Training in progress, step 300

.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

.hydra/config.yaml

@@ -0,0 +1,83 @@
+mode: train
+experiment:
+  dataset_size: 6000
+  dataset_seed: 1234
+  test_size: 0.1
+  hf_token: ${oc.env:HF_TOKEN,null}
+output:
+  root_path: ${oc.env:ROOT_PATH}
+  run_name: ${model.trim}_${task.name}_${algorithm.name}_${algorithm.training.curriculum_schedule}_${algorithm.training.scheduler_params.mu_exp}_${algorithm.training.scheduler_params.sigma}_${algorithm.training.scheduler_params.min_prob}_${algorithm.training.max_steps}
+lora:
+  r: 32
+  alpha: 64
+  dropout: 0.1
+  target_modules:
+  - q_proj
+  - v_proj
+  task_type: CAUSAL_LM
+occupy_gpu_memory: false
+occupy_gpu_memory_gb: 50
+gpu_device: cuda:0
+model:
+  family: meta-llama
+  trim: Llama-3.2-3B-Instruct
+  name: ${model.family}/${model.trim}
+  trust_remote_code: true
+  torch_dtype: bfloat16
+  attn_implementation: flash_attention_2
+task:
+  name: blocksworld1246
+  data_files:
+  - data/blocksworld/train_set-1-complete-correct.json
+  - data/blocksworld/train_set-2-complete-correct.json
+  - data/blocksworld/train_set-4-complete-correct.json
+  - data/blocksworld/train_set-6-complete-correct.json
+  icl_examples_file: data/blocksworld/train_set-2-more_with_trace.json
+  use_icl_examples: false
+  training:
+    max_prompt_length: 1600
+    max_completion_length: 512
+  inference:
+    checkpoint: 1200
+    steps: 4
+    temperature: 0.0
+    sc_num: 1
+    use_icl: false
+    icl_num: 2
+    prompt_path: prompts/blocksworld/pool_prompt_v1.json
+    data_path: data/blocksworld/split_v1/split_v1_step_{steps}_data.json
+    config_file: data/blocksworld/bw_config.yaml
+    domain_file: data/blocksworld/generated_domain.pddl
+    pass_at_k: 1
+    num_shot: 4
+    resume: 0
+    max_new_tokens: 512
+    max_batch_size: 64
+algorithm:
+  name: sgrpo
+  training:
+    learning_rate: 1.0e-06
+    lr_scheduler_type: cosine
+    logging_steps: 10
+    max_steps: 300
+    curriculum: true
+    curriculum_schedule: classic
+    scheduler_params:
+      mu_exp: 0.5
+      sigma: 0.5
+      min_prob: true
+    per_device_train_batch_size: 2
+    gradient_accumulation_steps: 4
+    gradient_checkpointing: true
+    bf16: true
+    num_generations: 8
+    beta: 0.001
+    use_vllm: true
+    vllm_gpu_memory_utilization: 0.5
+    report_to:
+    - wandb
+    push_to_hub: true
+    save_strategy: steps
+    save_steps: ${algorithm.training.max_steps}
+    eval_strategy: steps
+    tf32: true

.hydra/hydra.yaml

@@ -0,0 +1,166 @@
+hydra:
+  run:
+    dir: ${output.root_path}/outputs/${mode2name:${mode},${output.run_name},${model.trim}}
+  sweep:
+    dir: ${output.root_path}/multirun/${now:%Y%m%d}
+    subdir: ${hydra.job.override_dirname}
+  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:
+    - mode=train
+    - task=blocksworld1246
+    - algorithm=sgrpo
+    - model=llama3
+    - algorithm.training.per_device_train_batch_size=2
+    - algorithm.training.curriculum_schedule=classic
+    - algorithm.training.scheduler_params.mu_exp=0.5
+    - algorithm.training.scheduler_params.sigma=0.5
+    - algorithm.training.vllm_gpu_memory_utilization=0.5
+  job:
+    name: main
+    chdir: false
+    override_dirname: algorithm.training.curriculum_schedule=classic,algorithm.training.per_device_train_batch_size=2,algorithm.training.scheduler_params.mu_exp=0.5,algorithm.training.scheduler_params.sigma=0.5,algorithm.training.vllm_gpu_memory_utilization=0.5,algorithm=sgrpo,mode=train,model=llama3,task=blocksworld1246
+    id: ???
+    num: ???
+    config_name: config
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/data/shared/shparashar/Sys2Bench
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/data/shared/shparashar/Sys2Bench/methods/RL/conf
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/data/shared/shparashar/Sys2Bench/outputs/Llama-3.2-3B-Instruct_blocksworld1246_sgrpo_classic_0.5_0.5_True_300
+    choices:
+      algorithm: sgrpo
+      task: blocksworld1246
+      model: llama3
+      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 +1,9 @@
+- mode=train
+- task=blocksworld1246
+- algorithm=sgrpo
+- model=llama3
+- algorithm.training.per_device_train_batch_size=2
+- algorithm.training.curriculum_schedule=classic
+- algorithm.training.scheduler_params.mu_exp=0.5
+- algorithm.training.scheduler_params.sigma=0.5
+- algorithm.training.vllm_gpu_memory_utilization=0.5

config.json

@@ -0,0 +1,40 @@
+{
+  "_name_or_path": "meta-llama/Llama-3.2-3B-Instruct",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 3072,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 24,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 32.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.48.1",
+  "use_cache": true,
+  "vocab_size": 128256
+}

config_dump.yaml

@@ -0,0 +1,83 @@
+mode: train
+experiment:
+  dataset_size: 6000
+  dataset_seed: 1234
+  test_size: 0.1
+  hf_token: ${oc.env:HF_TOKEN,null}
+output:
+  root_path: ${oc.env:ROOT_PATH}
+  run_name: ${model.trim}_${task.name}_${algorithm.name}_${algorithm.training.curriculum_schedule}_${algorithm.training.scheduler_params.mu_exp}_${algorithm.training.scheduler_params.sigma}_${algorithm.training.scheduler_params.min_prob}_${algorithm.training.max_steps}
+lora:
+  r: 32
+  alpha: 64
+  dropout: 0.1
+  target_modules:
+  - q_proj
+  - v_proj
+  task_type: CAUSAL_LM
+occupy_gpu_memory: false
+occupy_gpu_memory_gb: 50
+gpu_device: cuda:0
+model:
+  family: meta-llama
+  trim: Llama-3.2-3B-Instruct
+  name: ${model.family}/${model.trim}
+  trust_remote_code: true
+  torch_dtype: bfloat16
+  attn_implementation: flash_attention_2
+task:
+  name: blocksworld1246
+  data_files:
+  - data/blocksworld/train_set-1-complete-correct.json
+  - data/blocksworld/train_set-2-complete-correct.json
+  - data/blocksworld/train_set-4-complete-correct.json
+  - data/blocksworld/train_set-6-complete-correct.json
+  icl_examples_file: data/blocksworld/train_set-2-more_with_trace.json
+  use_icl_examples: false
+  training:
+    max_prompt_length: 1600
+    max_completion_length: 512
+  inference:
+    checkpoint: 1200
+    steps: 4
+    temperature: 0.0
+    sc_num: 1
+    use_icl: false
+    icl_num: 2
+    prompt_path: prompts/blocksworld/pool_prompt_v1.json
+    data_path: data/blocksworld/split_v1/split_v1_step_{steps}_data.json
+    config_file: data/blocksworld/bw_config.yaml
+    domain_file: data/blocksworld/generated_domain.pddl
+    pass_at_k: 1
+    num_shot: 4
+    resume: 0
+    max_new_tokens: 512
+    max_batch_size: 64
+algorithm:
+  name: sgrpo
+  training:
+    learning_rate: 1.0e-06
+    lr_scheduler_type: cosine
+    logging_steps: 10
+    max_steps: 300
+    curriculum: true
+    curriculum_schedule: classic
+    scheduler_params:
+      mu_exp: 0.5
+      sigma: 0.5
+      min_prob: true
+    per_device_train_batch_size: 2
+    gradient_accumulation_steps: 4
+    gradient_checkpointing: true
+    bf16: true
+    num_generations: 8
+    beta: 0.001
+    use_vllm: true
+    vllm_gpu_memory_utilization: 0.5
+    report_to:
+    - wandb
+    push_to_hub: true
+    save_strategy: steps
+    save_steps: ${algorithm.training.max_steps}
+    eval_strategy: steps
+    tf32: true

main.log

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+[2025-05-01 16:25:00,180][__main__][INFO] - Data Schedule: classic
+[2025-05-01 16:25:13,514][__main__][INFO] - Iteration 0: Batch indices: [1435, 7087, 5853, 2339, 3277, 762, 3736, 6939]: Task Difficulties: [0 0 0 0 0 0 0 0]
+[2025-05-01 16:25:13,517][__main__][INFO] - Iteration 1: Batch indices: [2216, 4555, 2580, 3145, 4925, 4470, 5684, 2531]: Task Difficulties: [0 0 0 0 0 0 0 0]
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128250": {
+      "content": "<|reserved_special_token_242|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128251": {
+      "content": "<|reserved_special_token_243|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128252": {
+      "content": "<|reserved_special_token_244|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128253": {
+      "content": "<|reserved_special_token_245|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128254": {
+      "content": "<|reserved_special_token_246|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128255": {
+      "content": "<|reserved_special_token_247|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|begin_of_text|>",
+  "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n    {%- if strftime_now is defined %}\n        {%- set date_string = strftime_now(\"%d %b %Y\") %}\n    {%- else %}\n        {%- set date_string = \"26 Jul 2024\" %}\n    {%- endif %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content']|trim %}\n    {%- set messages = messages[1:] %}\n{%- else %}\n    {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if tools is not none %}\n    {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n    {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n    {#- Extract the first user message so we can plug it in here #}\n    {%- if messages | length != 0 %}\n        {%- set first_user_message = messages[0]['content']|trim %}\n        {%- set messages = messages[1:] %}\n    {%- else %}\n        {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n    {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n    {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n    {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n    {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {%- if not message.tool_calls|length == 1 %}\n            {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n        {%- endif %}\n        {%- set tool_call = message.tool_calls[0].function %}\n        {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n        {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n        {{- '\"parameters\": ' }}\n        {{- tool_call.arguments | tojson }}\n        {{- \"}\" }}\n        {{- \"<|eot_id|>\" }}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n        {%- if message.content is mapping or message.content is iterable %}\n            {{- message.content | tojson }}\n        {%- else %}\n            {{- message.content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 131072,
+  "pad_token": "<|eot_id|>",
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}

training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3f5ade8e56da68e79cd103506cab45963e83da87ad42e3746432fd9b6bea8e9d
+size 6968