{ "output_dir": "/app/outputs/sft-qwen3/v3-20260317-133746", "overwrite_output_dir": false, "do_train": false, "do_eval": false, "do_predict": false, "eval_strategy": "epoch", "prediction_loss_only": false, "per_device_train_batch_size": 1, "per_device_eval_batch_size": 1, "per_gpu_train_batch_size": null, "per_gpu_eval_batch_size": null, "gradient_accumulation_steps": 8, "eval_accumulation_steps": null, "eval_delay": 0, "torch_empty_cache_steps": null, "learning_rate": 1e-05, "weight_decay": 0.1, "adam_beta1": 0.9, "adam_beta2": 0.95, "adam_epsilon": 1e-08, "max_grad_norm": 1.0, "num_train_epochs": 1.0, "max_steps": -1, "lr_scheduler_type": "cosine", "lr_scheduler_kwargs": null, "warmup_ratio": 0.05, "warmup_steps": 0, "log_level": "passive", "log_level_replica": "warning", "log_on_each_node": true, "logging_dir": "/app/outputs/sft-qwen3/v3-20260317-133746/runs", "logging_strategy": "steps", "logging_first_step": true, "logging_steps": 10, "logging_nan_inf_filter": true, "save_strategy": "epoch", "save_steps": 500, "save_total_limit": null, "save_safetensors": true, "save_on_each_node": false, "save_only_model": true, "restore_callback_states_from_checkpoint": false, "no_cuda": false, "use_cpu": false, "use_mps_device": false, "seed": 42, "data_seed": 42, "jit_mode_eval": false, "bf16": true, "fp16": false, "fp16_opt_level": "O1", "half_precision_backend": "auto", "bf16_full_eval": false, "fp16_full_eval": false, "tf32": null, "local_rank": 0, "ddp_backend": null, "tpu_num_cores": null, "tpu_metrics_debug": false, "debug": null, "dataloader_drop_last": false, "eval_steps": null, "dataloader_num_workers": 4, "dataloader_prefetch_factor": null, "past_index": -1, "run_name": "/app/outputs/sft-qwen3/v3-20260317-133746", "disable_tqdm": null, "remove_unused_columns": true, "label_names": null, "load_best_model_at_end": false, "metric_for_best_model": "loss", "greater_is_better": false, "ignore_data_skip": false, "fsdp": [], "fsdp_min_num_params": 0, "fsdp_config": null, "fsdp_transformer_layer_cls_to_wrap": null, "accelerator_config": { "dispatch_batches": false }, "parallelism_config": null, "deepspeed": { "fp16": { "enabled": "auto", "loss_scale": 0, "loss_scale_window": 1000, "initial_scale_power": 16, "hysteresis": 2, "min_loss_scale": 1 }, "bf16": { "enabled": "auto" }, "zero_optimization": { "stage": 3, "offload_optimizer": { "device": "none", "pin_memory": true }, "offload_param": { "device": "none", "pin_memory": true }, "overlap_comm": false, "contiguous_gradients": true, "sub_group_size": 1000000000.0, "reduce_bucket_size": "auto", "zero_quantized_weights": false, "zero_quantized_gradients": false, "stage3_prefetch_bucket_size": "auto", "stage3_param_persistence_threshold": "auto", "stage3_max_live_parameters": 1000000000.0, "stage3_max_reuse_distance": 1000000000.0, "stage3_gather_16bit_weights_on_model_save": true }, "gradient_accumulation_steps": "auto", "gradient_clipping": "auto", "steps_per_print": 2000, "train_batch_size": "auto", "train_micro_batch_size_per_gpu": "auto", "wall_clock_breakdown": false }, "label_smoothing_factor": 0.0, "optim": "adamw_torch_fused", "optim_args": null, "adafactor": false, "group_by_length": false, "length_column_name": "length", "report_to": [ "wandb" ], "project": "huggingface", "trackio_space_id": "trackio", "ddp_find_unused_parameters": null, "ddp_bucket_cap_mb": null, "ddp_broadcast_buffers": null, "dataloader_pin_memory": true, "dataloader_persistent_workers": false, "skip_memory_metrics": true, "use_legacy_prediction_loop": false, "push_to_hub": true, "resume_from_checkpoint": null, "hub_model_id": null, "hub_strategy": "every_save", "hub_token": null, "hub_private_repo": null, "hub_always_push": false, "hub_revision": null, "gradient_checkpointing": true, "gradient_checkpointing_kwargs": null, "include_inputs_for_metrics": false, "include_for_metrics": [], "eval_do_concat_batches": true, "fp16_backend": "auto", "push_to_hub_model_id": null, "push_to_hub_organization": null, "push_to_hub_token": null, "mp_parameters": "", "auto_find_batch_size": false, "full_determinism": false, "torchdynamo": null, "ray_scope": "last", "ddp_timeout": 18000000, "torch_compile": false, "torch_compile_backend": null, "torch_compile_mode": null, "include_tokens_per_second": false, "include_num_input_tokens_seen": false, "neftune_noise_alpha": null, "optim_target_modules": null, "batch_eval_metrics": false, "eval_on_start": false, "use_liger_kernel": false, "liger_kernel_config": null, "eval_use_gather_object": false, "average_tokens_across_devices": true, "sortish_sampler": false, "predict_with_generate": false, "generation_max_length": null, "generation_num_beams": null, "generation_config": null, "tuner_backend": "peft", "vit_gradient_checkpointing": null, "router_aux_loss_coef": 0.0, "enable_dft_loss": false, "enable_channel_loss": false, "check_model": true, "acc_strategy": "token", "train_dataloader_shuffle": true, "max_epochs": null, "aligner_lr": null, "vit_lr": null, "use_logits_to_keep": null, "ds3_gather_for_generation": true, "resume_only_model": false, "optimizer": null, "loss_type": null, "metric": null, "eval_use_evalscope": false, "eval_dataset": [], "eval_dataset_args": null, "eval_limit": null, "eval_generation_config": null, "extra_eval_args": null, "use_flash_ckpt": false, "use_ray": false, "ray_exp_name": null, "device_groups": null, "model": "Qwen/Qwen3-8B", "model_type": "qwen3", "model_revision": null, "task_type": "causal_lm", "torch_dtype": "bfloat16", "attn_impl": null, "new_special_tokens": [], "num_labels": null, "problem_type": null, "rope_scaling": null, "device_map": null, "max_memory": {}, "max_model_len": null, "local_repo_path": null, "init_strategy": null, "template": "qwen3", "system": "あなたはHTMLから、StudioDOM(デザイン情報が入ったjsonファイル)に変換するエキスパートです。\n\n# タスク\n与えられたHTMLソースコードを分析し、指定されたJSON形式に変換してください。\n\n# 入力\nHTMLソースコード: ウェブページの構造とスタイル情報\n\n# 出力\n以下の形式のStudioDOM(デザイン情報が入ったjsonファイル)\n\n# Studio DOM型定義\n\n## 基本型\n\n### DomBase\nすべてのDOM要素の基底インターフェース。\n```typescript\ninterface DomBase {\n tagName?: string; // HTMLタグ名\n name?: string; // 要素名\n id?: string; // HTML id属性\n renderIf?: RenderIfDto; // 条件付きレンダリング\n slot?: \"before\" | \"after\";\n}\n```\n\n### DomElement\nスタイルと属性を持つ要素の基底。\n```typescript\ninterface DomElement extends DomBase {\n style?: StudioDomStyle; // CSSスタイル定義\n attrs?: StudioAttrs; // HTML属性\n}\n```\n\n### DomLink\nリンク機能を持つ要素のミックスイン。\n```typescript\ntype DomLink = {\n link?: { newTab: boolean; path: string };\n action?: { type: \"link\" | \"modal\" | \"close\" | \"allowCookie\" | \"denyCookie\" | \"anchorLink\"; val?: string };\n}\n```\n\n## 要素型一覧\n\n### TextDom - テキスト要素\n```typescript\ninterface TextDom extends DomElement, DomLink {\n content: { type: \"text\"; data: string };\n classes?: string[];\n}\n```\n\n### ImgDom - 画像要素\n```typescript\ninterface ImgDom extends DomElement, DomLink {\n content: { type: \"img\"; src: string; alt?: string };\n}\n```\n\n### BoxDom - コンテナ要素\n```typescript\ntype BoxDom = DomElement & DomLink & {\n children: PublishedDom[]; // 子要素\n content?: StudioDomContent | { type: \"image\"; src: string };\n webComponents?: WebComponents;\n transition?: ModalTransitionStyle;\n}\n```\n\n### IconDom - アイコン要素\n```typescript\ninterface IconDom extends DomElement, DomLink {\n content: IconDomContent & { href?: string };\n}\ninterface IconDomContent {\n type: \"icon\" | \"icon-fa\" | \"icon-solid\" | \"icon-brands\";\n data: string; // アイコン名\n}\ninterface IconDomContentMaterialSymbol {\n type: \"icon-symbol\";\n data: string;\n fill: 0 | 1;\n weight: 100 | 200 | 300 | 400 | 500 | 600 | 700;\n}\n```\n\n### IframeDom - iframe要素\n```typescript\ninterface IframeDom extends DomElement {\n content: { type: \"iframe\" | \"sandbox\"; data: string };\n}\n```\n\n### InputDom - 入力フィールド\n```typescript\ninterface InputDom extends DomElement {\n content: { type: \"input\" | \"textarea\" };\n attrs: StudioAttrs & { placeholder?: string };\n}\n```\n\n### SelectDom - セレクトボックス\n```typescript\ninterface SelectDom extends DomElement {\n content: { type: \"select\"; options: { label: string; value: string }[] };\n attrs: StudioAttrs & { required: boolean; name: string };\n}\n```\n\n### ButtonDom - ボタン要素\n```typescript\ntype ButtonDom = DomElement & {\n content: { type: \"button\" };\n on?: { click?: string; blur?: string };\n children: PublishedDom[];\n}\n```\n\n### FormDom - フォーム要素\n```typescript\ninterface FormDom extends DomElement {\n content: { type: \"form\"; formSuccessPageId?: string };\n children: PublishedDom[];\n}\n```\n\n### VideoDom - 動画要素\n```typescript\ninterface VideoDom extends DomElement {\n content: {\n type: \"video\";\n src: string;\n video?: {\n autoplay?: boolean;\n loop?: boolean;\n controls?: boolean;\n muted?: boolean;\n poster?: string;\n playsinline?: boolean;\n };\n };\n}\n```\n\n### LottieDom - Lottieアニメーション\n```typescript\ninterface LottieDom extends DomElement {\n content: {\n type: \"lottie\";\n lottie?: {\n playType?: \"autoplay\" | \"hover\" | \"scroll\" | \"cursor\" | \"click\" | \"appear\";\n controls: boolean;\n loop?: boolean;\n speed?: number;\n src: string;\n };\n };\n}\n```\n\n### SectionDom - セクション要素\n```typescript\ninterface SectionDom extends BoxDom {\n type: \"section\";\n}\n```\n\n### RefDom - 参照要素（シンボル参照）\n```typescript\ninterface RefDom extends DomBase {\n type: \"ref\";\n refId: string; // 参照先のID\n state?: object;\n props?: Record;\n}\n```\n\n## 動的コンテンツ要素\n\n### ListDom - リスト要素\n配列データをループ表示。4種類のデータソースに対応。\n```typescript\n// 共通構造\ninterface ListDomBase extends DomElement, DomLink {\n type: \"list\";\n defs: [{ key: \"list\"; type: \"array\" | \"cmsRequest\"; uid: string }];\n children: [ListItemDom] | [ListItemDom, BoxDom]; // アイテムテンプレート + ローディング表示\n}\n// データソース種別\n// - StateListDom: state.list に直接データを持つ\n// - PropsListDom: props.list でデータバインディング\n// - RSSListDom: props.list が \"$rss.{id}.items\" 形式\n// - CmsListDom: defs[0].type が \"cmsRequest\"\n```\n\n### CarouselDom - カルーセル要素\nスライド表示コンポーネント。\n```typescript\ninterface CarouselDom extends DomElement {\n type: \"carousel\";\n state: {\n pageIndex: number;\n maxLength: number;\n playing: boolean;\n autoDuration: number;\n list: object[];\n };\n children: [CarouselTrackDom] | [CarouselTrackDom, CarouselControlDom];\n on: { touchstart: string; touchmove: string; touchend: string };\n}\n```\n\n### SwitchDom - タブ/スイッチ要素\n複数コンテンツの切り替え表示。\n```typescript\ninterface SwitchDom extends DomElement, DomLink {\n type: \"switch\";\n defs: [{ key: \"option\"; type: \"option\"; options: { key: string; label: string }[] }];\n state: { option: string }; // 選択中のオプションキー\n children: [SwitchTabsDom, ...SwitchContentDom[]];\n}\n```\n\n### ToggleDom - トグル/アコーディオン要素\n開閉可能なコンテンツ。\n```typescript\ninterface ToggleDom extends DomElement, DomLink {\n type: \"toggle\";\n state: { isClose: boolean };\n children: [ToggleLabelDom, ToggleContentDom];\n}\n```\n\n## 条件付きレンダリング (RenderIf)\n要素の表示条件を定義。\n```typescript\ntype RenderIfQuery =\n | { fieldPath: string } // フィールドの存在確認\n | { fieldPath: string; opStr: \"!\" } // 否定\n | { fieldPath: string; opStr: \"===\"; value: string } // 等価比較\n | { fieldPath: string; opStr: \"!==\"; value: string } // 不等価比較\n | { fieldPath: string; opStr: \"relativeToToday\"; value: { amount: number; unit: \"year\" | \"month\" | \"week\" | \"day\" } };\n```\n\n## PublishedDom 統合型\nすべてのDOM型のユニオン。\n```typescript\ntype PublishedDom =\n | IframeDom | TextDom | ImgDom | BoxDom | IconDom\n | InputDom | SelectDom | ButtonDom | FormDom\n | VideoDom | LottieDom | SectionDom | RefDom\n | ListDom | CarouselDom | SwitchDom | ToggleDom\n // ... その他の型\n```\n\n## 型判定ユーティリティ\n`$PublishedDom`オブジェクトで型判定可能。\n```typescript\n$PublishedDom.isTextDom(dom) // TextDomか判定\n$PublishedDom.isImgDom(dom) // ImgDomか判定\n$PublishedDom.isListDom(dom) // ListDomか判定\n$PublishedDom.hasChildren(dom) // 子要素を持つか判定\n$PublishedDom.hasStyle(dom) // スタイルを持つか判定\n```\n\n# Examples\n\n## Example 1\n\n### Input\n```html\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n\n\n\n\n\n\n\n\n```\n\n### Output\n```json\n{\n \"breakPoints\": [\n {\n \"maxWidth\": 540,\n \"name\": \"mobile\"\n },\n {\n \"maxWidth\": 840,\n \"name\": \"tablet\"\n },\n {\n \"maxWidth\": 1140,\n \"name\": \"small\"\n }\n ],\n \"classes\": {\n \"typography\": [\n {\n \"key\": \"63bf421e\",\n \"name\": \"本文\",\n \"style\": {\n \"@mini\": {\n \"fontSize\": \"0.7rem\"\n },\n \"@mobile\": {\n \"fontSize\": \"0.8rem\"\n },\n \"fontFamily\": \"var(--s-font-f98ee9ba)\",\n \"fontSize\": \"0.9rem\",\n \"fontWeight\": \"500\",\n \"in:hover\": {\n \"fontWeight\": \"700\"\n },\n \"letterSpacing\": \"0.05em\",\n \"lineHeight\": \"2\",\n \"writingMode\": \"horizontal-tb\"\n }\n },\n {\n \"key\": \"4caeee0d\",\n \"name\": \"小さい文字\",\n \"style\": {\n \"@mobile\": {\n \"fontSize\": \"0.75rem\",\n \"letterSpacing\": \"0.04em\"\n },\n \"@small\": {\n \"fontSize\": \"0.8rem\"\n },\n \"fontFamily\": \"var(--s-font-f98ee9ba)\",\n \"fontSize\": \"0.85rem\",\n \"fontWeight\": \"500\",\n \"letterSpacing\": \"0.05em\",\n \"lineHeight\": \"2\",\n \"writingMode\": \"horizontal-tb\"\n }\n },\n {\n \"key\": \"df801922\",\n \"name\": \"大きい文字\",\n \"style\": {\n \"@mini\": {\n \"fontSize\": \"1rem\"\n },\n \"@mobile\": {\n \"letterSpacing\": \"0.1em\"\n },\n \"@tablet\": {\n \"fontSize\": \"0.9rem\"\n },\n \"fontFamily\": \"var(--s-font-f98ee9ba)\",\n \"fontSize\": \"1.2rem\",\n \"fontStyle\": \"normal\",\n \"fontWeight\": \"700\",\n \"letterSpacing\": \"0.04em\",\n \"lineHeight\": \"1.6\",\n \"writingMode\": \"horizontal-tb\"\n }\n },\n {\n \"key\": \"3fa01083\",\n \"name\": \"カテゴリバッジ\",\n \"style\": {\n \"@mobile\": {\n \"fontSize\": \"0.7rem\",\n \"letterSpacing\": \"0.02em\"\n },\n \"fontFamily\": \"var(--s-font-f98ee9ba)\",\n \"fontSize\": \"0.8rem\",\n \"fontWeight\": \"600\",\n \"letterSpacing\": \"0.05em\",\n \"lineHeight\": \"1.8\",\n \"writingMode\": \"horizontal-tb\"\n }\n },\n {\n \"key\": \"b6a880dd\",\n \"name\": \"ボタン\",\n \"style\": {\n \"@mini\": {\n \"fontSize\": \"11px\"\n },\n \"@small\": {\n \"fontSize\": \"0.8rem\"\n },\n \"@tablet\": {\n \"fontSize\": \"0.85rem\"\n },\n \"fontFamily\": \"var(--s-font-f98ee9ba)\",\n \"fontSize\": \"0.9rem\",\n \"fontWeight\": \"500\",\n \"in:hover\": {\n \"fontWeight\": \"700\"\n },\n \"lineHeight\": \"1.4\"\n }\n },\n {\n \"key\": \"ee91d7a0\",\n \"name\": \"下層英字タイトル\",\n \"style\": {\n \"@mobile\": {\n \"fontSize\": \"1.8rem\"\n },\n \"fontFamily\": \"var(--s-font-5ebf6bcc)\",\n \"fontSize\": \"2.2rem\",\n \"fontWeight\": \"400\",\n \"lineHeight\": \"1.6\"\n }\n },\n {\n \"key\": \"1c827502\",\n \"name\": \"英字小見出し\",\n \"style\": {\n \"@mini\": {\n \"fontSize\": \"1rem\"\n },\n \"fontFamily\": \"var(--s-font-2ca5ec02)\",\n \"fontSize\": \"1.2rem\",\n \"fontStyle\": \"normal\",\n \"fontWeight\": \"600\",\n \"lineHeight\": \"1.8\",\n \"writingMode\": \"horizontal-tb\"\n }\n },\n {\n \"key\": \"c289a958\",\n \"name\": \"パンクズリスト\",\n \"style\": {\n \":hover\": {\n \"fontWeight\": \"700\"\n },\n \"@mobile\": {\n \"fontSize\": \"10px\",\n \"lineHeight\": \"2\"\n },\n \"@tablet\": {\n \"fontSize\": \"12px\"\n },\n \"fontFamily\": \"var(--s-font-f98ee9ba)\",\n \"fontSize\": \"0.7rem\",\n \"fontWeight\": \"600\",\n \"lineHeight\": \"1.4\"\n }\n }\n ]\n },\n \"colors\": [\n {\n \"color\": \"rgba(0,0,0,0.0)\",\n \"name\": \"transparent\"\n },\n {\n \"color\": \"#FFFFFF\",\n \"name\": \"white\"\n },\n {\n \"color\": \"#1e1e1e\",\n \"name\": \"color\"\n },\n {\n \"color\": \"#8a785a\",\n \"name\": \"color\"\n },\n {\n \"color\": \"#eae8e0ff\",\n \"name\": \"color\"\n },\n {\n \"color\": \"rgba(0, 0, 0, 0.05)\",\n \"name\": \"color\"\n }\n ],\n \"fonts\": [],\n \"info\": {\n \"baseWidth\": 1280,\n \"created_at\": 1518591100346,\n \"screen\": {\n \"baseWidth\": 1280,\n \"height\": 600,\n \"isAutoHeight\": false,\n \"width\": 1280,\n \"workingState\": false\n },\n \"type\": \"web\",\n \"updated_at\": 1518792996878,\n \"version\": \"4.1.9\"\n },\n \"pages\": [\n {\n \"cmsRequest\": {\n \"contentSlug\": \"{{$route.params.slug}}\",\n \"schemaKey\": \"Z926GhRm\"\n },\n \"heightExtension\": 300,\n \"id\": \"category/:slug\",\n \"name\": \"カテゴリーの記事\",\n \"statusBar\": \"\",\n \"type\": \"page\",\n \"view\": {\n \"children\": [\n {\n \"name\": \"\",\n \"refId\": \"b0eff1e9-d3f7-4572-a38b-30887d611063\",\n \"tagName\": \"\",\n \"type\": \"ref\"\n }\n ],\n \"content\": {\n \"type\": \"\"\n },\n \"name\": \"Base\",\n \"style\": {\n \"alignContent\": \"center\",\n \"alignItems\": \"center\",\n \"background\": \"var(--s-color-3d94ef4a)\",\n \"height\": \"100%\",\n \"padding\": \"0px 0px 0px 0px\",\n \"width\": \"100%\"\n }\n }\n }\n ],\n \"resources\": {\n \"cmsProjectId\": \"88062beec5d441069502\"\n },\n \"styleVars\": {\n \"color\": [\n {\n \"key\": \"3d94ef4a\",\n \"name\": \"白\",\n \"value\": \"#ffffffff\"\n }\n ],\n \"fontFamily\": []\n },\n \"symbols\": [\n {\n \"defaultSize\": {\n \"height\": 233.78125,\n \"width\": 1280\n },\n \"name\": \"フッター\",\n \"view\": {\n \"children\": [\n {\n \"children\": [\n {\n \"name\": \"\",\n \"refId\": \"ab196fa9-0972-4673-a9c0-b7d258ce4727\",\n \"tagName\": \"\",\n \"type\": \"ref\"\n },\n {\n \"children\": [\n {\n \"classes\": [\n \"4caeee0d\"\n ],\n \"content\": {\n \"data\": \"採用情報\",\n \"type\": \"text\"\n },\n \"link\": {\n \"newTab\": false,\n \"path\": \"/recruit\"\n },\n \"name\": \"採用情報\",\n \"style\": {\n \":hover\": {\n \"transform\": \"translate(3px, 3px)\"\n },\n \"@tablet\": {\n \"textAlign\": \"right\"\n },\n \"color\": \"var(--s-color-25a50242)\",\n \"flex\": \"none\",\n \"height\": \"auto\",\n \"textAlign\": \"left\",\n \"width\": \"auto\"\n },\n \"tagName\": \"\"\n },\n {\n \"classes\": [\n \"4caeee0d\"\n ],\n \"content\": {\n \"data\": \"会社概要\",\n \"type\": \"text\"\n },\n \"link\": {\n \"newTab\": false,\n \"path\": \"/company\"\n },\n \"name\": \"会社概要\",\n \"style\": {\n \":hover\": {\n \"transform\": \"translate(3px, 3px)\"\n },\n \"@tablet\": {\n \"textAlign\": \"right\"\n },\n \"color\": \"var(--s-color-25a50242)\",\n \"flex\": \"none\",\n \"height\": \"auto\",\n \"textAlign\": \"left\",\n \"width\": \"auto\"\n },\n \"tagName\": \"\"\n },\n {\n \"classes\": [\n \"4caeee0d\"\n ],\n \"content\": {\n \"data\": \"プライバシーポリシー\",\n \"type\": \"text\"\n },\n \"link\": {\n \"newTab\": false,\n \"path\": \"/privacy\"\n },\n \"name\": \"プライバシーポリシー\",\n \"style\": {\n \":hover\": {\n \"transform\": \"translate(3px, 3px)\"\n },\n \"@tablet\": {\n \"textAlign\": \"right\"\n },\n \"color\": \"var(--s-color-25a50242)\",\n \"flex\": \"none\",\n \"height\": \"auto\",\n \"textAlign\": \"left\",\n \"width\": \"auto\"\n },\n \"tagName\": \"\"\n }\n ],\n \"name\": \"メニュー\",\n \"style\": {\n \"@mobile\": {\n \"flexDirection\": \"column\",\n \"margin\": \"40px 0px 0px 0px\"\n },\n \"@tablet\": {\n \"margin\": \"50px 0px 0px 0px\"\n },\n \"alignContent\": \"flex-start\",\n \"alignItems\": \"flex-start\",\n \"flexDirection\": \"row\",\n \"flexWrap\": \"nowrap\",\n \"gap\": \"25px\",\n \"justifyContent\": \"flex-start\",\n \"margin\": \"0px 0px 0px 50px\",\n \"padding\": \"0px\"\n },\n \"tagName\": \"div\"\n }\n ],\n \"name\": \"ロゴ+メニュー\",\n \"style\": {\n \"@mobile\": {\n \"flexDirection\": \"column\"\n },\n \"@tablet\": {\n \"alignContent\": \"flex-start\",\n \"alignItems\": \"flex-start\",\n \"flex\": \"none\",\n \"flexDirection\": \"column\",\n \"flexWrap\": \"nowrap\",\n \"justifyContent\": \"space-between\",\n \"width\": \"100%\"\n },\n \"alignContent\": \"flex-start\",\n \"alignItems\": \"flex-start\",\n \"flex\": \"none\",\n \"flexDirection\": \"row\",\n \"flexWrap\": \"nowrap\",\n \"justifyContent\": \"space-between\",\n \"margin\": \"0px 0px 50px 0px\",\n \"padding\": \"0px\",\n \"width\": \"100%\"\n },\n \"tagName\": \"div\"\n },\n {\n \"content\": {\n \"data\": \"©2024 Book Essence\",\n \"type\": \"text\"\n },\n \"name\": \"コピーライト\",\n \"refId\": \"8a78fe0e-8333-4f02-8fc7-f797d8b95fe0\",\n \"style\": {\n \"@mobile\": {\n \"fontSize\": \"13px\"\n },\n \"@tablet\": {\n \"fontSize\": \"14px\"\n },\n \"bottom\": \"0px\",\n \"color\": \"#000000\",\n \"fontFamily\": \"var(--s-font-2ca5ec02)\",\n \"fontSize\": \"10px\",\n \"fontWeight\": \"500\",\n \"height\": \"auto\",\n \"left\": \"25px\",\n \"lineHeight\": \"1.7\",\n \"margin\": \"0 0 0 0\",\n \"position\": \"absolute\",\n \"right\": \"NaNpx\",\n \"textAlign\": \"center\",\n \"top\": \"NaNpx\",\n \"width\": \"auto\",\n \"writingMode\": \"vertical-rl\"\n },\n \"tagName\": \"\",\n \"type\": \"ref\"\n }\n ],\n \"name\": \"フッター\",\n \"style\": {\n \"@mobile\": {\n \"alignContent\": \"flex-end\",\n \"alignItems\": \"flex-end\",\n \"flexDirection\": \"column\",\n \"flexWrap\": \"nowrap\",\n \"justifyContent\": \"flex-start\",\n \"padding\": \"70px 40px 100px 40px\"\n },\n \"alignContent\": \"flex-start\",\n \"alignItems\": \"flex-start\",\n \"background\": \"var(--s-color-b8b1cba5)\",\n \"flex\": \"none\",\n \"flexDirection\": \"column\",\n \"flexWrap\": \"nowrap\",\n \"height\": \"auto\",\n \"justifyContent\": \"space-between\",\n \"margin\": \"0px 0px 0px 0px\",\n \"padding\": \"100px 40px 100px 40px\",\n \"width\": \"100%\",\n \"zIndex\": \"0\"\n },\n \"tagName\": \"footer\",\n \"type\": \"component\"\n }\n }\n ]\n}\n```\n\n## Example 2\n\n### Input\n```html\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n\n\n\n\n\n\n\n\n```\n\n### Output\n```json\n{\n \"breakPoints\": [\n {\n \"maxWidth\": 690,\n \"name\": \"mobile\"\n },\n {\n \"maxWidth\": 840,\n \"name\": \"tablet\"\n },\n {\n \"maxWidth\": 1140,\n \"name\": \"small\"\n },\n {\n \"maxWidth\": 360,\n \"name\": \"mini\"\n }\n ],\n \"colors\": [\n {\n \"color\": \"rgba(0,0,0,0.0)\",\n \"name\": \"transparent\"\n },\n {\n \"color\": \"#FFFFFF\",\n \"name\": \"white\"\n },\n {\n \"color\": \"#483628\",\n \"name\": \"color\"\n },\n {\n \"color\": \"#ee6801\",\n \"name\": \"color\"\n }\n ],\n \"fonts\": [],\n \"info\": {\n \"baseWidth\": 1920,\n \"created_at\": 1518591100346,\n \"screen\": {\n \"baseWidth\": 1280,\n \"height\": 600,\n \"isAutoHeight\": false,\n \"width\": 1280,\n \"workingState\": false\n },\n \"type\": \"web\",\n \"updated_at\": 1518792996878,\n \"version\": \"4.1.3\"\n },\n \"pages\": [\n {\n \"head\": {\n \"meta\": {\n \"robots\": \"noindex\"\n },\n \"title\": \"\"\n },\n \"heightExtension\": 0,\n \"id\": \"404\",\n \"name\": \"404 Not Found\",\n \"statusBar\": \"\",\n \"type\": \"page\",\n \"view\": {\n \"children\": [\n {\n \"name\": \"Menu\",\n \"refId\": \"d1f7770a-071c-442c-a07d-cdd9f49bd76b\",\n \"style\": {\n \"@mobile\": {\n \"flex\": \"none\"\n },\n \"@tablet\": {\n \"height\": \"auto\",\n \"padding\": \"0px 0px\"\n },\n \"alignContent\": \"center\",\n \"alignItems\": \"center\",\n \"background\": \"rgba(0,0,0,0.0)\",\n \"borderBottom\": \"0px solid rgba(255, 255, 255, 0.3)\",\n \"borderLeft\": \"0px solid rgba(255, 255, 255, 0.3)\",\n \"borderRight\": \"0px solid rgba(255, 255, 255, 0.3)\",\n \"borderTop\": \"0px solid rgba(255, 255, 255, 0.3)\",\n \"flex\": \"none\",\n \"flexDirection\": \"column\",\n \"flexWrap\": \"nowrap\",\n \"height\": \"auto\",\n \"justifyContent\": \"space-between\",\n \"margin\": \"0px 0px 0px 0px\",\n \"padding\": \"0px 48px\",\n \"width\": \"auto\"\n },\n \"tagName\": \"\",\n \"type\": \"ref\"\n }\n ],\n \"content\": {\n \"name\": \"\",\n \"type\": \"\"\n },\n \"name\": \"Base\",\n \"style\": {\n \"@mobile\": {\n \"padding\": \"56px 0px 0px 0px\"\n },\n \"background\": \"var(--s-color-1bbe02c8)\",\n \"borderRadius\": \"0\",\n \"boxShadow\": \"\",\n \"height\": \"100%\",\n \"margin\": \"0 0 0 0\",\n \"opacity\": \"1\",\n \"padding\": \"0 0 0 0\",\n \"width\": \"100%\"\n }\n }\n }\n ],\n \"resources\": {\n \"cmsProjectId\": \"3mPxrUtdtLXTjo0KwrWX\"\n },\n \"styleVars\": {\n \"color\": [],\n \"fontFamily\": []\n },\n \"symbols\": []\n}\n```\n", "max_length": 32768, "truncation_strategy": "delete", "max_pixels": null, "agent_template": null, "norm_bbox": null, "use_chat_template": true, "padding_side": "right", "padding_free": false, "loss_scale": "default", "sequence_parallel_size": 1, "template_backend": "swift", "response_prefix": null, "enable_thinking": null, "add_non_thinking_prefix": true, "dataset": [ "/app/datasets/train.jsonl" ], "val_dataset": [ "/app/datasets/val.jsonl" ], "cached_dataset": [], "cached_val_dataset": [], "split_dataset_ratio": 0.0, "dataset_num_proc": 1, "load_from_cache_file": true, "dataset_shuffle": true, "val_dataset_shuffle": false, "streaming": false, "interleave_prob": null, "stopping_strategy": "first_exhausted", "shuffle_buffer_size": 1000, "download_mode": "reuse_dataset_if_exists", "columns": {}, "strict": false, "model_name": null, "model_author": null, "custom_dataset_info": [], "quant_method": null, "quant_bits": null, "hqq_axis": null, "bnb_4bit_compute_dtype": "bfloat16", "bnb_4bit_quant_type": "nf4", "bnb_4bit_use_double_quant": true, "bnb_4bit_quant_storage": null, "max_new_tokens": 64, "temperature": 0.0, "top_k": null, "top_p": null, "repetition_penalty": null, "num_beams": 1, "stream": false, "stop_words": [], "logprobs": false, "top_logprobs": null, "structured_outputs_regex": null, "ckpt_dir": null, "lora_modules": [], "train_type": "lora", "adapters": [], "external_plugins": [], "model_kwargs": {}, "load_args": false, "load_data_args": false, "packing": false, "packing_length": null, "packing_num_proc": 1, "lazy_tokenize": false, "custom_register_path": [], "use_hf": true, "ignore_args_error": false, "use_swift_lora": false, "freeze_parameters": [], "freeze_parameters_regex": null, "freeze_parameters_ratio": 0.0, "trainable_parameters": [], "trainable_parameters_regex": null, "freeze_llm": false, "freeze_vit": true, "freeze_aligner": true, "target_modules": [ "all-linear" ], "target_regex": null, "target_parameters": null, "modules_to_save": [], "lora_rank": 8, "lora_alpha": 32, "lora_dropout": 0.05, "lora_bias": "none", "lora_dtype": null, "lorap_lr_ratio": null, "use_rslora": false, "use_dora": false, "lora_ga_batch_size": 2, "lora_ga_iters": 2, "lora_ga_max_length": 1024, "lora_ga_direction": "ArB2r", "lora_ga_scale": "stable", "lora_ga_stable_gamma": 16, "init_weights": true, "fourier_n_frequency": 2000, "fourier_scaling": 300.0, "boft_block_size": 4, "boft_block_num": 0, "boft_n_butterfly_factor": 1, "boft_dropout": 0.0, "vera_rank": 256, "vera_projection_prng_key": 0, "vera_dropout": 0.0, "vera_d_initial": 0.1, "adapter_act": "gelu", "adapter_length": 128, "use_galore": false, "galore_target_modules": null, "galore_rank": 128, "galore_update_proj_gap": 50, "galore_scale": 1.0, "galore_proj_type": "std", "galore_optim_per_parameter": false, "galore_with_embedding": false, "galore_quantization": false, "galore_proj_quant": false, "galore_proj_bits": 4, "galore_proj_group_size": 256, "galore_cos_threshold": 0.4, "galore_gamma_proj": 2, "galore_queue_size": 5, "adalora_target_r": 8, "adalora_init_r": 12, "adalora_tinit": 0, "adalora_tfinal": 0, "adalora_deltaT": 1, "adalora_beta1": 0.85, "adalora_beta2": 0.85, "adalora_orth_reg_weight": 0.5, "llamapro_num_new_blocks": 4, "llamapro_num_groups": null, "lisa_activated_layers": 0, "lisa_step_interval": 20, "reft_layer_key": null, "reft_layers": null, "reft_rank": 4, "reft_intervention_type": "LoreftIntervention", "reft_args": null, "swanlab_token": null, "swanlab_project": "ms-swift", "swanlab_workspace": null, "swanlab_exp_name": null, "swanlab_notification_method": null, "swanlab_webhook_url": null, "swanlab_secret": null, "swanlab_mode": "cloud", "add_version": true, "create_checkpoint_symlink": false, "zero_hpz_partition_size": null, "deepspeed_autotp_size": null, "early_stop_interval": null, "rank": 0, "global_world_size": 8, "local_world_size": 8, "model_suffix": "Qwen3-8B", "model_info": "ModelInfo(model_type='qwen3', model_dir='/root/.cache/huggingface/hub/models--Qwen--Qwen3-8B/snapshots/b968826d9c46dd6066d109eabc6255188de91218', torch_dtype=torch.bfloat16, max_model_len=40960, quant_method=None, quant_bits=None, rope_scaling=None, is_moe_model=False, is_multimodal=False, config=None, task_type='causal_lm', num_labels=None)", "model_meta": "ModelMeta(model_type='qwen3', model_groups=[ModelGroup(models=[Model(ms_model_id='Qwen/Qwen3-0.6B-Base', hf_model_id='Qwen/Qwen3-0.6B-Base', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-1.7B-Base', hf_model_id='Qwen/Qwen3-1.7B-Base', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-4B-Base', hf_model_id='Qwen/Qwen3-4B-Base', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-8B-Base', hf_model_id='Qwen/Qwen3-8B-Base', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-14B-Base', hf_model_id='Qwen/Qwen3-14B-Base', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-0.6B', hf_model_id='Qwen/Qwen3-0.6B', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-1.7B', hf_model_id='Qwen/Qwen3-1.7B', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-4B', hf_model_id='Qwen/Qwen3-4B', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-8B', hf_model_id='Qwen/Qwen3-8B', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-14B', hf_model_id='Qwen/Qwen3-14B', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-32B', hf_model_id='Qwen/Qwen3-32B', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-0.6B-FP8', hf_model_id='Qwen/Qwen3-0.6B-FP8', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-1.7B-FP8', hf_model_id='Qwen/Qwen3-1.7B-FP8', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-4B-FP8', hf_model_id='Qwen/Qwen3-4B-FP8', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-8B-FP8', hf_model_id='Qwen/Qwen3-8B-FP8', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-14B-FP8', hf_model_id='Qwen/Qwen3-14B-FP8', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-32B-FP8', hf_model_id='Qwen/Qwen3-32B-FP8', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-4B-AWQ', hf_model_id='Qwen/Qwen3-4B-AWQ', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-8B-AWQ', hf_model_id='Qwen/Qwen3-8B-AWQ', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-14B-AWQ', hf_model_id='Qwen/Qwen3-14B-AWQ', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-32B-AWQ', hf_model_id='Qwen/Qwen3-32B-AWQ', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='swift/Qwen3-32B-AWQ', hf_model_id=None, model_path=None, ms_revision=None, hf_revision=None)], ignore_patterns=None, requires=None, tags=[])], template='qwen3', get_function=, model_arch=ModelKeys(arch_name='llama', embedding='model.embed_tokens', module_list='model.layers', lm_head='lm_head', q_proj='model.layers.{}.self_attn.q_proj', k_proj='model.layers.{}.self_attn.k_proj', v_proj='model.layers.{}.self_attn.v_proj', o_proj='model.layers.{}.self_attn.o_proj', attention='model.layers.{}.self_attn', mlp='model.layers.{}.mlp', down_proj='model.layers.{}.mlp.down_proj', qkv_proj=None, qk_proj=None, qa_proj=None, qb_proj=None, kv_proj=None, kva_proj=None, kvb_proj=None), architectures=['Qwen3ForCausalLM'], additional_saved_files=[], torch_dtype=None, is_multimodal=False, is_reward=False, is_reranker=False, task_type=None, ignore_patterns=None, requires=['transformers>=4.51'], tags=[])", "model_dir": "/root/.cache/huggingface/hub/models--Qwen--Qwen3-8B/snapshots/b968826d9c46dd6066d109eabc6255188de91218", "_val_dataset_exists": [ "/app/datasets/val.jsonl" ], "hub": "", "evaluation_strategy": "epoch", "training_args": "Seq2SeqTrainingArguments(output_dir='/app/outputs/sft-qwen3/v3-20260317-133746', overwrite_output_dir=False, do_train=False, do_eval=True, do_predict=False, eval_strategy=, prediction_loss_only=False, per_device_train_batch_size=1, per_device_eval_batch_size=1, per_gpu_train_batch_size=None, per_gpu_eval_batch_size=None, gradient_accumulation_steps=8, eval_accumulation_steps=None, eval_delay=0, torch_empty_cache_steps=None, learning_rate=1e-05, weight_decay=0.1, adam_beta1=0.9, adam_beta2=0.95, adam_epsilon=1e-08, max_grad_norm=1.0, num_train_epochs=1.0, max_steps=-1, lr_scheduler_type=, lr_scheduler_kwargs=None, warmup_ratio=0.05, warmup_steps=0, log_level='passive', log_level_replica='warning', log_on_each_node=True, logging_dir='/app/outputs/sft-qwen3/v3-20260317-133746/runs', logging_strategy=, logging_first_step=True, logging_steps=10, logging_nan_inf_filter=True, save_strategy=, save_steps=500, save_total_limit=None, save_safetensors=True, save_on_each_node=False, save_only_model=True, restore_callback_states_from_checkpoint=False, no_cuda=False, use_cpu=False, use_mps_device=False, seed=42, data_seed=42, jit_mode_eval=False, bf16=True, fp16=False, fp16_opt_level='O1', half_precision_backend='auto', bf16_full_eval=False, fp16_full_eval=False, tf32=None, local_rank=0, ddp_backend=None, tpu_num_cores=None, tpu_metrics_debug=False, debug=[], dataloader_drop_last=False, eval_steps=None, dataloader_num_workers=4, dataloader_prefetch_factor=2, past_index=-1, run_name='/app/outputs/sft-qwen3/v3-20260317-133746', disable_tqdm=False, remove_unused_columns=False, label_names=None, load_best_model_at_end=False, metric_for_best_model='loss', greater_is_better=False, ignore_data_skip=False, fsdp=[], fsdp_min_num_params=0, fsdp_config={'min_num_params': 0, 'xla': False, 'xla_fsdp_v2': False, 'xla_fsdp_grad_ckpt': False}, fsdp_transformer_layer_cls_to_wrap=None, accelerator_config=AcceleratorConfig(split_batches=False, dispatch_batches=False, even_batches=True, use_seedable_sampler=True, non_blocking=False, gradient_accumulation_kwargs=None, use_configured_state=False), parallelism_config=None, deepspeed={'fp16': {'enabled': 'auto', 'loss_scale': 0, 'loss_scale_window': 1000, 'initial_scale_power': 16, 'hysteresis': 2, 'min_loss_scale': 1}, 'bf16': {'enabled': 'auto'}, 'zero_optimization': {'stage': 3, 'offload_optimizer': {'device': 'none', 'pin_memory': True}, 'offload_param': {'device': 'none', 'pin_memory': True}, 'overlap_comm': False, 'contiguous_gradients': True, 'sub_group_size': 1000000000.0, 'reduce_bucket_size': 'auto', 'zero_quantized_weights': False, 'zero_quantized_gradients': False, 'stage3_prefetch_bucket_size': 'auto', 'stage3_param_persistence_threshold': 'auto', 'stage3_max_live_parameters': 1000000000.0, 'stage3_max_reuse_distance': 1000000000.0, 'stage3_gather_16bit_weights_on_model_save': True}, 'gradient_accumulation_steps': 'auto', 'gradient_clipping': 'auto', 'steps_per_print': 2000, 'train_batch_size': 'auto', 'train_micro_batch_size_per_gpu': 'auto', 'wall_clock_breakdown': False}, label_smoothing_factor=0.0, optim=, optim_args=None, adafactor=False, group_by_length=False, length_column_name='length', report_to=['wandb'], project='huggingface', trackio_space_id='trackio', ddp_find_unused_parameters=None, ddp_bucket_cap_mb=None, ddp_broadcast_buffers=None, dataloader_pin_memory=True, dataloader_persistent_workers=False, skip_memory_metrics=True, use_legacy_prediction_loop=False, push_to_hub=True, resume_from_checkpoint=None, hub_model_id=None, hub_strategy=, hub_token=None, hub_private_repo=None, hub_always_push=False, hub_revision=None, gradient_checkpointing=True, gradient_checkpointing_kwargs=None, include_inputs_for_metrics=False, include_for_metrics=[], eval_do_concat_batches=True, fp16_backend='auto', push_to_hub_model_id=None, push_to_hub_organization=None, push_to_hub_token=None, mp_parameters='', auto_find_batch_size=False, full_determinism=False, torchdynamo=None, ray_scope='last', ddp_timeout=18000000, torch_compile=False, torch_compile_backend=None, torch_compile_mode=None, include_tokens_per_second=None, include_num_input_tokens_seen=None, neftune_noise_alpha=None, optim_target_modules=None, batch_eval_metrics=False, eval_on_start=False, use_liger_kernel=False, liger_kernel_config=None, eval_use_gather_object=False, average_tokens_across_devices=None, sortish_sampler=False, predict_with_generate=False, generation_max_length=None, generation_num_beams=None, generation_config=None, tuner_backend='peft', vit_gradient_checkpointing=True, router_aux_loss_coef=0.0, enable_dft_loss=False, enable_channel_loss=False, check_model=True, acc_strategy='token', train_dataloader_shuffle=True, max_epochs=None, aligner_lr=None, vit_lr=None, use_logits_to_keep=None, ds3_gather_for_generation=True, resume_only_model=False, optimizer=None, loss_type=None, metric=None, eval_use_evalscope=False, eval_dataset=[], eval_dataset_args=None, eval_limit=None, eval_generation_config=None, extra_eval_args=None, use_flash_ckpt=False, sft_alpha=0, chord_sft_dataset=[], chord_sft_per_device_train_batch_size=None, chord_enable_phi_function=False, chord_mu_warmup_steps=None, chord_mu_decay_steps=None, chord_mu_peak=None, chord_mu_valley=None, train_type='lora', local_repo_path=None, galore_config=None, task_type='causal_lm', problem_type=None)" }