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Model: SeongryongJung/Qwen3-4B-Physics-GRPO-TR
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---
license: apache-2.0
library_name: transformers
pipeline_tag: text-generation
tags:
- qwen3
- reinforcement-learning
- grpo
- text-generation
base_model: Qwen/Qwen3-4B
---
# Qwen3-4B-Physics-GRPO-TR
This repository contains the Qwen3-4B `Physics` `GRPO` batch-size-32 run. The repository name uses the project `GRPO-TR` naming convention, but the actual training method for this checkpoint is GRPO.
The repository root contains the best validation checkpoint, selected by validation `mean@16`. `checkpoints/last/` contains the final checkpoint. For this run, best and final are both `global_step_100`.
## Performance
| Dataset | Method | Base model | Train batch size | Best val mean@16 | Best checkpoint | Final val mean@16 | Final checkpoint |
|---|---|---|---:|---:|---:|---:|---:|
| Physics | GRPO | Qwen3-4B | 32 | 68.28% | 100 | 68.28% | 100 |
![Training and validation scores](results/training_score.png)
## Validation Mean@16
| step | val_mean16 | percent |
|---:|---:|---:|
| 10 | 0.594531250000 | 59.45% |
| 20 | 0.613281250000 | 61.33% |
| 30 | 0.631250000000 | 63.12% |
| 40 | 0.624218750000 | 62.42% |
| 50 | 0.645312500000 | 64.53% |
| 60 | 0.637500000000 | 63.75% |
| 70 | 0.638281250000 | 63.83% |
| 80 | 0.639062500000 | 63.91% |
| 90 | 0.662500000000 | 66.25% |
| 100 | 0.682812500000 | 68.28% |
## Detailed Training Hyperparameters
| Section | Parameter | Value | Source |
|---|---|---:|---|
| Run identity | `Base model` | `Qwen/Qwen3-4B` | queue/script override |
| Run identity | `Dataset` | `Physics / SciKnowEval physics` | run_qwen3_generalization.sh |
| Run identity | `Method` | `GRPO` | run_qwen3_generalization.sh |
| Run identity | `Config` | `baseline_grpo` | run_qwen3_generalization.sh |
| Run identity | `Experiment` | `qwen3gen-physics-GRPO-Qwen-Qwen3-4B-mbs8-train32-rollout8-lr1e-6-vllm0.8` | run_qwen3_generalization.sh |
| Run identity | `W&B run` | `run-20260702_073403-o8ivivjg` | wandb |
| Data | `Train file` | `datasets/sciknoweval/physics/train.parquet` | script override |
| Data | `Validation file` | `datasets/sciknoweval/physics/test.parquet` | script override |
| Data | `Train batch size` | `32` | queue/script override |
| Data | `Train max samples` | `3200` | queue/script override |
| Data | `Prompt key` | `prompt` | legacy_data.yaml default |
| Data | `Reward key` | `data_source` | legacy_data.yaml default |
| Data | `Shuffle train data` | `True` | user.yaml / legacy_data.yaml |
| Data | `Validation shuffle` | `False` | legacy_data.yaml default |
| Data | `Filter overlong prompts` | `True` | user.yaml |
| Data | `Prompt truncation` | `error` | legacy_data.yaml default |
| Data | `enable_thinking` | `false` | script override |
| Schedule | `Total training steps` | `100` | queue/script override |
| Schedule | `Total epochs` | `30` | ppo_trainer/user.yaml default |
| Schedule | `Validation before train` | `False` | queue/script override |
| Schedule | `Save frequency` | `10` | queue/script override |
| Schedule | `Validation frequency` | `10` | queue/script override |
| Sequence | `Max prompt length` | `2048` | queue/script override |
| Sequence | `Max response length` | `8192` | queue/script override |
| Sequence | `Max model length` | `10240` | queue/script override |
| Sequence | `Actor max token length per GPU` | `10240` | queue/script override |
| Rollout | `Rollout engine` | `vllm` | user.yaml |
| Rollout | `Rollout dtype` | `bfloat16` | rollout.yaml default |
| Rollout | `Train rollout n` | `8` | queue/script override |
| Rollout | `Train rollout temperature` | `1.0` | script override |
| Rollout | `Train rollout top_p` | `1.0` | script override |
| Rollout | `Train rollout do_sample` | `True` | rollout.yaml default |
| Rollout | `Calculate rollout log probs` | `True` | baseline_grpo.yaml / script override |
| Rollout | `Max num batched tokens` | `10240` | queue/script override |
| Rollout | `vLLM GPU memory utilization` | `0.8` | queue/script override |
| Rollout | `Tensor model parallel size` | `2` | rollout.yaml default |
| Rollout | `Free cache engine` | `True` | rollout.yaml default |
| Validation | `Validation rollout n` | `16` | queue/script override |
| Validation | `Validation temperature` | `0.6` | queue/script override |
| Validation | `Validation top_p` | `0.95` | queue/script override |
| Validation | `Validation do_sample` | `True` | queue/script override |
| Optimization | `Optimizer` | `AdamW` | fsdp optimizer config |
| Optimization | `Learning rate` | `1e-6` | GRPO method override |
| Optimization | `LR scheduler` | `constant` | W&B config |
| Optimization | `LR warmup steps` | `10` | script override |
| Optimization | `Weight decay` | `0.01` | script override |
| Optimization | `Betas` | `(0.9, 0.999)` | W&B config |
| Optimization | `Gradient clip` | `1.0` | script override |
| PPO/GRPO | `Policy loss mode` | `vanilla` | method override |
| PPO/GRPO | `Advantage estimator` | `grpo` | baseline_grpo.yaml |
| PPO/GRPO | `Normalize GRPO advantages by std` | `False` | baseline_grpo.yaml / script override |
| PPO/GRPO | `PPO epochs` | `1` | W&B config |
| PPO/GRPO | `PPO mini batch size` | `8` | queue/script override |
| PPO/GRPO | `PPO micro batch size per GPU` | `1` | user.yaml |
| PPO/GRPO | `Clip ratio low` | `0.2` | script override |
| PPO/GRPO | `Clip ratio high` | `0.28` | script override |
| PPO/GRPO | `Gamma` | `1.0` | ppo_trainer.yaml default |
| PPO/GRPO | `Lambda` | `1.0` | ppo_trainer.yaml default |
| PPO/GRPO | `Actor KL loss coef` | `0.0` | method override |
| PPO/GRPO | `Use KL in reward` | `False` | ppo_trainer/user.yaml |
| Rollout correction | `Importance sampling mode` | `token` | script override |
| Rollout correction | `IS threshold` | `2.0` | script override |
| FSDP/System | `Actor strategy` | `fsdp` | dp_actor.yaml |
| FSDP/System | `FSDP dtype` | `bfloat16` | W&B config |
| FSDP/System | `FSDP model dtype` | `fp32` | W&B config |
| FSDP/System | `Use torch compile` | `True` | W&B config |
| FSDP/System | `GPUs per node` | `8` | queue/script override |
| FSDP/System | `Nodes` | `1` | user.yaml |
| FSDP/System | `GPU type` | `NVIDIA H200` | wandb-metadata |
| Checkpoint/Logging | `Checkpoint root` | `checkpoints/datasets/sciknoweval/physics` | script override |
| Checkpoint/Logging | `Latest checkpointed iteration` | `100` | latest_checkpointed_iteration.txt |
| Checkpoint/Logging | `Max actor checkpoints to keep` | `1` | user.yaml |
| Checkpoint/Logging | `Logger` | `console, wandb` | ppo_trainer.yaml |
| Checkpoint/Logging | `W&B entity` | `seongryongjung-chung-ang-university` | environment |
| Checkpoint/Logging | `W&B project` | `SDPO-root` | user.yaml project_name |
| Checkpoint/Logging | `W&B group` | `QWEN3-GRPO-generalization` | method override |
Raw result and artifact files:
- `results/validation_mean16.csv`
- `results/training_scores.csv`
- `results/hyperparameters.csv`
- `results/training_score.png`
- `results/training_score.svg`
- `artifacts/config.yaml`
- `artifacts/wandb-summary.json`
- `artifacts/wandb-metadata.json`
- `artifacts/output.log`
- `artifacts/queue.log`
## Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
repo_id = "SeongryongJung/Qwen3-4B-Physics-GRPO-TR"
tokenizer = AutoTokenizer.from_pretrained(repo_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
repo_id,
torch_dtype="auto",
device_map="auto",
trust_remote_code=True,
)
```
## Source
- Checkpoint: `checkpoints/datasets/sciknoweval/physics/qwen3gen-physics-GRPO-Qwen-Qwen3-4B-mbs8-train32-rollout8-lr1e-6-vllm0.8`
- W&B run: `run-20260702_073403-o8ivivjg`
- Queue log: `artifacts/queue.log`

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default_agent_loop: single_turn_agent
num_workers: 8
calculate_log_probs: true
cudagraph_capture_sizes: null
data_parallel_size: 1
disable_log_stats: true
do_sample: true
dtype: bfloat16
enable_chunked_prefill: true
enable_prefix_caching: true
enable_rollout_routing_replay: false
enforce_eager: false
expert_parallel_size: 1
free_cache_engine: true
gpu_memory_utilization: 0.8
ignore_eos: false
layered_summon: false
load_format: dummy
log_prob_max_token_len_per_gpu: 10240
log_prob_micro_batch_size: null
log_prob_micro_batch_size_per_gpu: 1
log_prob_use_dynamic_bsz: false
logprobs_mode: processed_logprobs
max_model_len: 10240
max_num_batched_tokens: 10240
max_num_seqs: 1024
mode: async
multi_stage_wake_up: false
multi_turn:
_target_: verl.workers.config.MultiTurnConfig
enable: false
format: hermes
interaction_config_path: null
max_assistant_turns: null
max_parallel_calls: 1
max_tool_response_length: 256
max_user_turns: null
num_repeat_rollouts: null
tokenization_sanity_check_mode: strict
tool_config_path: null
tool_response_truncate_side: middle
use_inference_chat_template: false
"n": 8
name: vllm
over_sample_rate: 0
pipeline_model_parallel_size: 1
profiler:
_target_: verl.utils.profiler.ProfilerConfig
all_ranks: false
enable: false
ranks: []
save_path: outputs/profile
tool: null
tool_config:
npu:
_target_: verl.utils.profiler.config.NPUToolConfig
analysis: true
contents: []
discrete: false
level: level0
nsys:
_target_: verl.utils.profiler.config.NsightToolConfig
discrete: false
torch:
_target_: verl.utils.profiler.config.TorchProfilerToolConfig
step_end: null
step_start: 0
torch_memory:
_target_: verl.utils.profiler.config.TorchMemoryToolConfig
stack_depth: 32
trace_alloc_max_entries: 100000
prometheus:
_target_: verl.workers.config.PrometheusConfig
enable: false
file: /tmp/ray/session_latest/metrics/prometheus/prometheus.yml
port: 9090
served_model_name: Qwen/Qwen3-4B
prompt_length: 2048
quantization: null
quantization_config_file: null
response_length: 8192
scheduling_policy: fcfs
skip_dump_dir: /tmp/rollout_dump
skip_rollout: false
skip_tokenizer_init: true
temperature: 1
tensor_model_parallel_size: 2
top_k: -1
top_p: 1
trace:
_target_: verl.workers.config.TraceConfig
backend: null
max_samples_per_step_per_worker: null
token2text: false
update_weights_bucket_megabytes: 512
val_kwargs:
_target_: verl.workers.config.SamplingConfig
do_sample: true
"n": 16
temperature: 0.6
top_k: -1
top_p: 0.95
algorithm:
value:
_target_: verl.trainer.config.AlgoConfig
adv_estimator: grpo
gamma: 1
kl_ctrl:
_target_: verl.trainer.config.KLControlConfig
horizon: 10000
kl_coef: 0.001
target_kl: 0.1
type: fixed
kl_penalty: kl
lam: 1
norm_adv_by_std_in_grpo: false
pf_ppo:
reweight_method: pow
weight_pow: 2
rollout_correction:
bypass_mode: false
loss_type: ppo_clip
rollout_is: token
rollout_is_batch_normalize: false
rollout_is_threshold: 2
rollout_rs: null
rollout_rs_threshold: null
use_kl_in_reward: false
use_pf_ppo: false
critic:
value:
_target_: verl.workers.config.FSDPCriticConfig
checkpoint:
_target_: verl.trainer.config.CheckpointConfig
async_save: false
load_contents:
- model
- optimizer
- extra
save_contents:
- model
- optimizer
- extra
cliprange_value: 0.5
data_loader_seed: 42
enable: null
forward_max_token_len_per_gpu: 32768
forward_micro_batch_size: null
forward_micro_batch_size_per_gpu: null
grad_clip: 1
loss_agg_mode: token-mean
model:
_target_: verl.workers.config.FSDPCriticModelCfg
enable_activation_offload: false
enable_gradient_checkpointing: true
external_lib: null
fsdp_config:
_target_: verl.workers.config.FSDPEngineConfig
dtype: bfloat16
entropy_checkpointing: false
entropy_from_logits_with_chunking: false
forward_only: false
forward_prefetch: false
fsdp_size: -1
full_determinism: false
model_dtype: fp32
offload_policy: false
optimizer_offload: false
param_offload: false
reshard_after_forward: true
seed: 42
strategy: fsdp
ulysses_sequence_parallel_size: 1
use_orig_params: false
use_torch_compile: true
wrap_policy:
min_num_params: 0
lora_alpha: 16
lora_rank: 0
path: Qwen/Qwen3-8B
target_modules: all-linear
tiled_mlp:
enabled: false
num_shards: 4
tokenizer_path: Qwen/Qwen3-4B
trust_remote_code: true
use_remove_padding: false
use_shm: false
optim:
_target_: verl.workers.config.FSDPOptimizerConfig
betas:
- 0.9
- 0.999
clip_grad: 1
lr: 1e-05
lr_scheduler_type: constant
lr_warmup_steps: -1
lr_warmup_steps_ratio: 0
min_lr_ratio: 0
num_cycles: 0.5
optimizer: AdamW
optimizer_impl: torch.optim
override_optimizer_config: null
total_training_steps: 100
warmup_style: null
weight_decay: 0.01
ppo_epochs: 1
ppo_max_token_len_per_gpu: 32768
ppo_micro_batch_size: null
ppo_micro_batch_size_per_gpu: null
ppo_mini_batch_size: 8
profiler:
_target_: verl.utils.profiler.ProfilerConfig
all_ranks: false
enable: false
ranks: []
save_path: outputs/profile
tool: null
tool_config:
npu:
_target_: verl.utils.profiler.config.NPUToolConfig
analysis: true
contents: []
discrete: false
level: level0
nsys:
_target_: verl.utils.profiler.config.NsightToolConfig
discrete: false
torch:
_target_: verl.utils.profiler.config.TorchProfilerToolConfig
step_end: null
step_start: 0
torch_memory:
_target_: verl.utils.profiler.config.TorchMemoryToolConfig
stack_depth: 32
trace_alloc_max_entries: 100000
rollout_n: 8
shuffle: false
strategy: fsdp
ulysses_sequence_parallel_size: 1
use_dynamic_bsz: false
custom_reward_function:
value:
name: compute_score
path: /mnt/mole/SDPO/L2T/verl/utils/reward_score/feedback/__init__.py
data:
value:
apply_chat_template_kwargs:
enable_thinking: false
custom_cls:
name: null
path: null
datagen:
name: null
path: null
dataloader_num_workers: 8
filter_overlong_prompts: true
filter_overlong_prompts_workers: 1
image_key: images
image_patch_size: 14
max_prompt_length: 2048
max_response_length: 8192
prompt_key: prompt
return_full_prompt: false
return_multi_modal_inputs: true
return_raw_chat: true
return_raw_input_ids: false
reward_fn_key: data_source
sampler:
class_name: null
class_path: null
seed: null
shuffle: true
tokenizer: null
tool_config_path: null
train_batch_size: 32
train_files:
- /mnt/mole/SDPO/L2T/datasets/sciknoweval/physics/train.parquet
train_max_samples: 3200
truncation: error
trust_remote_code: true
use_shm: false
val_batch_size: null
val_files:
- /mnt/mole/SDPO/L2T/datasets/sciknoweval/physics/test.parquet
val_max_samples: -1
validation_shuffle: false
video_key: videos
global_profiler:
value:
_target_: verl.utils.profiler.ProfilerConfig
global_tool_config:
nsys:
_target_: verl.utils.profiler.config.NsightToolConfig
controller_nsight_options:
cuda-graph-trace: graph
cuda-memory-usage: "true"
trace: cuda,nvtx,cublas,ucx
discrete: false
worker_nsight_options:
capture-range: cudaProfilerApi
capture-range-end: null
cuda-graph-trace: graph
cuda-memory-usage: "true"
kill: none
trace: cuda,nvtx,cublas,ucx
torch_memory:
context: all
stack_depth: 32
stacks: all
trace_alloc_max_entries: 100000
profile_continuous_steps: false
save_path: outputs/profile
steps: null
tool: null
max_model_len:
value: 10240
ray_kwargs:
value:
ray_init:
_temp_dir: /tmp/ray_q3g_physics_grpo_Qwen3_4B
include_dashboard: false
num_cpus: null
runtime_env:
env_vars:
EXPERIMENT: qwen3gen-physics-GRPO-Qwen-Qwen3-4B-mbs8-train32-rollout8-lr1e-6-vllm0.8
TASK: datasets/sciknoweval/physics
USER: root
timeline_json_file: null
reward_manager:
value:
_target_: verl.trainer.config.config.RewardManagerConfig
module:
_target_: verl.trainer.config.config.ModuleConfig
name: custom_reward_manager
path: null
name: naive
source: register
reward_model:
value:
enable: false
enable_resource_pool: false
forward_max_token_len_per_gpu: 32768
launch_reward_fn_async: false
max_length: null
micro_batch_size: null
micro_batch_size_per_gpu: null
model:
external_lib: null
fsdp_config:
_target_: verl.workers.config.FSDPEngineConfig
forward_prefetch: false
fsdp_size: -1
param_offload: false
reshard_after_forward: true
wrap_policy:
min_num_params: 0
input_tokenizer: Qwen/Qwen3-4B
path: ~/models/FsfairX-LLaMA3-RM-v0.1
trust_remote_code: false
use_fused_kernels: false
use_remove_padding: false
use_shm: false
n_gpus_per_node: 8
nnodes: 0
num_workers: 1
profiler:
_target_: verl.utils.profiler.ProfilerConfig
all_ranks: false
enable: false
ranks: []
save_path: outputs/profile
tool: null
tool_config:
npu:
_target_: verl.utils.profiler.config.NPUToolConfig
analysis: true
contents: []
discrete: false
level: level0
nsys:
_target_: verl.utils.profiler.config.NsightToolConfig
discrete: false
torch:
_target_: verl.utils.profiler.config.TorchProfilerToolConfig
step_end: null
step_start: 0
torch_memory:
_target_: verl.utils.profiler.config.TorchMemoryToolConfig
stack_depth: 32
trace_alloc_max_entries: 100000
reward_loop_class_name: null
reward_loop_module_path: null
reward_loop_source: register
reward_manager: naive
rollout:
_target_: verl.workers.config.RolloutConfig
cudagraph_capture_sizes: null
data_parallel_size: 1
disable_log_stats: true
dtype: bfloat16
enable_chunked_prefill: true
enable_prefix_caching: true
enforce_eager: true
expert_parallel_size: 1
free_cache_engine: true
gpu_memory_utilization: 0.5
limit_images: null
load_format: auto
max_model_len: null
max_num_batched_tokens: 8192
max_num_seqs: 1024
name: ???
prompt_length: 2048
response_length: 2048
skip_tokenizer_init: false
tensor_model_parallel_size: 2
sandbox_fusion:
max_concurrent: 64
memory_limit_mb: 1024
url: null
strategy: fsdp
ulysses_sequence_parallel_size: 1
use_dynamic_bsz: false
use_reward_loop: false
trainer:
value:
balance_batch: true
critic_warmup: 0
default_hdfs_dir: null
default_local_dir: /mnt/mole/SDPO/L2T/checkpoints/datasets/sciknoweval/physics/qwen3gen-physics-GRPO-Qwen-Qwen3-4B-mbs8-train32-rollout8-lr1e-6-vllm0.8
del_local_ckpt_after_load: false
device: cuda
esi_redundant_time: 0
experiment_name: qwen3gen-physics-GRPO-Qwen-Qwen3-4B-mbs8-train32-rollout8-lr1e-6-vllm0.8
group_name: QWEN3-GRPO-generalization
log_val_generations: 0
logger:
- console
- wandb
max_actor_ckpt_to_keep: 1
max_critic_ckpt_to_keep: null
n_gpus_per_node: 8
nnodes: 1
project_name: SDPO-root
ray_wait_register_center_timeout: 300
resume_from_path: null
resume_mode: auto
rollout_data_dir: null
save_freq: 10
test_freq: 10
total_epochs: 30
total_training_steps: 100
use_legacy_worker_impl: auto
val_before_train: false
val_only: false
validation_data_dir: null
transfer_queue:
value:
enable: false
vars:
value:
ckpt_dir: /capstor/scratch/cscs/root/ttrl_runs/datasets/sciknoweval/physics
dir: /users/root/SDPO
log_dir: /users/root/output
task: datasets/sciknoweval/physics

1045
artifacts/output.log Normal file

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5099
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89
chat_template.jinja Normal file
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{%- 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 %}

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@@ -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
}

View File

@@ -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 %}

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section,parameter,value,source
Run identity,Base model,Qwen/Qwen3-4B,queue/script override
Run identity,Dataset,Physics / SciKnowEval physics,run_qwen3_generalization.sh
Run identity,Method,GRPO,run_qwen3_generalization.sh
Run identity,Config,baseline_grpo,run_qwen3_generalization.sh
Run identity,Experiment,qwen3gen-physics-GRPO-Qwen-Qwen3-4B-mbs8-train32-rollout8-lr1e-6-vllm0.8,run_qwen3_generalization.sh
Run identity,W&B run,run-20260702_073403-o8ivivjg,wandb
Data,Train file,datasets/sciknoweval/physics/train.parquet,script override
Data,Validation file,datasets/sciknoweval/physics/test.parquet,script override
Data,Train batch size,32,queue/script override
Data,Train max samples,3200,queue/script override
Data,Prompt key,prompt,legacy_data.yaml default
Data,Reward key,data_source,legacy_data.yaml default
Data,Shuffle train data,True,user.yaml / legacy_data.yaml
Data,Validation shuffle,False,legacy_data.yaml default
Data,Filter overlong prompts,True,user.yaml
Data,Prompt truncation,error,legacy_data.yaml default
Data,enable_thinking,false,script override
Schedule,Total training steps,100,queue/script override
Schedule,Total epochs,30,ppo_trainer/user.yaml default
Schedule,Validation before train,False,queue/script override
Schedule,Save frequency,10,queue/script override
Schedule,Validation frequency,10,queue/script override
Sequence,Max prompt length,2048,queue/script override
Sequence,Max response length,8192,queue/script override
Sequence,Max model length,10240,queue/script override
Sequence,Actor max token length per GPU,10240,queue/script override
Rollout,Rollout engine,vllm,user.yaml
Rollout,Rollout dtype,bfloat16,rollout.yaml default
Rollout,Train rollout n,8,queue/script override
Rollout,Train rollout temperature,1.0,script override
Rollout,Train rollout top_p,1.0,script override
Rollout,Train rollout do_sample,True,rollout.yaml default
Rollout,Calculate rollout log probs,True,baseline_grpo.yaml / script override
Rollout,Max num batched tokens,10240,queue/script override
Rollout,vLLM GPU memory utilization,0.8,queue/script override
Rollout,Tensor model parallel size,2,rollout.yaml default
Rollout,Free cache engine,True,rollout.yaml default
Validation,Validation rollout n,16,queue/script override
Validation,Validation temperature,0.6,queue/script override
Validation,Validation top_p,0.95,queue/script override
Validation,Validation do_sample,True,queue/script override
Optimization,Optimizer,AdamW,fsdp optimizer config
Optimization,Learning rate,1e-6,GRPO method override
Optimization,LR scheduler,constant,W&B config
Optimization,LR warmup steps,10,script override
Optimization,Weight decay,0.01,script override
Optimization,Betas,"(0.9, 0.999)",W&B config
Optimization,Gradient clip,1.0,script override
PPO/GRPO,Policy loss mode,vanilla,method override
PPO/GRPO,Advantage estimator,grpo,baseline_grpo.yaml
PPO/GRPO,Normalize GRPO advantages by std,False,baseline_grpo.yaml / script override
PPO/GRPO,PPO epochs,1,W&B config
PPO/GRPO,PPO mini batch size,8,queue/script override
PPO/GRPO,PPO micro batch size per GPU,1,user.yaml
PPO/GRPO,Clip ratio low,0.2,script override
PPO/GRPO,Clip ratio high,0.28,script override
PPO/GRPO,Gamma,1.0,ppo_trainer.yaml default
PPO/GRPO,Lambda,1.0,ppo_trainer.yaml default
PPO/GRPO,Actor KL loss coef,0.0,method override
PPO/GRPO,Use KL in reward,False,ppo_trainer/user.yaml
Rollout correction,Importance sampling mode,token,script override
Rollout correction,IS threshold,2.0,script override
FSDP/System,Actor strategy,fsdp,dp_actor.yaml
FSDP/System,FSDP dtype,bfloat16,W&B config
FSDP/System,FSDP model dtype,fp32,W&B config
FSDP/System,Use torch compile,True,W&B config
FSDP/System,GPUs per node,8,queue/script override
FSDP/System,Nodes,1,user.yaml
FSDP/System,GPU type,NVIDIA H200,wandb-metadata
Checkpoint/Logging,Checkpoint root,checkpoints/datasets/sciknoweval/physics,script override
Checkpoint/Logging,Latest checkpointed iteration,100,latest_checkpointed_iteration.txt
Checkpoint/Logging,Max actor checkpoints to keep,1,user.yaml
Checkpoint/Logging,Logger,"console, wandb",ppo_trainer.yaml
Checkpoint/Logging,W&B entity,seongryongjung-chung-ang-university,environment
Checkpoint/Logging,W&B project,SDPO-root,user.yaml project_name
Checkpoint/Logging,W&B group,QWEN3-GRPO-generalization,method override
1 section parameter value source
2 Run identity Base model Qwen/Qwen3-4B queue/script override
3 Run identity Dataset Physics / SciKnowEval physics run_qwen3_generalization.sh
4 Run identity Method GRPO run_qwen3_generalization.sh
5 Run identity Config baseline_grpo run_qwen3_generalization.sh
6 Run identity Experiment qwen3gen-physics-GRPO-Qwen-Qwen3-4B-mbs8-train32-rollout8-lr1e-6-vllm0.8 run_qwen3_generalization.sh
7 Run identity W&B run run-20260702_073403-o8ivivjg wandb
8 Data Train file datasets/sciknoweval/physics/train.parquet script override
9 Data Validation file datasets/sciknoweval/physics/test.parquet script override
10 Data Train batch size 32 queue/script override
11 Data Train max samples 3200 queue/script override
12 Data Prompt key prompt legacy_data.yaml default
13 Data Reward key data_source legacy_data.yaml default
14 Data Shuffle train data True user.yaml / legacy_data.yaml
15 Data Validation shuffle False legacy_data.yaml default
16 Data Filter overlong prompts True user.yaml
17 Data Prompt truncation error legacy_data.yaml default
18 Data enable_thinking false script override
19 Schedule Total training steps 100 queue/script override
20 Schedule Total epochs 30 ppo_trainer/user.yaml default
21 Schedule Validation before train False queue/script override
22 Schedule Save frequency 10 queue/script override
23 Schedule Validation frequency 10 queue/script override
24 Sequence Max prompt length 2048 queue/script override
25 Sequence Max response length 8192 queue/script override
26 Sequence Max model length 10240 queue/script override
27 Sequence Actor max token length per GPU 10240 queue/script override
28 Rollout Rollout engine vllm user.yaml
29 Rollout Rollout dtype bfloat16 rollout.yaml default
30 Rollout Train rollout n 8 queue/script override
31 Rollout Train rollout temperature 1.0 script override
32 Rollout Train rollout top_p 1.0 script override
33 Rollout Train rollout do_sample True rollout.yaml default
34 Rollout Calculate rollout log probs True baseline_grpo.yaml / script override
35 Rollout Max num batched tokens 10240 queue/script override
36 Rollout vLLM GPU memory utilization 0.8 queue/script override
37 Rollout Tensor model parallel size 2 rollout.yaml default
38 Rollout Free cache engine True rollout.yaml default
39 Validation Validation rollout n 16 queue/script override
40 Validation Validation temperature 0.6 queue/script override
41 Validation Validation top_p 0.95 queue/script override
42 Validation Validation do_sample True queue/script override
43 Optimization Optimizer AdamW fsdp optimizer config
44 Optimization Learning rate 1e-6 GRPO method override
45 Optimization LR scheduler constant W&B config
46 Optimization LR warmup steps 10 script override
47 Optimization Weight decay 0.01 script override
48 Optimization Betas (0.9, 0.999) W&B config
49 Optimization Gradient clip 1.0 script override
50 PPO/GRPO Policy loss mode vanilla method override
51 PPO/GRPO Advantage estimator grpo baseline_grpo.yaml
52 PPO/GRPO Normalize GRPO advantages by std False baseline_grpo.yaml / script override
53 PPO/GRPO PPO epochs 1 W&B config
54 PPO/GRPO PPO mini batch size 8 queue/script override
55 PPO/GRPO PPO micro batch size per GPU 1 user.yaml
56 PPO/GRPO Clip ratio low 0.2 script override
57 PPO/GRPO Clip ratio high 0.28 script override
58 PPO/GRPO Gamma 1.0 ppo_trainer.yaml default
59 PPO/GRPO Lambda 1.0 ppo_trainer.yaml default
60 PPO/GRPO Actor KL loss coef 0.0 method override
61 PPO/GRPO Use KL in reward False ppo_trainer/user.yaml
62 Rollout correction Importance sampling mode token script override
63 Rollout correction IS threshold 2.0 script override
64 FSDP/System Actor strategy fsdp dp_actor.yaml
65 FSDP/System FSDP dtype bfloat16 W&B config
66 FSDP/System FSDP model dtype fp32 W&B config
67 FSDP/System Use torch compile True W&B config
68 FSDP/System GPUs per node 8 queue/script override
69 FSDP/System Nodes 1 user.yaml
70 FSDP/System GPU type NVIDIA H200 wandb-metadata
71 Checkpoint/Logging Checkpoint root checkpoints/datasets/sciknoweval/physics script override
72 Checkpoint/Logging Latest checkpointed iteration 100 latest_checkpointed_iteration.txt
73 Checkpoint/Logging Max actor checkpoints to keep 1 user.yaml
74 Checkpoint/Logging Logger console, wandb ppo_trainer.yaml
75 Checkpoint/Logging W&B entity seongryongjung-chung-ang-university environment
76 Checkpoint/Logging W&B project SDPO-root user.yaml project_name
77 Checkpoint/Logging W&B group QWEN3-GRPO-generalization method override

24
results/summary.json Normal file
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{
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"output_dir": "/mnt/mole/SDPO/L2T/hf_upload_tr/Qwen3-4B-Physics-GRPO-TR",
"best_step": 100,
"best_val_mean16": 0.6828125,
"final_step": 100,
"final_val_mean16": 0.6828125,
"train_rows": 90,
"val_rows": 10,
"hf_model_files": [
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"chat_template.jinja",
"config.json",
"generation_config.json",
"merges.txt",
"model.safetensors.index.json",
"special_tokens_map.json",
"tokenizer.json",
"tokenizer_config.json",
"vocab.json",
"model-00001-of-00002.safetensors",
"model-00002-of-00002.safetensors"
]
}

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step,critic_score_mean
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1 step val_mean16
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31
special_tokens_map.json Normal file
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{
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