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@@ -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

.hydra/config.yaml

@@ -0,0 +1,269 @@
+dataset:
+  type: ambrosia
+  dir: /data/datasets_original/data/
+  use_modified_db: false
+  splits:
+    train: train
+    test: test
+    validation: validation
+  instruction_format_settings:
+    use_ambig_instruction: true
+    use_ambig_instruction_simple: false
+    use_disambiguation: false
+  processing_options:
+    all_correct_sql: true
+    format_sql: true
+    data_filter: both
+    balance_ambiguous_questions: false
+    balance_strategy: downsample
+    balance_seed: 42
+    grouping_mode: unambig_1_ambig_3_cycle
+    grouping_seed: 42
+    grouping_repeats: 1
+  paths:
+    processed: /data/datasets_csc_sql_format
+  output:
+    directory: /saved-models/logs/
+    filename: unified_dataset
+    save_json: true
+model:
+  name_or_path: Qwen/Qwen3-4B-Instruct-2507
+  revision: main
+  torch_dtype: bfloat16
+  attn_implementation: flash_attention_2
+  max_model_len: 8192
+  max_train_prompt_len: 8192
+  max_completion_length: 1024
+  peft:
+    enabled: false
+    lora_r: 64
+    lora_alpha: 16
+    lora_dropout: 0.1
+    target_modules:
+    - q_proj
+    - v_proj
+    - k_proj
+    - o_proj
+    - gate_proj
+    - up_proj
+    - down_proj
+  tokenizer:
+    trust_remote_code: true
+    padding_side: right
+    truncation_side: left
+mode:
+  type: grpo_training
+  seed: 42
+  learning_rate: 5.0e-07
+  num_train_epochs: 5
+  max_steps: -1
+  per_device_train_batch_size: 16
+  per_device_eval_batch_size: 16
+  gradient_accumulation_steps: 1
+  eval_accumulation_steps: 1
+  warmup_ratio: 0.03
+  weight_decay: 0.0
+  loss_type: dapo
+  mask_truncated_completions: true
+  optim: adamw_torch_fused
+  lr_scheduler_type: linear
+  max_grad_norm: 1.0
+  dataloader_pin_memory: false
+  bf16: true
+  gradient_checkpointing: true
+  gradient_checkpointing_kwargs:
+    use_reentrant: false
+  output_dir: /saved-models/csc_sql/models/cscsql_ambrosia/grpo_training_recall_prec_mixed_e2e_v3_grouping_${now:%Y%m%d_%H%M%S}
+  eval_strategy: steps
+  save_strategy: steps
+  save_steps: 400
+  save_total_limit: 3
+  save_only_model: true
+  evaluation_strategy: steps
+  eval_steps: 100
+  do_eval: true
+  load_best_model_at_end: false
+  overwrite_output_dir: true
+  logging:
+    level: info
+    report_to: wandb
+    wandb_project: cscsql_ambrosia_grpo
+    wandb_run_group: recall_prec_mixed_e2e_grouping
+    log_completions: true
+    logging_steps: 5
+    logging_strategy: steps
+    logging_first_step: true
+  save_checkpoints: true
+  resume_from_checkpoint: null
+  push_to_hub: false
+  template_name: ambig
+  max_train_prompt_len: 8192
+  max_prompt_length: 8192
+  max_completion_length: 2500
+  eval_dataset_sample_size: 100
+  reward_funcs:
+  - e2e_recall_precision_mixed_reward
+  reward_weights:
+  - 1.0
+  likelihood_reward_model_name: Qwen/Qwen3-4B-Instruct-2507
+  allfound_reward_model_name: Qwen/Qwen3-4B-Instruct-2507
+  interpretations_extraction_mode: hard
+  cosine_min_value_wrong: 0.0
+  cosine_max_value_wrong: -0.5
+  cosine_min_value_correct: 0.5
+  cosine_max_value_correct: 1.0
+  cosine_max_len: 1000
+  repetition_n_grams: 3
+  repetition_max_penalty: -1.0
+  code_language: python
+  num_generations: 16
+  num_completions_to_print: 0
+  log_completions: true
+  use_vllm: true
+  vllm_server_port: 14000
+  use_vllm_server_reward: false
+  vllm_server_url_reward: null
+  use_liger_kernel: true
+  torch_compile: false
+  use_liger_loss: false
+  use_interpretations: true
+  max_interpretations: 5
+  check_answer_structure: true
+  min_reasoning: 100
+hardware:
+  type: single_gpu
+  gpu:
+    device: cuda:0
+    memory_utilization: 0.95
+    tensor_parallel_size: 1
+    max_lora_rank: 64
+  vllm:
+    enabled: false
+    gpu_memory_utilization: 0.9
+    max_model_len: 8192
+    swap_space: 42
+    enforce_eager: true
+    disable_custom_all_reduce: true
+    server_port: 14000
+  accelerate:
+    mixed_precision: bf16
+    gradient_checkpointing: true
+    gradient_checkpointing_kwargs:
+      use_reentrant: false
+system_prompt:
+  content: 'You are a helpful AI Assistant that follows the user''s instructions and
+    provides an accurate answer.
+
+    '
+  description: Default concise system prompt for general assistance
+user_prompt:
+  template: 'You receive a context and a question. First analyze the question to identify
+    different possible interpretations, then provide the corresponding answer for
+    each interpretation.
+
+
+    If the question is unambiguous, provide a single clear interpretation and answer.
+    If the question contains ambiguities, underspecifications, or could be understood
+    in multiple ways, provide multiple plausible interpretations (maximum of 5) and
+    corresponding answers.
+
+
+    An interpretation is a self-contained, precise reformulation of the question that
+    clarifies scope, entities, and intent so that the question could be answered unambiguously.
+    Different interpretations should lead to meaningfully different answers.
+
+
+    Context:
+
+    SQLite database schema:
+
+    {schema}
+
+    This schema describes the database''s structure, including tables, columns, primary
+    keys, foreign keys, and any relevant relationships or constraints.
+
+
+    Question to interpret and answer:
+
+    {question}
+
+
+    General Instructions:
+
+    - Think through the question step-by-step
+
+    - Consider different ways the question could be understood
+
+    - Look for potential ambiguities in terminology, scope, or intent
+
+    - Consider how the provided context might influence interpretation
+
+
+    SQL Generation Instructions:
+
+    - Make sure you only output the information that is asked in the question. If
+    the question asks for a specific column, make sure to only include that column
+    in the SELECT clause, nothing more
+
+    - The generated query(ies) should return all of the information asked in the question
+    without any missing or extra information
+
+    - Use a fenced code block with "sql" annotation, e.g. ```sql ... ```
+
+
+    Output Format:
+
+    Provide your analysis and reasoning, then conclude with interpretations and answers.
+    Follow the format below:
+
+
+    ...analysis and reasoning...
+
+    <answer>
+
+    **Interpretation 1:** [State first interpretation]
+
+    [Answer for interpretation 1]
+
+
+    [Continue for all interpretations (up to 5) if the question is ambiguous...]
+
+    </answer>
+
+    '
+  variables:
+  - question
+  - schema
+  description: text2sql_ambig_experimental_v3
+  parse_function: extract_interpretations_and_sqls_from_xml_answer
+second_stage_prompt:
+  template: 'Task Overview:
+
+    Below is a SQLite database schema and a question. Your task is to generate a valid
+    SQL query to answer the question.
+
+
+    Database Schema:
+
+    {schema}
+
+
+    Question:
+
+    {interpretation}
+
+
+    Instructions:
+
+    - Only include the columns explicitly requested in the SELECT clause.
+
+    - Use a fenced code block with "sql" annotation, e.g. ```sql ... ```
+
+    '
+  description: intent_clarification
+  variables:
+  - schema
+  - interpretation
+  parse_function: extract_sql_from_code_blocks
+experiment:
+  name: ambrosia_grpo_recall_prec_mixed_e2e_v3_grouping

.hydra/hydra.yaml

@@ -0,0 +1,161 @@
+hydra:
+  run:
+    dir: ${mode.output_dir}
+  sweep:
+    dir: ${mode.output_dir}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task: []
+  job:
+    name: nl2sql_grpo
+    chdir: null
+    override_dirname: ''
+    id: ???
+    num: ???
+    config_name: ambrosia_grpo_recall_prec_mixed_e2e_v3_grouping
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /workspace/act/csc_sql
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /workspace/act/csc_sql/config
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /saved-models/csc_sql/models/cscsql_ambrosia/grpo_training_recall_prec_mixed_e2e_v3_grouping_20250926_185345
+    choices:
+      second_stage_prompt: text2sql_plain
+      user_prompt: text2sql_ambig_experimental_v3
+      system_prompt: default_concise
+      hardware: single_gpu
+      mode: grpo_training
+      model: qwen3-4b-instruct-2507
+      dataset: ambrosia_both
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

.hydra/overrides.yaml

@@ -0,0 +1 @@
+[]

README.md

@@ -0,0 +1,69 @@
+---
+base_model: Qwen/Qwen3-4B-Instruct-2507
+datasets: ambrosia
+library_name: transformers
+tags:
+- generated_from_trainer
+- trl
+- open-r1
+- grpo
+licence: license
+---
+
+# Model Card for None
+
+This model is a fine-tuned version of [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) on the [ambrosia](https://huggingface.co/datasets/ambrosia) dataset.
+It has been trained using [TRL](https://github.com/huggingface/trl).
+
+## Quick start
+
+```python
+from transformers import pipeline
+
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="None", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/saparina/cscsql_ambrosia_grpo/runs/mbpj7wgz) 
+
+
+This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
+
+### Framework versions
+
+- TRL: 0.23.0
+- Transformers: 4.56.2
+- Pytorch: 2.8.0
+- Datasets: 4.1.1
+- Tokenizers: 0.22.1
+
+## Citations
+
+Cite GRPO as:
+
+```bibtex
+@article{shao2024deepseekmath,
+    title        = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
+    author       = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
+    year         = 2024,
+    eprint       = {arXiv:2402.03300},
+}
+
+```
+
+Cite TRL as:
+    
+```bibtex
+@misc{vonwerra2022trl,
+	title        = {{TRL: Transformer Reinforcement Learning}},
+	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
+```

added_tokens.json

@@ -0,0 +1,28 @@
+{
+  "</think>": 151668,
+  "</tool_call>": 151658,
+  "</tool_response>": 151666,
+  "<think>": 151667,
+  "<tool_call>": 151657,
+  "<tool_response>": 151665,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

all_results.json

@@ -0,0 +1,13 @@
+{
+    "eval_loss": 0.0013490546261891723,
+    "eval_runtime": 451.086,
+    "eval_samples": 100,
+    "eval_samples_per_second": 0.222,
+    "eval_steps_per_second": 0.004,
+    "total_flos": 0.0,
+    "train_loss": 0.0002628941724753198,
+    "train_runtime": 110827.1867,
+    "train_samples": 3406,
+    "train_samples_per_second": 0.154,
+    "train_steps_per_second": 0.038
+}

chat_template.jinja

@@ -0,0 +1,61 @@
+{%- 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 %}
+{%- 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" %}
+        {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- 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' }}
+{%- endif %}

config.json

@@ -0,0 +1,68 @@
+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 2560,
+  "initializer_range": 0.02,
+  "intermediate_size": 9728,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 262144,
+  "max_window_layers": 36,
+  "model_type": "qwen3",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 8,
+  "pad_token_id": 151643,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 5000000,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "4.56.2",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

eval_results.json

@@ -0,0 +1,7 @@
+{
+    "eval_loss": 0.0013490546261891723,
+    "eval_runtime": 451.086,
+    "eval_samples": 100,
+    "eval_samples_per_second": 0.222,
+    "eval_steps_per_second": 0.004
+}

generation_config.json

@@ -0,0 +1,12 @@
+{
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "4.56.2"
+}

model-00001-of-00002.safetensors

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+size 4967215360

model-00002-of-00002.safetensors

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train_results.json

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+    "train_steps_per_second": 0.038
+}

training_args.bin

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