Model save

.gitattributes

@@ -33,3 +33,7 @@ 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
+plots/reward_panels_eval_chain.png filter=lfs diff=lfs merge=lfs -text
+plots/reward_panels_eval_run.png filter=lfs diff=lfs merge=lfs -text
+plots/reward_panels_train_chain.png filter=lfs diff=lfs merge=lfs -text
+plots/reward_panels_train_run.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,68 @@
+---
+base_model: Navid-AI/Yehia-7B-preview
+library_name: transformers
+model_name: Shaer-adapters-grpo
+tags:
+- generated_from_trainer
+- trl
+- grpo
+licence: license
+---
+
+# Model Card for Shaer-adapters-grpo
+
+This model is a fine-tuned version of [Navid-AI/Yehia-7B-preview](https://huggingface.co/Navid-AI/Yehia-7B-preview).
+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="Shaer-AI/Shaer-adapters-grpo", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+ 
+
+
+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: 0.23.1
+- Transformers: 4.57.0
+- Pytorch: 2.8.0
+- Datasets: 4.8.4
+- Tokenizers: 0.22.2
+
+## 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}}
+}
+```

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Navid-AI/Yehia-7B-preview",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 128,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "down_proj",
+    "q_proj",
+    "k_proj",
+    "v_proj",
+    "gate_proj",
+    "o_proj",
+    "up_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": true
+}

adapter_model.safetensors

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+size 639691872

chat_template.jinja

@@ -0,0 +1 @@
+{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\n' + system_message + '\n<</SYS>>\n\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + ' [INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' '  + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}

checkpoint_events.jsonl

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+{"timestamp_utc": "2026-04-11T12:38:05Z", "event_type": "evaluation_completed", "global_step": 2, "metrics": {"eval_loss": 0.06863964349031448, "eval_runtime": 14.0, "eval_samples_per_second": 0.571, "eval_steps_per_second": 0.143}}
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+{"timestamp_utc": "2026-04-11T12:38:07Z", "event_type": "train_end", "global_step": 2, "best_model_checkpoint": "/root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/checkpoint-2"}

config_snapshot.json

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+{
+  "run": {
+    "seed": 42,
+    "run_name_prefix": "shaer_grpo",
+    "output_root": "outputs/train",
+    "base_model_id": "Navid-AI/Yehia-7B-preview",
+    "start_adapter_repo": "Shaer-AI/Shaer-adapters",
+    "start_adapter_mode": "fresh_sft/train",
+    "output_model_repo": "Shaer-AI/Shaer-adapters-grpo"
+  },
+  "dataset": {
+    "train_dataset_id": "Shaer-AI/ashaar-enhanced-desc-baseform-final-sft-lte20-min500-splits-grpo-meter-count-v1",
+    "source_dataset_id": "Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500-splits",
+    "train_manifest_path": "outputs/curated_meter_count_locked/cap_3000/selected_manifest.csv",
+    "hard_diagnostic_manifest_path": "outputs/curated_meter_count_locked/hard_diagnostic_cap_256/selected_manifest.csv",
+    "train_split": "train",
+    "eval_split": "eval",
+    "test_split": "test",
+    "eval_bank_per_meter_per_bucket": 2,
+    "test_bank_per_meter_per_bucket": 4
+  },
+  "studies": {
+    "inspect_lengths": {
+      "output_root": "outputs/inspect_lengths",
+      "coverage_target": 0.9,
+      "push_filtered_default": false
+    },
+    "publish_grpo_splits": {
+      "output_root": "outputs/publish_grpo_splits",
+      "seed": 42,
+      "validation_total": 104,
+      "test_total": 208,
+      "validation_short_per_meter": 4,
+      "validation_full_per_meter": 4,
+      "test_short_per_meter": 8,
+      "test_full_per_meter": 8
+    },
+    "sanity_check_model": {
+      "output_root": "outputs/sanity_check_model_base_n5_k5",
+      "backend": "vllm",
+      "n_prompts_per_meter": 5,
+      "k_generations": 5,
+      "thresholds": [
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+        0.5,
+        0.7,
+        0.9
+      ],
+      "max_new_tokens": 384,
+      "temperature": 0.95,
+      "top_p": 0.95,
+      "seed": 42,
+      "vllm_gpu_memory_utilization": 0.3,
+      "vllm_tensor_parallel_size": 1,
+      "vllm_dtype": "bfloat16",
+      "vllm_max_loras": 1,
+      "vllm_max_lora_rank": 64,
+      "flashinfer_disable_version_check": true
+    },
+    "sanity_check_rewards": {
+      "output_root": "outputs/sanity_check_rewards",
+      "golden_samples": 39,
+      "seed": 42,
+      "sample_strategy": "balanced_by_base_meter"
+    }
+  },
+  "phase1": {
+    "active_rewards": [
+      "meter",
+      "exact_count_bonus"
+    ],
+    "inactive_rewards": [
+      "meaning_fit",
+      "meaning_substance",
+      "count_adherence",
+      "fluency",
+      "poeticness",
+      "cohesion"
+    ],
+    "reward_weights": {
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+      "exact_count_bonus": 0.2
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+  },
+  "model": {
+    "load_in_4bit": true,
+    "bnb_4bit_quant_type": "nf4",
+    "bnb_4bit_use_double_quant": true,
+    "gradient_checkpointing": true
+  },
+  "generation": {
+    "use_vllm": true,
+    "vllm_mode": "colocate",
+    "vllm_gpu_memory_utilization": 0.6,
+    "max_prompt_length": 1024,
+    "max_completion_length": 640,
+    "temperature": 1.0,
+    "top_p": 1.0,
+    "num_generations": 8,
+    "num_generations_eval": 2
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+  "trainer": {
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+    "per_device_train_batch_size": 1,
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+    "gradient_accumulation_steps": 8,
+    "max_steps": 1000,
+    "logging_steps": 1,
+    "eval_steps": 50,
+    "save_steps": 50,
+    "save_total_limit": 4,
+    "beta": 0.02,
+    "remove_unused_columns": false,
+    "report_to": [],
+    "bf16": true,
+    "load_best_model_at_end": true,
+    "metric_for_best_model": "eval_reward_total_mean",
+    "greater_is_better": true,
+    "hub_strategy": "checkpoint"
+  },
+  "sanity_check": {
+    "output_root": "outputs/sanity_check",
+    "max_steps": 2,
+    "num_generations": 2,
+    "subset_size": 8,
+    "save_steps": 1,
+    "eval_steps": 1,
+    "logging_steps": 1
+  },
+  "logging": {
+    "save_env_snapshot": true,
+    "save_config_snapshot": true,
+    "metrics_jsonl_name": "metrics.jsonl",
+    "metrics_csv_name": "metrics.csv",
+    "train_log_name": "train.log",
+    "generations_jsonl_name": "all_generations.jsonl",
+    "checkpoint_events_name": "checkpoint_events.jsonl",
+    "split_summary_name": "split_summary.json",
+    "plots_dir_name": "plots"
+  },
+  "watcher": {
+    "enabled": true,
+    "interval_minutes": 30,
+    "send_on_checkpoint": true,
+    "send_on_error": true
+  },
+  "preprocess_grpo": {
+    "output_root": "outputs/preprocess_grpo",
+    "num_generations": 6,
+    "generator_batch_size": 32,
+    "max_prompt_length": 1024,
+    "max_completion_length": 640,
+    "temperature": 1.0,
+    "top_p": 1.0,
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+    "vllm_gpu_memory_utilization": 0.75,
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+    "vllm_dtype": "bfloat16",
+    "vllm_max_loras": 1,
+    "vllm_max_lora_rank": 64,
+    "flashinfer_disable_version_check": true,
+    "trust_remote_code": true
+  },
+  "preprocess_grpo_pipeline": {
+    "output_root": "outputs/preprocess_grpo_pipeline",
+    "num_generations": 6,
+    "generator_batch_size": 32,
+    "max_prompt_length": 1024,
+    "max_completion_length": 640,
+    "temperature": 1.0,
+    "top_p": 1.0,
+    "progress_every": 10,
+    "judge_poll_seconds": 20,
+    "judge_claim_stale_after_seconds": 1800,
+    "vllm_gpu_memory_utilization": 0.75,
+    "vllm_tensor_parallel_size": 1,
+    "vllm_dtype": "bfloat16",
+    "vllm_max_loras": 1,
+    "vllm_max_lora_rank": 64,
+    "flashinfer_disable_version_check": true,
+    "trust_remote_code": true
+  }
+}

dataset_summary.json

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+{
+  "dataset_id": "Shaer-AI/ashaar-enhanced-desc-baseform-final-sft-lte20-min500-splits-grpo-meter-count-v1",
+  "dataset_source_id": "Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500-splits",
+  "train_dataset_id": "Shaer-AI/ashaar-enhanced-desc-baseform-final-sft-lte20-min500-splits-grpo-meter-count-v1",
+  "source_dataset_id": "Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500-splits",
+  "train_split": "train",
+  "eval_split": "eval",
+  "test_split": "test",
+  "train_size": 8,
+  "eval_size": 8,
+  "test_size": 204,
+  "hard_diagnostic_size": 8,
+  "phase1_max_bayts": "20",
+  "allowed_meters": [],
+  "train_manifest_path": "/root/workspace/Shaer/grpo/outputs/curated_meter_count_locked/cap_3000/selected_manifest.csv",
+  "hard_diagnostic_manifest_path": "/root/workspace/Shaer/grpo/outputs/curated_meter_count_locked/hard_diagnostic_cap_256/selected_manifest.csv",
+  "eval_bank_per_meter_per_bucket": 2,
+  "test_bank_per_meter_per_bucket": 4,
+  "train_length_bucket_counts": {
+    "11-20": 2,
+    "4-6": 3,
+    "1-3": 3
+  },
+  "eval_length_bucket_counts": {
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+    "1-3": 4
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+  "hard_diagnostic_length_bucket_counts": {
+    "4-6": 3,
+    "11-20": 1,
+    "1-3": 4
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+  "train_base_meter_counts": {
+    "الطويل": 1,
+    "الوافر": 3,
+    "الكامل": 1,
+    "السريع": 1,
+    "الخفيف": 2
+  },
+  "eval_base_meter_counts": {
+    "الوافر": 2,
+    "البسيط": 2,
+    "الرجز": 2,
+    "المنسرح": 2
+  },
+  "hard_diagnostic_base_meter_counts": {
+    "الرمل": 3,
+    "البسيط": 1,
+    "المتقارب": 1,
+    "المنسرح": 1,
+    "الرجز": 1,
+    "المديد": 1
+  }
+}

effective_runtime_config.json

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+{
+  "mode": "sanity",
+  "lineage": {
+    "created_at_utc": "2026-04-11T12:36:18Z",
+    "run_id": "sanity_20260411_123535",
+    "run_dir": "/root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535",
+    "chain_id": "sanity_20260411_123535",
+    "root_run_id": "sanity_20260411_123535",
+    "parent_run_id": "",
+    "parent_run_dir": "",
+    "run_sequence_index": 0
+  },
+  "dataset": {
+    "dataset_id": "Shaer-AI/ashaar-enhanced-desc-baseform-final-sft-lte20-min500-splits-grpo-meter-count-v1",
+    "dataset_source_id": "Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500-splits",
+    "train_split": "train",
+    "eval_split": "eval",
+    "test_split": "test",
+    "train_size": 8,
+    "eval_size": 8,
+    "test_size": 204,
+    "hard_diagnostic_size": 8,
+    "phase1_max_bayts": "20",
+    "allowed_meters": [],
+    "train_manifest_path": "/root/workspace/Shaer/grpo/outputs/curated_meter_count_locked/cap_3000/selected_manifest.csv",
+    "hard_diagnostic_manifest_path": "/root/workspace/Shaer/grpo/outputs/curated_meter_count_locked/hard_diagnostic_cap_256/selected_manifest.csv"
+  },
+  "rewards": {
+    "active_rewards": [
+      "meter",
+      "exact_count_bonus"
+    ],
+    "weights": {
+      "meter": 1.0,
+      "exact_count_bonus": 0.2
+    }
+  },
+  "model": {
+    "base_model_id": "Navid-AI/Yehia-7B-preview",
+    "sft_adapter_repo": "Shaer-AI/Shaer-adapters",
+    "sft_adapter_mode": "fresh_sft/train",
+    "load_in_4bit_requested": true,
+    "gradient_checkpointing": true
+  },
+  "effective_generation": {
+    "use_vllm": true,
+    "vllm_mode": "colocate",
+    "vllm_gpu_memory_utilization": 0.6,
+    "max_prompt_length": 1024,
+    "max_completion_length": 640,
+    "temperature": 1.0,
+    "top_p": 1.0,
+    "num_generations": 2,
+    "num_generations_eval": 2
+  },
+  "effective_trainer": {
+    "learning_rate": 1e-05,
+    "per_device_train_batch_size": 1,
+    "per_device_eval_batch_size_configured": 4,
+    "per_device_eval_batch_size": 4,
+    "gradient_accumulation_steps": 8,
+    "max_steps": 2,
+    "logging_steps": 1,
+    "eval_steps": 1,
+    "save_steps": 1,
+    "save_total_limit": 4,
+    "beta": 0.02,
+    "bf16": true,
+    "load_best_model_at_end": true,
+    "metric_for_best_model": "eval_reward_total_mean",
+    "greater_is_better": true,
+    "hub_strategy": "HubStrategy.CHECKPOINT",
+    "push_to_hub": true,
+    "hub_model_id": "Shaer-AI/Shaer-adapters-grpo",
+    "generations_repo_id": "Shaer-AI/Shaer-adapters-grpo-generations"
+  },
+  "sanity_mode_note": "When mode='sanity', these effective values override the base trainer/generation blocks from config_snapshot.json."
+}

env_snapshot_masked.json

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+{
+  "GRPO_HARD_DIAGNOSTIC_MANIFEST_PATH": "/root/workspace/Shaer/grpo/outputs/curated_meter_count_locked/hard_diagnostic_cap_256/selected_manifest.csv",
+  "SHELL": "/bin/bash",
+  "GRPO_TRAIN_DATASET_ID": "Shaer-AI/ashaar-enhanced-desc-baseform-final-sft-lte20-min500-splits-grpo-meter-count-v1",
+  "COLORTERM": "",
+  "GRPO_RUN_DIR": "/root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535",
+  "ELECTRON_RUN_AS_NODE": "1",
+  "GH_PAGER": "cat",
+  "PWD": "/root/workspace/Shaer/grpo",
+  "LOGNAME": "root",
+  "VSCODE_ESM_ENTRYPOINT": "vs/workbench/api/node/extensionHostProcess",
+  "RUNPOD_CPU_COUNT": "32",
+  "MOTD_SHOWN": "pam",
+  "HOME": "/root",
+  "LANG": "C.UTF-8",
+  "LS_COLORS": "",
+  "RUNPOD_POD_ID": "k1f57wae4bek9m",
+  "VSCODE_AGENT_FOLDER": "/root/.vscode-server",
+  "GRPO_CURATED_MANIFEST_PATH": "/root/workspace/Shaer/grpo/outputs/curated_meter_count_locked/cap_3000/selected_manifest.csv",
+  "SSH_CONNECTION": "212.98.144.20 53044 172.18.0.2 22",
+  "WATCHER_STEP_EMAIL_EVERY": "1",
+  "RUNPOD_MEM_GB": "125",
+  "RUNPOD_PUBLIC_IP": "91.199.227.82",
+  "RUNPOD_GPU_COUNT": "1",
+  "VSCODE_HANDLES_SIGPIPE": "true",
+  "TERM": "dumb",
+  "CODEX_THREAD_ID": "019d7bfa-ce14-7a21-ac86-d30246a06465",
+  "RUNPOD_POD_HOSTNAME": "k1f57wae4bek9m-64410a37",
+  "GRPO_OUTPUT_REPO": "Shaer-AI/Shaer-adapters-grpo",
+  "USER": "root",
+  "GIT_PAGER": "cat",
+  "RUNPOD_DC_ID": "EU-NL-1",
+  "SHLVL": "0",
+  "PAGER": "cat",
+  "VSCODE_CWD": "/root",
+  "SFT_ADAPTER_MODE": "fresh_sft/train",
+  "VSCODE_RECONNECTION_GRACE_TIME": "10800000",
+  "RUNPOD_GPU_NAME": "NVIDIA+L40S",
+  "NO_COLOR": "1",
+  "CODEX_CI": "1",
+  "LC_CTYPE": "C.UTF-8",
+  "SSH_CLIENT": "212.98.144.20 53044 22",
+  "RUNPOD_TCP_PORT_22": "31293",
+  "VSCODE_CLI_REQUIRE_TOKEN": "***MASKED***",
+  "CODEX_INTERNAL_ORIGINATOR_OVERRIDE": "codex_vscode",
+  "LC_ALL": "C.UTF-8",
+  "SFT_ADAPTER_REPO": "Shaer-AI/Shaer-adapters",
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+  "BROWSER": "/root/.vscode-server/cli/servers/Stable-41dd792b5e652393e7787322889ed5fdc58bd75b/server/bin/helpers/browser.sh",
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+}

final_adapter/README.md

@@ -0,0 +1,209 @@
+---
+base_model: Navid-AI/Yehia-7B-preview
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:Navid-AI/Yehia-7B-preview
+- grpo
+- lora
+- transformers
+- trl
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1

final_adapter/adapter_config.json

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+  "use_qalora": false,
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+}

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final_adapter/chat_template.jinja

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+{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\n' + system_message + '\n<</SYS>>\n\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + ' [INST] ' + content.strip() + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' '  + content.strip() + ' ' + eos_token }}{% endif %}{% endfor %}

final_adapter/special_tokens_map.json

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plots/chain_metrics.jsonl

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plots/chain_runs.json

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+[
+  {
+    "run_id": "sanity_20260411_123535",
+    "run_dir": "/root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535",
+    "run_sequence_index": 0,
+    "chain_id": "sanity_20260411_123535"
+  }
+]

plotter.log

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+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_train_run.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_eval_run.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_train_chain.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_eval_chain.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_train_run.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_eval_run.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_train_chain.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_eval_chain.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_train_run.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_eval_run.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_train_chain.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_eval_chain.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_train_run.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_eval_run.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_train_chain.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_eval_chain.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_train_run.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_eval_run.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_train_chain.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_eval_chain.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_train_run.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_eval_run.png
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+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_train_run.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_eval_run.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_train_chain.png
+[plot_live_rewards] updated /root/workspace/Shaer/grpo/outputs/sanity_check/sanity_20260411_123535/plots/reward_panels_eval_chain.png

plotter.pid

@@ -0,0 +1 @@
+11521

resume_decision.json

@@ -0,0 +1,12 @@
+{
+  "timestamp_utc": "2026-04-11T12:36:18Z",
+  "resume_mode": "auto",
+  "requested_spec": "",
+  "result": "fresh",
+  "reason": "resume_not_found: FileNotFoundError",
+  "local_resume_path": null,
+  "remote_repo": null,
+  "remote_prefix": null,
+  "compatibility": "unchecked",
+  "config_fingerprint": "f1af89e03892f32e677c238fac409c4e9de7ee84de340974e468cc8fb4c82d8b"
+}

reward_exact_count_bonus_debug.jsonl

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+{"i": 0, "score": 0.0, "requested_bayts": 6, "generated_bayts": 7, "has_odd_tail": false, "num_lines": 14, "exact_count": false, "bonus_value": 0.0, "complete_bayts": 7, "dataset_split": "train", "poem_preview": "أتى مؤسسها لنا فرداً شريراً\nوبتنا آمريه أمراً جميعاً\nبعثنا أفاويقنا ووفراً\nوأتحفنا بأرزاقنا جميعاً\nهدفنا ما نطيق الحياة حسناً\nوقد أعطتني الخمرة قرطعاً دقيقاً\nوبحتُ عِذارحي وعلمت صبري\nوقد أنفقت هديا عليّ رقيّا\nفيا للعالمين كم دولة حلّت\nلشقينا وكم هم أدركا فيه\nفصار العدل والفسحة منساقاً\nوحالف الغي بعدو هنالك إياك\nوصروف الزمان وقل وسميك\nقد أصبحت خامل الحق حبيرا"}
+{"i": 1, "score": 1.0, "requested_bayts": 6, "generated_bayts": 6, "has_odd_tail": false, "num_lines": 12, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 6, "dataset_split": "train", "poem_preview": "كانَ عِزٌ فَحَلَّ جِذلانِ طَروقاً\nفِي حَشاهُ بِالخُمُولِ وَتَقطِيعِ\nوَمِنَ المَورِقِ الجَديدِ صَرَيمٌ\nيَستَدارُ الخُلودِ فِي القَصدِ جَتمِع\nفَالنَّيلُ أَقسَمُ رَض يُنيخُ سُوراً\nنَحوَهُ بُرءَةٌ مِنَ الأَبعَدِ البُلغ\nهُوَكتوريا ألقَبوتُ وَسطُوهُ\nقَد تَهابَت دِعائِمَ البُطُلِ البُلغ\nأرضُهَا في اِنحِلالٍ فَعارضَتها\nبِالمِحَلِّ المُخمِسِ الخُلوِفِ البُلغ\nنِمتُ مُفَرِّداً بِغُربَةٍ يَوماً\nفَوَجَدتُ فِي "}
+{"i": 2, "score": 0.0, "requested_bayts": 17, "generated_bayts": 19, "has_odd_tail": false, "num_lines": 38, "exact_count": false, "bonus_value": 0.0, "complete_bayts": 19, "dataset_split": "train", "poem_preview": "لذاكَ لِكِّي تَعلَمَ قارِعَ الأَدْمِ\nوَلَولاي الأَكرَمَينِ أَخُ الواذِمِ\nفَإِن أَسأُوا فَإِنِّيالدَّلؤْمُ لا أَمِني\nفِراقَ الإِخوانِ إِن هَرَموا\nأَظالمعُهُم بِنائِلَةٍ يَتيمِ\nوَلا يَكفي بِها زَمرُ النوافِمِ\nوَإِلّا فالشُّروذَةُ لا أُقيمُها\nوَما النيلُ السِّواكِلُ والحقيقةُ وَهْمُل\nيُوَشِّيها الأَغرَّ الصحارِبِيُّ في\nمَشاجبٍ تُسَنُّ مِنَ الفَيلَقِ الجُوْمِ\nمَحا بارِزُهَا حَرْفَها بِخِيارِها\nوأَنصَا"}
+{"i": 3, "score": 0.0, "requested_bayts": 17, "generated_bayts": 19, "has_odd_tail": true, "num_lines": 39, "exact_count": false, "bonus_value": 0.0, "complete_bayts": 19, "dataset_split": "train", "poem_preview": "لِكُلِّ مَعشَرٍ غَفرٌ طُمُوحٌ\nبِهِ في حُبِّهِم ضَرَمُ المَغافِصِ\nوَلَكِن مِن تَميمِ بَني نُمَيرٍ\nنَواحي أَو يُفارِطُها مُفارِصي\nيَمُرُّ شُبابُها لِتَعِتاقِ خَيلٍ\nوَشَيخٌ ما دَمِي في القِرنِ ناسِصِ\nوَتَثقُبَ فَوقَهُم بِيَدي قَناةٍ\nتَزاصِفُ أَو يَفُه الحَرفُ الزَراصِصِ\n وآلِفُ مُعلَماتِ الهَولِ كابٍ\nبِجِزٍّ رَهنَ أَرجُلِ بالنَقائِصِ\nوَما أَوعِدَ التَميمِيُّ طِفلُ تِبرٍ\nكَساهُ لِوَالِدٍ عَفواً بِأَلع"}
+{"i": 4, "score": 0.0, "requested_bayts": 11, "generated_bayts": 12, "has_odd_tail": true, "num_lines": 25, "exact_count": false, "bonus_value": 0.0, "complete_bayts": 12, "dataset_split": "train", "poem_preview": "أيا نعمة الله العظيمة حملها\nعلى حمل أمثال الخضروات شوها\nبمن بدلت إقدامه لوثاته\nذمام ضيافة صيره شوها\nتلافا بها اللاوين عني تخبرن\nعلى ما رأيت نكهة الخشن ريها\nففصح فوق الماء لما جفقطر\nفظل هنالك ماءه يقطر ريها\nأبالهون حقات لها كل ذكبة\nينمون ألحمنات رميت عميها\nأدلج فصافح إسعاف طالب النهو\n فأخبر أن است كثبان سؤاتها\nوفي عستي أن أتيح من اللؤم لازمة\nولا والغير يدعى لبها سامها\nأهيم إذا نادت إلى اللطم لاهج\nر"}
+{"i": 5, "score": 0.0, "requested_bayts": 11, "generated_bayts": 12, "has_odd_tail": false, "num_lines": 24, "exact_count": false, "bonus_value": 0.0, "complete_bayts": 12, "dataset_split": "train", "poem_preview": "حسود قيادي ضاج وإذا هزو\nنفقت وأفقعني إذا شئت نفقة\nرأيت ع��ولي غير ما يستحقه\nنفيست رأي الرجال الوشيقة\nوكم ليخنى عبث الثلاث علة\nوموثقة من حسفها موثقة\nوكنت أنا لولا خللٌ عذرة\nوفي الضيم لو جادلتني رحمةٌ رقة\nواللوم والشفع المودة والهوى\nوكم كلم في الرقّ يحسب رفسة\nوكم نطقت في عارضي فحشّة\nوكم راحت من سوقها نغمقة\nولو أنني لولا جوادة طبعي\nوهرم رضاع صورها ولج نفقة\nلسميتها في الكوكب السبحة التي\nأقام بها برح ال"}
+{"i": 6, "score": 0.0, "requested_bayts": 4, "generated_bayts": 5, "has_odd_tail": false, "num_lines": 10, "exact_count": false, "bonus_value": 0.0, "complete_bayts": 5, "dataset_split": "train", "poem_preview": "أما وحي المهيمن والمسلم\nوالهدية بل بهلال البشارة\nإن الأحرار والمسيحين قوم\nلأمثالهم رق سوق البوار\nلداعيهم سكارى من رهبتنا\nوالأفضلون بأيدي الترك في بلخ\nيخال المخوف من خبث فيهم\nمجوساً أو نسيباً أو نصارى\nكأن الترك فوقهم صقور\nوهم من فرط خوفهم كالحبارى"}
+{"i": 7, "score": 1.0, "requested_bayts": 4, "generated_bayts": 4, "has_odd_tail": false, "num_lines": 8, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 4, "dataset_split": "train", "poem_preview": "إِذا أَحديَةَ الأَحرا\nرِ كانوا كَالمَسيرِ الحيارى\nيُقادُ بِأَيدي التُركِ إِذ ها\nجَه فَرخَ التُركِ التَسيرِ\nخوافٍ فَهُم لا بإِكرَ\nمٍ فيما يُقرِب أَو إِنكارِ\nكأَنَّ المُجوسَ أَو اليَهو\nد أَو نصارى نحنُ التُصارى"}
+{"i": 0, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "eval", "poem_preview": "وداع من في الوداد يَجمَعنا\nيوُدع فيه وخلّ يبُعده\nفضيمنا من فراقي أوسع\nدمع وقلبي ضيق موعده"}
+{"i": 1, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "eval", "poem_preview": "أَوصى حَصيانُ روحَه وَدَعاً\nمِن غَير وَدَاع لَم يَقلِهِ\nفَافتَرَقنا بَينَ انشراحٍ\nفي القَلب وَضيقٍ في أَدْمُعِهِ"}
+{"i": 2, "score": 1.0, "requested_bayts": 5, "generated_bayts": 5, "has_odd_tail": false, "num_lines": 10, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 5, "dataset_split": "eval", "poem_preview": "هل طرفه بارحٌ تقتلُ\nمقلتاه أمْ غرارُهُ يتصل\nعينٌ تكسِّرُ من فؤادي\nمحالفاً لا بلا وثُكلِ\nكيف السلامةُ من احتمالك يا\nمَنْ عرفها ائتلفتِ بالقلبِ\nكأنّ ما اعتذرَتْ بدا وجْهاً\nمَنْ عاذري من لها ولم تكسلِ\nلو كانت ما ألِبْت ما غدت\nتحمَرُّ بانِ الفدِ عنْ خَجَلِ الصبي"}
+{"i": 3, "score": 1.0, "requested_bayts": 5, "generated_bayts": 5, "has_odd_tail": false, "num_lines": 10, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 5, "dataset_split": "eval", "poem_preview": "ما غَرَسَت مُقلَةُ الأَسيافِ عَنكُم أَسَفاً\nباتِرَ لَم يُتَهَذَّبِ العارِضُ الذُّقُل\nأَقَمتُم صُدغاً عَلى شَأنِه بِيَفي\nأَجفَفَت مُقلَةً تُفني المُقلَةَ الكُحُل\nيا عَينُ ما أَخطَأَ التَّدذيبُ إِلاّها\nيا قَوسُ ما مَن كسباني غَيرُكُم غَزل\nكَيفَ الوَفاءُ لِمَن أَقصَتكُمُ لَيسَت\nجَوارِ خَفَّ عنهُنَّ الواشونَ وَالعُزَلُ\nيا بَغُصونِ أَجَنَّ البانُ مَيلا بِهُمُ\nوَكالنَّسرِ بِالخَجَلِ الطُّرفِيّ الحَسَلُ"}
+{"i": 0, "score": 1.0, "requested_bayts": 4, "generated_bayts": 4, "has_odd_tail": false, "num_lines": 8, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 4, "dataset_split": "eval", "poem_preview": "أعزانا الفخر والعليا بشبلٍ\nعلى صيده ساوى اللحمَ رخمُ\nورُبْ طفلٍ رفيع الشأن قائم\nبمحيي خير الدّاعي بالتمام\nأصابته أعين المآثر لفظاً\nوقال المجد إنه غلامُ\nوموّم بعدمِ مكارمِ ثغرِ\nبدتْ لو أنه أفلته ابتسامُ"}
+{"i": 1, "score": 1.0, "requested_bayts": 4, "generated_bayts": 4, "has_odd_tail": false, "num_lines": 8, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 4, "dataset_split": "eval", "poem_preview": "عَزَاءُ الفَخْرِ والعَليَاءِ تَأنَّى\nبشِّبلٍ أبْرَزُوهُ عنِ الصَّيَدِ\nغَدا بَيْنَ الرِّجَال كَيَفْلَ خِزْرٍ\nرَفيعِ الشَّانِ مَعْرُوفِ المَقَامِ\nبَكَتهُ أعْيُنُ المَادِحَاتِ وقَالَ\nعَلَى قَوْلِ المَجِيدِ أرَختُ غَارِمِ\nوعَادَى مَا تَرَى مِنْه وسامِعٌ\nعَنِ السَّمَمِ السَّماءِ وَابتِسامِ ثَغْرِ"}
+{"i": 2, "score": 1.0, "requested_bayts": 3, "generated_bayts": 3, "has_odd_tail": false, "num_lines": 6, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 3, "dataset_split": "eval", "poem_preview": "عَزَّت عَلى الأَهلِ وَالنَوَى دَارٌ\nبَينَ العَقيقِ وَبَينَ كَوثَبُ\nكَسُوؤَنَ الواكِفاتِ ساحَتَها\nمِن مُجَلجِلٍ جَوٍّهِ لَجِبُ\nما تَلَطَّفَت فَنَفَضَت مَئزَرُها\nوَلا غَدَوا بالعُلابِ دِعصَبُ"}
+{"i": 3, "score": 1.0, "requested_bayts": 3, "generated_bayts": 3, "has_odd_tail": false, "num_lines": 6, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 3, "dataset_split": "eval", "poem_preview": "يا دارَ سُقعٍ أَسقَى بِلا رَحَبِ\nمِن ذي الغَمامِ المُجَلجِلِ اللَجبِ\nداراً سَقَت بِالعَقيقِ دارَ بَني\nأَكبَيِّ ذا الكثبِّ أَو بَني كَثِبِ\nخانَتكِ من فضائِلِ المِئزرِ الدُّرَى\nوَغانِمٍ دُعدُمُ العُُلُبِ"}
+{"i": 0, "score": 0.0, "requested_bayts": 6, "generated_bayts": 7, "has_odd_tail": false, "num_lines": 14, "exact_count": false, "bonus_value": 0.0, "complete_bayts": 7, "dataset_split": "eval", "poem_preview": "يَا مَالِكاً حَوَتْ تُرْبَتُكَ قِدْماً\nيَا مَنْ لَهُ كَسَبَتْ مِنْ سَيِّدٍ وِدَّا\nيَا خَيْرَ مَوْقِعٍ يَشْهَدُ الإِخْوَانُ بِهَا\nأَنَّهُ مَحَطُّ فَضْلٍ وَمَجْرَى نَهْدَى\nلَقَدْ ثَوَى لَكَ قَوْمٌ بَادُوا وَأَبْقَى\nمَا تَرْمُقُ العَيْنُ مِنْ شَمْسٍ وَمِنْ بَدْرِ\nهَذِي بَدَائِعُ مَنْ كَانَتْ بَيَانُتهُمْ\nتُمْلِي البَيَانَ عَلَى الْيَرْعَينِ فَهْوَ سَداً\nمِنْ عِتْرَةٍ ثَوَتِ العُلُومُ بِدَارِهِمُ\nفَهُ"}
+{"i": 1, "score": 1.0, "requested_bayts": 6, "generated_bayts": 6, "has_odd_tail": false, "num_lines": 12, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 6, "dataset_split": "eval", "poem_preview": "يا قبرَ أحمدَ يا مَحلَّ فَضلِ وَليّ\nبرَحِ الخَتلِ مِن بَدر الدَليلِ حَليّ\nيا مَوضِعَ الحَقِّ مِن أَنيابِ مُعتدي\nوَمَن بِهِ صَرح الدين المَحليّ\nالمُستَوقِف قافيةً بِسُكانِهِ قَد\nبات يُسَمّي التِّبْرَيهِ بِالتَنزيؤ\nيَرجو بِحَقِّ الرَسولِ الغَني بالمحِل\nوَهوَ المَهيَم بِالحَقِّ الموفيء\nأَمنَعت أمكنتِ السودانَ ضمةً\nمِن عُترة الثّقلين دار الهُدى فعليهِ\nراحوا قبولًا على مَلكِ الرَحيم بِها\nوَما عَلا المُ"}
+{"i": 2, "score": 1.0, "requested_bayts": 5, "generated_bayts": 5, "has_odd_tail": false, "num_lines": 10, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 5, "dataset_split": "eval", "poem_preview": "وَجَفنحُ اللحمِ قَد بَشبَشتُ فيهِ\nحَوادثُهُ وَأَينَ بِهِ فِداها\nبِتَ بهيئةِ صاحبَين مَراً بي\nعَلى آثارها وَدَنَت سراها\nتُرجِّي نِلت طبق الحنظَلِيات\nعَلى شوق صبا وَمشت ذُراها\nبَيقضها إِنَّني أَهوى هِجاناً\nشَدَت لَكَ إِن أَرادَت الصرمَ نهاها\nوَإِلّا فَاِنشُ الهُجندوب وخُطَّا\nوَضَرَّ جَديدها وَطَوانى مَداها"}
+{"i": 3, "score": 1.0, "requested_bayts": 5, "generated_bayts": 5, "has_odd_tail": false, "num_lines": 10, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 5, "dataset_split": "eval", "poem_preview": "وَما بَكري وَفي أُختي لَيالٍ\nبِقَفّ المُفضِلاتِ فَأَحشاهُما\nأَقَمتنا عَلى شَفٍّ رِفاقِ جُؤذُقٍ\nفَذَكَّرَنا صِباهُوَا وَنَشاهُما\nوَندَعُها إِن تُنادِ هُجواً بِنَفسِهِ\nفَراقِب هَيهاتَ الَّذي أُزكياهُما\nأَمِ�� نَفسٍ تُنِيتكُم بَعدَ عَهدِيَه\nرُكوبُ مَدى النَومِ البَعيدِ شِفاءُها\nكَما قالَتِ الإِناءَةُ يا فَسَوَّدي\nوُقِف الانتخاباتِ الجِلَّ هُداؤُها"}
+{"i": 0, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "eval", "poem_preview": "لُذتُ بِكَ يا مَرْجَوي\nوَمَمَّنْ بَلْ والِغِيِّ\nوَفِي المُلِمّاتِ إنْ لَحْ\nظَةَ نِعْمَةِ وابْغِي غِ"}
+{"i": 1, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "eval", "poem_preview": "قلت لأحمد صَيْدِ\nفي وقت شدّاتي جِرَينا\nأنت المُرْجّي والغَوْثُ\nلو كنتَ نِعْمَ الصَّيدا"}
+{"i": 2, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "eval", "poem_preview": "باسم إله العدل قد حكمّا\nإذ نحن وجلسنا بالنادي جهرما\nلفصله القضاه بين أقران\nمستويين بالقسطاس ميزانا"}
+{"i": 3, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "eval", "poem_preview": "باسم إلهِ العدلِ حاكمنا\nالقِسْطَاسُ لدى الميزانِ هامُوا\nوفي جِهور النَّدِي إِنِ اِعتَاضُوا\nفي الخَصْم لَدى إِقْرَانهمْ فَقامُوا"}
+{"i": 0, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "train", "poem_preview": "قد جمعت مصائب دا مدبر\nوالتوت أوجاعه وتكاثرا\nطلب التطبع في القريض بجهده\nفجرت طبيعته وقام طباعها"}
+{"i": 1, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "train", "poem_preview": "جُمعَت عُهاجِرُ بَطنِهِ\nوَتَكاثَفَ الوَجدانُ فيهِ\nفَكَتَبَ طَبعاً في القَريضِ\nفَقامَ حيناً بِالنِسيانِ فيهِ"}
+{"i": 2, "score": 1.0, "requested_bayts": 4, "generated_bayts": 4, "has_odd_tail": false, "num_lines": 8, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 4, "dataset_split": "train", "poem_preview": "ألا لَيتَ المنايا حَدَّ عَنّي عُمَر\nمُعَاوِيَة وَرَيبُ الدَهرَ يَرحَبُ\nبَلَوتُ دَنِيّاً أَترَعتُ الجَوَّ في سَير\nعَلِيلَ اللُبِّ يَجنَبُ جَوهَباً مَجنَباً\nوبِالظهْرِ القَرِيحِ أُفَدَّى غرابَ\nأَذُولُ أَغَنَ مِجَلَّمَةَ القَوَافِبِ\nإِذا البَحرُ أَولِعَهُ بالبيدِ شَحَطَت\nبِمُعاوِيَةَ نَجدَتي أُمُّ مَسغَباً"}
+{"i": 3, "score": 1.0, "requested_bayts": 4, "generated_bayts": 4, "has_odd_tail": false, "num_lines": 8, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 4, "dataset_split": "train", "poem_preview": "لَتَرعَ مُعاوِيَةَ كُلَّ مُطيفٍ\nبِمَعرَسَةٍ لَدى سَنَبَ الثَقالِ\nبِهِ الإِبِلُ التَهَوى في مَواخِرٍ\nثَمانِينَ السُرى نَكلاً زِلالِ\nأَفِر لامَناقِبِهِ الشَمَّاريحُ غَلباً\nوَهُنَّ إِذا غَرثْنَ إِلى ثَمالِ\nبِصَوحِ اللَوى وَظُهورِ غِرابٍ\nوَكَونِ مُعاوِيَةَ المَأمونا"}
+{"i": 4, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "train", "poem_preview": "وعائِبٍ عَيْني لِما نَصْبَتْ\nأُسْماعَه قَدَّنْتُه بِالشِيَاشْ\nيَقولُ نَارِي لَكَ رِياشةٌ\nوإنَّ قارُونَ ليَ سِوى رِيَاشْ"}
+{"i": 5, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "train", "poem_preview": "مَه يا عَائبًا جفونَ الرِّشا\nما حُقَّ لكَ أن تَتَشوَّشَا\nسَهمُكَ كشّافُ المَنايا فلا\nيَطيرُ سَهْمٌ لكَ بُرْيُ الريشَا"}
+{"i": 6, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "train", "poem_preview": "أَرحمَنَّا بشدةٍ بالنَّبِيِّ\nوَخَفَانا إلهي من خِفالِ\nلا تَهِتنَّا وَلا تَخَلِّ عُودَ أَمري\nرائدَ إِرشِد إلينا تَمِّمِ"}
+{"i": 7, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "train", "poem_preview": "لك الإسلام إن أردت فبحمد ال\nباري ترحمنا تفضلا منكا\nلا تتركنا أيا كريم لأمرنا\nوهب رشادنا وسر لإتمامكا"}
+{"i": 0, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "eval", "poem_preview": "أتسلّي ليومِ تفريقِنا\nوقد توديتُ من لا أتوَدِّى\nوملّت أرواحنا وتشتَّتت\nوراءنا عمَدَتْ حشا الواسعِ"}
+{"i": 1, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "eval", "poem_preview": "قلْ لمَن مودع بِلا بُعدِ\nتعزَّ من لا يودّع الولهان\nفصلتما والغرام يجمعنا\nوالضيقُ في نحوه والدمع سيلان"}
+{"i": 2, "score": 1.0, "requested_bayts": 5, "generated_bayts": 5, "has_odd_tail": false, "num_lines": 10, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 5, "dataset_split": "eval", "poem_preview": "مقل العيون ما بي ليس ينصرم\nلكنها تفصم القلب بالغزل\nلم تنقشك بلا ذنب ولا خطأ\nبل أنت بالعدوان تجدين مبتلي\nأورييت ما ابتنت عني فكم خفيت\nوفي طريق الوشاة سار من أهلي\nمن داع قلبي إلى ضجرى وإلى جزعى\nوملعبى إن دنيت ذكراً على ملل\nما ملت عن عادة الغصن الذي طربت\nلانيه ولما حمرتُهُ خجل"}
+{"i": 3, "score": 1.0, "requested_bayts": 5, "generated_bayts": 5, "has_odd_tail": false, "num_lines": 10, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 5, "dataset_split": "eval", "poem_preview": "مَا قَاتِلٌ يَحْكِي عُيُونَاً قَائِلَّمَا\nمُنْتَقِمٌ فِي قَتِ السِّجَافَانِ تَكْتَقِل\nوَاسَلاً لِمَنْ أَعْرَضَتْ بِلْعَابِ أَسَىً\nوَمُطْلَباً لِلهَوَى مَالَغَيْرُهُ سَبَلِ\nوَمَنْ جَرَى صَاحِبٌ غَدَواً بِذَاتِ وَلَنْ\nيَكُونُ ضَرَّ يَعُودُ تَطَوُّلَهُ فَقَلُ\nيُسْأَمُ عُيُونٍ طُيُورٌ فِي فَمَاذَا\nتَطْعَنُ مَقَلاً يُطْعَنَّ مِثْلَ الأَسَلِ\nأَسِيِّدي قَصْمُ غُصْنٍ عَنْ عَادَاتِهِ\nوَحَيْثُ مَا اهْتَدَى "}
+{"i": 0, "score": 1.0, "requested_bayts": 4, "generated_bayts": 4, "has_odd_tail": false, "num_lines": 8, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 4, "dataset_split": "eval", "poem_preview": "عَزَاؤُكَ قد أَعزَّ الفَخْرَ قِيلاً\nرَفيعَ الشأنِ والشّانِ ظَلآمُ\nعَزَاكَ شَبِيلُكَ الفَذَّ ارَّخُوهُ\nسَما عن صَيْدِهِ باكَت حِيَامُ\nوأَطْلَعُهُ عَلى الأَيْنَاقِ طفلاً\nرَفِيعَ المَنْصِبِ المَعْروفِ مَقَامُ\nرَماكَ الغُورُ والشَّنْهُ الغ إِلاّ\nلِثَمَّ الثَّغْر مَبْسَمُهُ الضِّرَامُ"}
+{"i": 1, "score": 1.0, "requested_bayts": 4, "generated_bayts": 4, "has_odd_tail": false, "num_lines": 8, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 4, "dataset_split": "eval", "poem_preview": "عَزَاءُ الفَخْرِ والعَلْياءِ عَنْهُ\nشَبِيلٌ رُفِعَتْ عَنْهُ انْتِهازُهُ\nوَبِكَّرَ مِنْ رُتُوءٍ قِدْرُهُ فِيهِ\nوَعُرْسٌ عَنْهُ هَذا عالٍ رِسْمُ\nبَكَتْهُ عُيُونِ الْقَاصِفِ عُودٌ\nوقَالَ الْمَجْدُ مُذْ هَذَا غُلامِي\nغِيَبْتَ مَكارِمَ السُّمْتِ فَبَاعَدَتْ\nفِرَاقٍ مِنْ ثَغْرِ الفَضْلِ ابْتِسَامِ"}
+{"i": 2, "score": 1.0, "requested_bayts": 3, "generated_bayts": 3, "has_odd_tail": false, "num_lines": 6, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 3, "dataset_split": "eval", "poem_preview": "سَقَتنَا بين تُلعُ العَقيقِ إلى\nكَثيبِ رَملِ السَّ��يعِ مِن لُجُبِ\nدارٌ ما تَلَطَّفت فَضائلهَا\nبالذَّاتِ في مِئزَرٍ ولا غَذَت\nدَعدَ بلَحظاً وَلم تُغِذ بِ عُلبٍ\nما زالَ بالتَّلاعِ والخُطب"}
+{"i": 3, "score": 1.0, "requested_bayts": 3, "generated_bayts": 3, "has_odd_tail": false, "num_lines": 6, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 3, "dataset_split": "eval", "poem_preview": "سَقْياً لدارٍ بينَ العقيقِ وما\nنحوَ الكثيبَينِ من أفضَل الثمَرِ\nسقوا وسحبُ الغَمامِ مجلجِلَةٌ\nلجبٌ تَغَشَّاهُمُ من المَطَرِ\nدارٌ تَخوَّضَ نَوَاه أضرارُها\nولم تُغِذْ دَعْداً بالعُلَبِ الكُثُرُ"}
+{"i": 0, "score": 1.0, "requested_bayts": 6, "generated_bayts": 6, "has_odd_tail": false, "num_lines": 12, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 6, "dataset_split": "eval", "poem_preview": "يا قبرَ بالمصطفى نعم إقامة\nشهدت لك الفضلَ والمدحَ العميمَه\nمنّا المنادي باجتماعٍ وذيّةً\nيتلو علينا من الميقاتِ أبنَمه\nمحلّك الباقياتُ المحمَّدِيّة\nالعلمُ والحرب والسياسيةُ\nأبناءُ عترتك الثوَّاءِ بقبرهمُ\nممَّن بفتواهم يُملي البيانِ على\nإنا إلى اللَه المُهيبِ وَراحَتمْ\nومن تَصيَد مَن الغابرين شآهدا\nواللَه أكبرُ أنت الموهبُ يا\nرَحمنُ لولانا وجَيّنا الأعظُما"}
+{"i": 1, "score": 1.0, "requested_bayts": 6, "generated_bayts": 6, "has_odd_tail": false, "num_lines": 12, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 6, "dataset_split": "eval", "poem_preview": "يَاقبرَ رَبِّ المِلاَ مَنْ غامضٍ حُلاً\nفيكَ أَحَلَّ فآذَنَّا بِهِ أَثَرُ\nمُحْتَلاً بِحَظْوَةَ مَحْلٍ بِفضله\nفِيهِ وَمَأْوىً لَهُ عِلْمٌ وَمَا فكرُوا\nوَذَلِكَ الَّذِي حالتْ دَارُهُ حِفِيَةً\nفِيهِ دَرًى وَبَدَائِعُ الفِكْرِ تَمْرِي\nمِن عُتْرَةٍ سفَرُوا يعْلُ العُلُومَ بِدارِهِمْ\nفَهُمُ لأَكْرمِ القَومِ أَنْجُمٌ يُنْبِتُ\nفَالله ممثلُ موظفٍ في مَحَلاًّ\nروَحْمَتُهُ مَزْتُه إِذ لم يخصِّص مُنْفِيتُ\nوَالل"}
+{"i": 2, "score": 1.0, "requested_bayts": 5, "generated_bayts": 5, "has_odd_tail": false, "num_lines": 10, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 5, "dataset_split": "eval", "poem_preview": "وقَفنا بالديارةِ والظروفِ\nعَلى آثارِ دُورٍ قَد بَلَتاهاا\nلنستشمَّل من صَبا عيش خفضٍ\nولم تستدعيْ شجوناً عند بَاها\nوقالت حين تهواها بأَنْسى\nمقالتَها علَى عجلٍ إليها\n لنردْم مشيئَمها إن أردنا\nومنّها الصرمَ أو نُودِي بِنَاها\nفان يك خُطّ إِنا فارضُّوا بِهَمْ\nوإن لم تَبلُغِها فَارْتجِ خُطَّتايا"}
+{"i": 3, "score": 1.0, "requested_bayts": 5, "generated_bayts": 5, "has_odd_tail": false, "num_lines": 10, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 5, "dataset_split": "eval", "poem_preview": "أَلا إِنَّ المُحِبَّ لَهُ غَرِ امرَه\nبِأُنْمُلِهِ إِذا ذَكَرَ الصَّبا حَداهْ\nعَتَبتَ عَليَّ مِدرهُّ عَيشَ صِبوي\nكَمِثلِ المَكوَثِ نَقَّبَهُ غِداهْ\nوَقالَت أَنتَ فيما كانَ جاهِلٌ\nوَلَكِنَّك قَد أَصَبتَ بِها سَلاهْ\nتَسَرّي تناول جُثمانَها إِذا غَبَت\nوَتُجمل في القُدودِ إِذا أَلا شَهْ\nفَقُلتُ لَها أَرُدّي هَجوَكَ وَاِرجِعيهِ\nإِن أَراَدتِ الصِرمَ أَو دُعي مُرَداهْ"}
+{"i": 0, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "eval", "poem_preview": "إن غضَّ عني أحمدٌ\nفإنه لي نعمَ الرجُلْ\nأو ذادِني في شدَّتي\nفإنَّه غوثُ المَلَملَمْ"}
+{"i": 1, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "eval", "poem_preview": "سواكَ أحمدٌ صيا\nدِي والمُرجَى عندَ شدَّتي\nأنتَ غَوثِي في مُلمَّ\nأرجو فيكُم نُعمَى"}
+{"i": 2, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "eval", "poem_preview": "باسم إله العدل في النادي\nنحكم على الحالات بالهادي\nللفصل بين الأقران بالتصاف\nبالقسطاس وبالميزان"}
+{"i": 3, "score": 1.0, "requested_bayts": 2, "generated_bayts": 2, "has_odd_tail": false, "num_lines": 4, "exact_count": true, "bonus_value": 0.2, "complete_bayts": 2, "dataset_split": "eval", "poem_preview": "باسم إله العدل بالآفي\nأدلي حكم عادل في نادي\nلقسمة أقران معنا مساوي\nعدلا بقسطاس وميزان"}

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train.log

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+2026-04-11 12:35:42,502 | INFO | train_grpo_sanity | mode=sanity
+2026-04-11 12:37:04,532 | INFO | train_grpo_sanity | dataset_id=Shaer-AI/ashaar-enhanced-desc-baseform-final-sft-lte20-min500-splits-grpo-meter-count-v1 train_size=8 eval_size=8
+2026-04-11 12:37:04,532 | INFO | train_grpo_sanity | source_dataset_id=Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500-splits test_size=204 hard_diagnostic_size=8
+2026-04-11 12:37:04,532 | INFO | train_grpo_sanity | active_rewards=['meter', 'exact_count_bonus']
+2026-04-11 12:37:04,532 | INFO | train_grpo_sanity | reward_weights={'meter': 1.0, 'exact_count_bonus': 0.2}
+2026-04-11 12:37:04,532 | INFO | train_grpo_sanity | output_repo=Shaer-AI/Shaer-adapters-grpo
+2026-04-11 12:37:04,532 | INFO | train_grpo_sanity | train_manifest_path=/root/workspace/Shaer/grpo/outputs/curated_meter_count_locked/cap_3000/selected_manifest.csv
+2026-04-11 12:37:04,532 | INFO | train_grpo_sanity | hard_diagnostic_manifest_path=/root/workspace/Shaer/grpo/outputs/curated_meter_count_locked/hard_diagnostic_cap_256/selected_manifest.csv
+2026-04-11 12:37:04,532 | INFO | train_grpo_sanity | trainable_params=159907840 total_params=7160467456 trainable_ratio=0.022332
+2026-04-11 12:37:04,533 | INFO | train_grpo_sanity | resume_decision={"timestamp_utc": "2026-04-11T12:36:18Z", "resume_mode": "auto", "requested_spec": "", "result": "fresh", "reason": "resume_not_found: FileNotFoundError", "local_resume_path": null, "remote_repo": null, "remote_prefix": null, "compatibility": "unchecked", "config_fingerprint": "f1af89e03892f32e677c238fac409c4e9de7ee84de340974e468cc8fb4c82d8b"}
+2026-04-11 12:37:04,533 | INFO | train_grpo_sanity | starting trainer.train()
+2026-04-11 12:37:27,241 | INFO | train_grpo_sanity | metrics_logged mode=train step=1
+2026-04-11 12:37:42,965 | INFO | train_grpo_sanity | metrics_logged mode=eval step=1
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+2026-04-11 12:38:05,526 | INFO | train_grpo_sanity | metrics_logged mode=eval step=2
+2026-04-11 12:38:07,651 | INFO | train_grpo_sanity | metrics_logged mode=train step=2

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