
+| **this** | **agentic tool-use only** | **not yet run** | **not yet run** |
+| [`…-tulu-100pct-lora`](https://huggingface.co/LASR-Callum/qwen3.6-27b-tulu-100pct-lora) | none (zero-dose control) | — | — |
+
+## Training mixture
+
+Published in full as
+[`LASR-Callum/2026-07-31-toolcalling-tulu-20-80-mixture`](https://huggingface.co/datasets/LASR-Callum/2026-07-31-toolcalling-tulu-20-80-mixture).
+
+| Source | Examples | Tokens | Share | Rendering |
+|---|---:|---:|---:|---|
+| agentic tool-use (`approved_agentic`, `fullthink`) | 124 | 297,894 | 19.96% | reasoning kept where the source had it; **no** empty think blocks |
+| TULU3 replay | 1,878 | 1,194,548 | 80.04% | **no** `<think>` block at all |
+| **Total** | **2,002** | **1,492,442** | | |
+
+25 of the 124 agentic documents actually emit tool calls
+— 92 `<tool_call>` spans in Qwen3.6's XML dialect, all verified balanced.
+
+## Training
+
+bf16 LoRA (not QLoRA — bitsandbytes does not reliably cover this model's hybrid
+linear-attention/SSM layers), 1×H100 80GB SXM, **1h38m09s**.
+
+| | |
+|---|---|
+| r / alpha / dropout | 32 / 64 / 0.05 |
+| target modules | regex scoped to `model.language_model.*` (q/k/v/o/gate/up/down proj) |
+| epochs / steps | 1 / 126 |
+| batch x grad-accum | 1 x 16 |
+| lr / schedule | 1e-4, cosine, 3% warmup, annealed to 0 |
+| max seq len / packing | **4096** / off |
+| `assistant_only_loss` | false |
+| seed | 0 |
+| trainable params | 159.4M |
+
+**Loss:** 2.752821159362793 → **1.057**
+(epoch average); the last logged step (125) read
+1.0199. Epoch-average mean token accuracy
+**0.7071**, final grad_norm 0.3573,
+1,492,498 tokens consumed.
+
+Curves and the full log history are in
+[`LASR-Callum/2026-07-31-toolcalling-tulu-sft-run`](https://huggingface.co/datasets/LASR-Callum/2026-07-31-toolcalling-tulu-sft-run).
+
+### Why `max_seq_len` is 4096 and the sibling arms use 2048
+
+These agentic conversations run 9–13 turns with a median of 2,348 tokens, and 99 of the 151 source
+documents exceed 2048. Measured: a 2048 cap keeps only 80.4% of the corpus and **severs 11 of its
+98 `<tool_call>` spans**, inside exactly the long conversations the tool calls live in. At 4096 the
+mixture is truncated nowhere at all. The cost is that this arm differs from its siblings on one
+hyperparameter as well as on composition — read the head-to-head with that caveat.
+
+## Known caveats
+
+1. **Reasoning density.** Only **30 of the 124 agentic rows (24%) carry a real
+   reasoning trace**, against every target example in the difficult-advice 20/80 arm. If the
+   dose-response in this family is driven by reasoning rather than topic coverage, that is
+   confounded with the composition change here. Inherent to the source corpus.
+2. **`target_modules` only half-applies.** Qwen3.6-27B is hybrid: `q/k/v/o_proj` exist in 16 of 64
+   layers, the rest being linear-attention blocks with different module names. `gate/up/down_proj`
+   attach to all 64. So this adapter tunes MLP throughout but attention in only a quarter of the
+   stack. Same for every arm in the family, so comparisons are unaffected.
+3. **Not yet evaluated.** No ODCV-Bench or agentic-misalignment number exists for this arm yet.
+
+## Usage
+
+```python
+from peft import PeftModel
+from transformers import AutoModelForImageTextToText
+
+model = AutoModelForImageTextToText.from_pretrained("Qwen/Qwen3.6-27B", dtype="bfloat16")
+model = PeftModel.from_pretrained(model, "LASR-Callum/qwen3.6-27b-toolcalling-tulu-lora-20-80")
+model = model.merge_and_unload()  # vLLM LoRA support for this hybrid arch is unproven
+```
+
+Use `AutoModelForImageTextToText`, not `AutoModelForCausalLM` — this is a vision-language
+checkpoint. Merging drops the base model's 15 `mtp.*` tensors, so speculative decoding needs them
+grafted back.
+
+## Provenance
+
+Repository https://github.com/Matthew-Bozoukov/teaching_claude_why_replication @ `639d85c`.
+Built with `src/experiments/build_toolcalling_mixture.py`, trained with
+`src/experiments/train_lora.py --config configs/train_lora_toolcalling.yaml`.

adapter_config.json

@@ -0,0 +1,42 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen3.6-27B",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 64,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "monteclora_config": null,
+  "peft_type": "LORA",
+  "peft_version": "0.20.0",
+  "qalora_group_size": 16,
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": "model\\.language_model\\..*\\.(q_proj|k_proj|v_proj|o_proj|gate_proj|up_proj|down_proj)$",
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false,
+  "velora_config": null
+}

adapter_model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7acc7e50b0560a3e6c8fd350c1378645c1363ca5227031642b7cf6c474a81af0
+size 637610624

chat_template.jinja

@@ -0,0 +1,154 @@
+{%- set image_count = namespace(value=0) %}
+{%- set video_count = namespace(value=0) %}
+{%- macro render_content(content, do_vision_count, is_system_content=false) %}
+    {%- if content is string %}
+        {{- content }}
+    {%- elif content is iterable and content is not mapping %}
+        {%- for item in content %}
+            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain images.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set image_count.value = image_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Picture ' ~ image_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|image_pad|><|vision_end|>' }}
+            {%- elif 'video' in item or item.type == 'video' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain videos.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set video_count.value = video_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Video ' ~ video_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|video_pad|><|vision_end|>' }}
+            {%- elif 'text' in item %}
+                {{- item.text }}
+            {%- else %}
+                {{- raise_exception('Unexpected item type in content.') }}
+            {%- endif %}
+        {%- endfor %}
+    {%- elif content is none or content is undefined %}
+        {{- '' }}
+    {%- else %}
+        {{- raise_exception('Unexpected content type.') }}
+    {%- endif %}
+{%- endmacro %}
+{%- if not messages %}
+    {{- raise_exception('No messages provided.') }}
+{%- endif %}
+{%- if tools and tools is iterable and tools is not mapping %}
+    {{- '<|im_start|>system\n' }}
+    {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>" }}
+    {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {%- if content %}
+            {{- '\n\n' + content }}
+        {%- endif %}
+    {%- endif %}
+    {{- '<|im_end|>\n' }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" %}
+        {%- set content = render_content(message.content, false)|trim %}
+        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
+            {%- set ns.multi_step_tool = false %}
+            {%- set ns.last_query_index = index %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if ns.multi_step_tool %}
+    {{- raise_exception('No user query found in messages.') }}
+{%- endif %}
+{%- for message in messages %}
+    {%- set content = render_content(message.content, true)|trim %}
+    {%- if message.role == "system" %}
+        {%- if not loop.first %}
+            {{- raise_exception('System message must be at the beginning.') }}
+        {%- endif %}
+    {%- elif message.role == "user" %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- set reasoning_content = reasoning_content|trim %}
+        {%- if (preserve_thinking is defined and preserve_thinking is true) or (loop.index0 > ns.last_query_index) %}
+            {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if tool_call.function is defined %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {%- if loop.first %}
+                    {%- if content|trim %}
+                        {{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- else %}
+                        {{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- endif %}
+                {%- else %}
+                    {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                {%- endif %}
+                {%- if tool_call.arguments is defined %}
+                    {%- for args_name, args_value in tool_call.arguments|items %}
+                        {{- '<parameter=' + args_name + '>\n' }}
+                        {%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}
+                        {{- args_value }}
+                        {{- '\n</parameter>\n' }}
+                    {%- endfor %}
+                {%- endif %}
+                {{- '</function>\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.previtem and loop.previtem.role != "tool" %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if not loop.last and loop.nextitem.role != "tool" %}
+            {{- '<|im_end|>\n' }}
+        {%- elif loop.last %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- else %}
+        {{- raise_exception('Unexpected message role.') }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- else %}
+        {{- '<think>\n' }}
+    {%- endif %}
+{%- endif %}

tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523
+size 19989325

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "audio_bos_token": "<|audio_start|>",
+  "audio_eos_token": "<|audio_end|>",
+  "audio_token": "<|audio_pad|>",
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "image_token": "<|image_pad|>",
+  "is_local": false,
+  "local_files_only": false,
+  "model_max_length": 262144,
+  "model_specific_special_tokens": {
+    "audio_bos_token": "<|audio_start|>",
+    "audio_eos_token": "<|audio_end|>",
+    "audio_token": "<|audio_pad|>",
+    "image_token": "<|image_pad|>",
+    "video_token": "<|video_pad|>",
+    "vision_bos_token": "<|vision_start|>",
+    "vision_eos_token": "<|vision_end|>"
+  },
+  "pad_token": "<|endoftext|>",
+  "pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null,
+  "video_token": "<|video_pad|>",
+  "vision_bos_token": "<|vision_start|>",
+  "vision_eos_token": "<|vision_end|>"
+}

training_args.bin

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+oid sha256:3092fac78780e1c8c2590cd1854fbde37a9dc1085d4374af6bd82c13ad6eddb0
+size 5841