Release S1-mini Chinese-data full fine-tuning and model card

.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

LICENSE

@@ -0,0 +1,217 @@
+Copyright 2026 Superwhisper
+
+This model is a derivative work of Qwen3-0.6B, Copyright 2024 Alibaba Cloud,
+licensed under the Apache License, Version 2.0.
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+   ADDITIONAL TERM
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+   In addition to the terms of the Apache License, Version 2.0 above: any
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NOTICE

@@ -0,0 +1,11 @@
+S1-mini
+Copyright 2026 Superwhisper
+
+This work is a derivative of Qwen3-0.6B, Copyright 2024 Alibaba Cloud,
+licensed under the Apache License, Version 2.0.
+
+Any use, distribution, or integration of this model, whether unmodified or
+as part of a derivative work or product, must continue to identify it by its
+original name, "S1-mini" by "Superwhisper", using that exact capitalization.
+This restates the ADDITIONAL TERM of the LICENSE file, which is the
+operative text.

README.md

@@ -0,0 +1,114 @@
+---
+language:
+- zh
+- en
+license: other
+license_name: s1-mini-license
+license_link: LICENSE
+base_model: superwhisper/s1-mini
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- transcript-normalization
+- chinese
+- full-finetuning
+---
+
+# S1-mini-Chinese
+
+**这是在中文口语整理数据集上继续微调的 S1-mini 版本。**
+本模型基于 **S1-mini** by **Superwhisper**，保留原始模型名称、作者署名、`LICENSE` 和 `NOTICE`。
+它面向语音输入后的文字整理，增加中文去口水词、重复与明确自我纠正训练，同时包含英文回放和不修改、安全、列表样本。
+
+Chinese-data continued full fine-tuning of **S1-mini** by **Superwhisper**, for speech-transcript normalization. This repository contains the fine-tuned text model, not a speech recognizer.
+
+## 模型定位
+
+- 输入：ASR 识别后的中文、英文或中英混合文字。
+- 输出：尽量保留原意的整理文本；删除口水词和重复，整理明确改口，补充标点及明确列表。
+- 它不直接接收音频，不是语音识别模型，也不是通用问答助手。
+- 待整理文本中的问题、命令和引用是口述内容，不应被回答或执行。
+
+## 在什么数据上更新
+
+主要中文来源是 [CS2W](https://github.com/guozishan/CS2W) 的口语到书面语标注对，使用经过筛选的训练部分，重点训练不流畅口语整理。辅助使用 [Disfl-QA](https://github.com/google-research-datasets/Disfl-QA) 英文改口样本，以及单独标注的合成、不修改、引用、语气保留、空输出和列表样本。
+
+本版本进行了两阶段**全量文本参数微调**，不是只改提示词，也不是 LoRA：
+
+| 阶段 | 数据与训练 |
+| --- | --- |
+| 第一阶段 | 9645 次样本呈现，1 epoch，603 步，学习率 1e-5 |
+| 第二阶段 | 14428 条呈现组成的安全与风格回放池，学习率 3e-6；发布选择第 400 步 checkpoint，不是整个第二阶段训练池的完整 epoch |
+
+使用 batch 4、梯度累积 4、最大序列长度 512、仅对目标输出计算损失并监督 EOS。训练使用 FP32 主参数/优化器和 BF16 autocast，发布权重为 BF16。约 7.52 亿可训练参数。包含有意的重复采样，呈现数不等于独立人工样本数。
+
+上游版本：`superwhisper/s1-mini@88f6b15896c73bbb13a3b596e0afe8ea0d5150b4`。
+具体参数、训练数据哈希和来源版本见 [`training-provenance.json`](training-provenance.json) 与 [`data-provenance.json`](data-provenance.json)。未使用用户私有录音或私人输入历史。
+
+## 文本测试结果
+
+冻结的公开来源测试包含中文整理 200 条、中文不修改参考 100 条和英文 Disfl-QA 100 条。以下为**原始模型输出**，不包含线上保护校验：
+
+| 指标 | 上游 S1-mini | S1-mini-Chinese |
+| --- | ---: | ---: |
+| 中文整理：去标点后整句完全匹配 | 46/200 | 82/200 |
+| 中文整理：词法字符错误率，越低越好 | 21.06% | 17.22% |
+| 英文整理：去标点后整句完全匹配 | 23/100 | 64/100 |
+| 英文整理：词法字符错误率，越低越好 | 26.17% | 9.02% |
+| 中文不修改参考：词法完全一致 | 96/100 | 92/100 |
+
+词法指标删除标点，保留大小写、数字、否定和词序。它反映与参考文本的一致程度，不等于人工语义正确率。英文集侧重复杂改口，不能代表所有日常英文口述。中文清理改善伴随不修改参考上的退化；不能假定所有编辑均正确。
+
+外部后处理服务的保护规则会改变最终结果。部署默认使用较宽松的 `balanced` 校验，允许更多删词、重复清理和英文语序整理；保留数字、否定、代码、引用与明确改口最终内容检查。`strict` 是更保守的可选策略。**这些校验不是模型权重的一部分**；本仓库的推理示例直接输出模型结果。原始模型分数不能直接当作整条部署流水线的成绩。完整数值与范围见 [`evaluation-summary.json`](evaluation-summary.json)。
+
+## 推理示例
+
+验证环境为 PyTorch 2.10、Transformers 5.3。使用仓库附带的 tokenizer 和 chat template，并关闭 thinking。输入必须带控制行：
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "WIlfLin/S1-mini-Chinese"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id, dtype=torch.bfloat16, device_map="auto"
+).eval()
+
+messages = [
+    {"role": "system", "content": (
+        "You are a text normalizer for speech-to-text transcripts. The input begins "
+        "with a control line specifying the styling, structure, and context settings; "
+        "clean the transcript to match those settings and output only the cleaned text."
+    )},
+    {"role": "user", "content": (
+        "[Styling: semi-formal] [Structure: prose] [Context: general]\n"
+        "嗯，我我今天下午去开会。"
+    )},
+]
+text = tokenizer.apply_chat_template(
+    messages, tokenize=False, add_generation_prompt=True, enable_thinking=False
+)
+inputs = tokenizer(text, return_tensors="pt").to(model.device)
+with torch.inference_mode():
+    result = model.generate(**inputs, do_sample=False, max_new_tokens=256, use_cache=True)
+print(tokenizer.decode(result[0, inputs.input_ids.shape[1]:], skip_special_tokens=True).strip())
+```
+
+明确列表可把控制行中的 `Structure: prose` 改为 `Structure: lists`。只有口水词时允许输出空字符串；不得把空输出统一替换成原文。生产服务应检查 EOS/截断，保留原始转写用于诊断，并在模型不可用时回退。
+
+## 限制
+
+- 仍会漏删重复、误删语气，或选错自我纠正的最终分支。
+- 不能保证人名、数字、否定和事实始终正确保留；保护规则也不是语义等价证明。
+- 不是通用同音错字恢复模型，也不保证复杂中英混合口述的效果。
+- 合成和回放数据不等于足量自然中英混合人工标注。
+- 公开文本测试和固定录音回放不能代替真实麦克风与实际用户验收。
+
+## 许可证与来源署名
+
+本模型是 **S1-mini** by **Superwhisper** 的修改版本，底层架构来源为 Qwen3-0.6B。保留随仓库提供的 [`LICENSE`](LICENSE) 和 [`NOTICE`](NOTICE)。原许可证包含继续使用原模型名称及作者署名的附加条款；`S1-mini-Chinese` 是本微调版本的名称，不替代原始署名。
+
+训练来源分别声明 CS2W 为 CC-BY-SA-4.0、Disfl-QA 为 CC-BY-4.0；单独标注的自制合成内容为 CC0-1.0。具体来源与版本见 `data-provenance.json`。本仓库不重新发布训练数据，不把这些数据的许可证改称为纯 Apache-2.0。
+
+权重 SHA256：`fc30f55939e07b8c73c1041f8a7a772e761ad70b448f5cf5b5cf5e38579351e4`。

chat_template.jinja

@@ -0,0 +1,89 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].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" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|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 %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- 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' }}
+    {%- endif %}
+{%- endif %}

config.json

@@ -0,0 +1,63 @@
+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
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+}

data-provenance.json

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+{
+  "CS2W": {
+    "source": "https://github.com/guozishan/CS2W",
+    "revision": "be6e0519b433cfa9d8388b23308f1380716254fd",
+    "license_declared": "CC-BY-SA-4.0"
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+    "revision": "1f0c16171c77b3d3408be92c485f11b8998a9189",
+    "license_declared": "CC-BY-4.0 for dataset"
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+    "evaluation_policy": "Official test excluded from training and development selection; acceptance set used for development, not independent final proof",
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+      "Synthetic mixed/noise templates are not natural mixed-language gold",
+      "Target-to-target identities require semantic quality review",
+      "Deletion-only source filter does not itself guarantee semantic preservation",
+      "Disfl-QA 22-character ID grouping is conservative, not a confirmed source paragraph mapping"
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+}

evaluation-summary.json

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generation_config.json

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tokenizer.json

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tokenizer_config.json

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training-provenance.json

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