{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "807eccb7-ee57-40bb-abdd-35c9f3136127",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ All installed\n"
     ]
    }
   ],
   "source": [
    "!pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118 -q\n",
    "!pip install \"unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git\" -q\n",
    "!pip install --no-deps trl peft accelerate bitsandbytes -q\n",
    "!pip install transformers datasets requests matplotlib numpy -q\n",
    "print(\"✅ All installed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "89dd3865-10d1-407e-9819-0f9032834ad1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "NVIDIA A100-SXM4-80GB\n",
      "85.1 GB\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "print(torch.cuda.is_available())\n",
    "print(torch.cuda.get_device_name(0))\n",
    "print(round(torch.cuda.get_device_properties(0).total_memory/1e9,1), \"GB\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e0e35f8b-0e82-4660-aa67-5724ec521212",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cloning into '/home/user/project'...\n",
      "remote: Enumerating objects: 330, done.\u001b[K\n",
      "remote: Counting objects: 100% (73/73), done.\u001b[K\n",
      "remote: Compressing objects: 100% (52/52), done.\u001b[K\n",
      "remote: Total 330 (delta 31), reused 58 (delta 20), pack-reused 257 (from 1)\u001b[K\n",
      "Receiving objects: 100% (330/330), 637.91 KiB | 19.93 MiB/s, done.\n",
      "Resolving deltas: 100% (173/173), done.\n",
      "Dockerfile   blog\t   openenv.yaml      server\t\t  uv.lock\n",
      "README.md    dataset\t   pyproject.toml    test_environment.py\n",
      "api\t     env\t   requirements.txt  tests\n",
      "baseline.py  inference.py  sdea-trained      training\n"
     ]
    }
   ],
   "source": [
    "import os, sys\n",
    "!git clone https://github.com/Mdjunaid06/sql-db-engineer-agent /home/user/project\n",
    "os.chdir(\"/home/user/project\")\n",
    "sys.path.insert(0, \".\")\n",
    "!ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9d2add93-fe60-4e7d-98e9-6d1fef5101a6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ Config set\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "os.environ[\"HF_TOKEN\"]   = \"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\"\n",
    "os.environ[\"ENV_URL\"]    = \"https://junaid0600-sql-db-engineer-agent.hf.space\"\n",
    "os.environ[\"MODEL_NAME\"] = \"unsloth/Qwen2.5-7B-Instruct\"\n",
    "os.environ[\"OUTPUT_DIR\"] = \"./sdea-trained\"\n",
    "os.environ[\"MAX_STEPS\"]  = \"200\"\n",
    "print(\"✅ Config set\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "16726a24-e960-40f8-beb4-dabd40291930",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'status': 'ok', 'version': '2.0.0', 'uptime': 20286.33}\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "r = requests.get(os.environ[\"ENV_URL\"] + \"/health\", timeout=15)\n",
    "print(r.json())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "590e3163-31a9-4b13-9294-cfc341ff8c56",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n",
      "Unsloth: Your Flash Attention 2 installation seems to be broken. Using Xformers instead. No performance changes will be seen.\n",
      "🦥 Unsloth Zoo will now patch everything to make training faster!\n",
      "✅ GPU: NVIDIA A100-SXM4-80GB\n",
      "✅ VRAM: 85.1GB\n",
      "\n",
      "[CONFIG] Model:     unsloth/Qwen2.5-7B-Instruct\n",
      "[CONFIG] Max steps: 200\n",
      "[CONFIG] Output:    ./sdea-trained\n",
      "\n",
      "  ✅ 5 from easy_scenarios.json\n",
      "  ✅ 5 from medium_scenarios.json\n",
      "  ✅ 5 from hard_scenarios.json\n",
      "  Total: 15 scenarios\n",
      "\n",
      "⏳ Loading unsloth/Qwen2.5-7B-Instruct...\n",
      "==((====))==  Unsloth 2026.4.8: Fast Qwen2 patching. Transformers: 5.5.0.\n",
      "   \\\\   /|    NVIDIA A100-SXM4-80GB. Num GPUs = 1. Max memory: 79.251 GB. Platform: Linux.\n",
      "O^O/ \\_/ \\    Torch: 2.7.1+cu118. CUDA: 8.0. CUDA Toolkit: 11.8. Triton: 3.3.1\n",
      "\\        /    Bfloat16 = TRUE. FA [Xformers = None. FA2 = False]\n",
      " \"-____-\"     Free license: http://github.com/unslothai/unsloth\n",
      "Unsloth: Fast downloading is enabled - ignore downloading bars which are red colored!\n",
      "Loading weights: 100%|███████████████████████| 339/339 [00:00<00:00, 402.24it/s]\n",
      "unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit does not have a padding token! Will use pad_token = <|PAD_TOKEN|>.\n",
      "Unsloth 2026.4.8 patched 28 layers with 28 QKV layers, 28 O layers and 28 MLP layers.\n",
      "✅ Model + LoRA ready\n",
      "\n",
      "  ✅ Dataset: 15 examples\n",
      "Unsloth: We now expect `per_device_train_batch_size` * `gradient_accumulation_steps` * `world_size` to be a multiple of `num_generations`.\n",
      "We will change the batch size of 1 to the `num_generations` of 4\n",
      "🏋️  GRPO training — 200 steps\n",
      "Expected rewards:\n",
      "  inspect_query / analyze_indexes:       ~0.10\n",
      "  create_index (no table/col match):     ~0.10  (was 0.001)\n",
      "  create_index (partial hint match):     ~0.20-0.45\n",
      "  create_index (perfect hint match):     ~0.55-0.80\n",
      "  create_index (simulator confirms):     ~0.75-0.99\n",
      "  Milestones: 25%=+0.15  50%=+0.25  75%=+0.40 (cumulative)\n",
      "\n",
      "The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'bos_token_id': None}.\n",
      "==((====))==  Unsloth - 2x faster free finetuning | Num GPUs used = 1\n",
      "   \\\\   /|    Num examples = 15 | Num Epochs = 29 | Total steps = 200\n",
      "O^O/ \\_/ \\    Batch size per device = 4 | Gradient accumulation steps = 2\n",
      "\\        /    Data Parallel GPUs = 1 | Total batch size (4 x 2 x 1) = 8\n",
      " \"-____-\"     Trainable parameters = 40,370,176 of 7,655,986,688 (0.53% trained)\n",
      "  0%|                                                   | 0/200 [00:00<?, ?it/s]Passing `generation_config` together with generation-related arguments=({'pad_token_id', 'disable_compile', 'cache_implementation'}) is deprecated and will be removed in future versions. Please pass either a `generation_config` object OR all generation parameters explicitly, but not both.\n",
      "Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "`use_return_dict` is deprecated! Use `return_dict` instead!\n",
      "Unsloth: Will smartly offload gradients to save VRAM!\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '4.917e-07', 'grad_norm': '0.1122', 'learning_rate': '0', 'num_tokens': '3900', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.0004782', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '0.1429'}\n",
      "  0%|▏                                        | 1/200 [00:19<1:03:12, 19.06s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s004 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] easy_s005 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '6.109e-07', 'grad_norm': '0.2144', 'learning_rate': '2e-06', 'num_tokens': '9040', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.1714', 'rewards/reward_fn/std': '0.1367', 'reward': '0.1714', 'reward_std': '0.1188', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0005815', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '0.2857'}\n",
      "  1%|▍                                          | 2/200 [00:30<49:04, 14.87s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +15.2pts delta=15.2[hint] 🎯 25% milestone! | score=0.469\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '3.8e-07', 'grad_norm': '0.1515', 'learning_rate': '4e-06', 'num_tokens': '1.338e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3686', 'rewards/reward_fn/std': '0.2829', 'reward': '0.3686', 'reward_std': '0.2553', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0003718', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '0.4286'}\n",
      "  2%|▋                                          | 3/200 [00:42<43:05, 13.12s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '3.278e-07', 'grad_norm': '0.1651', 'learning_rate': '6e-06', 'num_tokens': '1.961e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2573', 'rewards/reward_fn/std': '0.1403', 'reward': '0.2573', 'reward_std': '0.1503', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0003088', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '0.5714'}\n",
      "  2%|▊                                          | 4/200 [00:54<41:31, 12.71s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s003 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] easy_s004 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s005 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=analyze_indexes | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '3.371e-07', 'grad_norm': '0.1244', 'learning_rate': '8e-06', 'num_tokens': '2.563e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.1535', 'rewards/reward_fn/std': '0.1374', 'reward': '0.1535', 'reward_std': '0.1017', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0002155', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '0.7143'}\n",
      "  2%|█                                          | 5/200 [01:05<40:19, 12.41s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "{'loss': '3.265e-07', 'grad_norm': '0.09222', 'learning_rate': '1e-05', 'num_tokens': '3.14e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.1189', 'rewards/reward_fn/std': '0.05334', 'reward': '0.1189', 'reward_std': '0.03769', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.0003011', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '0.8571'}\n",
      "  3%|█▎                                         | 6/200 [01:17<39:13, 12.13s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s004 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '4.731e-07', 'grad_norm': '0.2206', 'learning_rate': '1.2e-05', 'num_tokens': '3.702e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2301', 'rewards/reward_fn/std': '0.1665', 'reward': '0.2301', 'reward_std': '0.1744', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0004765', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '1'}\n",
      "  4%|█▌                                         | 7/200 [01:29<38:29, 11.97s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] easy_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s004 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s005 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] medium_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "{'loss': '4.619e-07', 'grad_norm': '0.1626', 'learning_rate': '1.4e-05', 'num_tokens': '4.325e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.1347', 'rewards/reward_fn/std': '0.1403', 'reward': '0.1347', 'reward_std': '0.1117', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0003566', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '1.143'}\n",
      "  4%|█▋                                         | 8/200 [01:41<38:18, 11.97s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s002 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] easy_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s004 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | UNKNOWN ACTION | score=0.05\n",
      "{'loss': '3.576e-07', 'grad_norm': '0.1628', 'learning_rate': '1.6e-05', 'num_tokens': '4.841e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.1599', 'rewards/reward_fn/std': '0.141', 'reward': '0.1599', 'reward_std': '0.1016', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0002718', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '1.286'}\n",
      "  4%|█▉                                         | 9/200 [01:52<37:45, 11.86s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +23.0pts delta=22.9[sim] 🎯 25%+50% milestone! | score=0.918\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '4.768e-07', 'grad_norm': '0.1818', 'learning_rate': '1.8e-05', 'num_tokens': '5.274e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3672', 'rewards/reward_fn/std': '0.3352', 'reward': '0.3672', 'reward_std': '0.3614', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0004242', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '1.429'}\n",
      "  5%|██                                        | 10/200 [02:03<36:47, 11.62s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s004 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s005 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "{'loss': '3.874e-07', 'grad_norm': '0.2006', 'learning_rate': '2e-05', 'num_tokens': '5.778e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.1724', 'rewards/reward_fn/std': '0.1314', 'reward': '0.1724', 'reward_std': '0.1144', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0003946', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '1.571'}\n",
      "  6%|██▎                                       | 11/200 [02:15<36:12, 11.49s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s004 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '5.086e-07', 'grad_norm': '0.1991', 'learning_rate': '1.989e-05', 'num_tokens': '6.326e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.1965', 'rewards/reward_fn/std': '0.1209', 'reward': '0.1965', 'reward_std': '0.09225', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.000533', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '1.714'}\n",
      "  6%|██▌                                       | 12/200 [02:26<36:22, 11.61s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '3.427e-07', 'grad_norm': '0.07924', 'learning_rate': '1.979e-05', 'num_tokens': '6.762e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3005', 'rewards/reward_fn/std': '0.2822', 'reward': '0.3005', 'reward_std': '0.1996', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.000346', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '1.857'}\n",
      "  6%|██▋                                       | 13/200 [02:38<35:42, 11.46s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] easy_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s004 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '4.005e-07', 'grad_norm': '0.1886', 'learning_rate': '1.968e-05', 'num_tokens': '7.276e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2565', 'rewards/reward_fn/std': '0.306', 'reward': '0.2565', 'reward_std': '0.2312', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.000461', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '2'}\n",
      "  7%|██▉                                       | 14/200 [02:49<35:43, 11.52s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] medium_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s003 | UNKNOWN ACTION | score=0.05\n",
      "{'loss': '1.341e-07', 'grad_norm': '0.0961', 'learning_rate': '1.958e-05', 'num_tokens': '7.973e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.1316', 'rewards/reward_fn/std': '0.07566', 'reward': '0.1316', 'reward_std': '0.0732', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.00017', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '2.143'}\n",
      "  8%|███▏                                      | 15/200 [03:01<36:02, 11.69s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s002 | action=analyze_indexes | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "{'loss': '6.109e-07', 'grad_norm': '0.1977', 'learning_rate': '1.947e-05', 'num_tokens': '8.575e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2069', 'rewards/reward_fn/std': '0.1705', 'reward': '0.2069', 'reward_std': '0.09664', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.0006609', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '2.286'}\n",
      "  8%|███▎                                      | 16/200 [03:13<36:01, 11.75s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "{'loss': '6.66e-07', 'grad_norm': '0.1302', 'learning_rate': '1.937e-05', 'num_tokens': '9.218e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.1252', 'rewards/reward_fn/std': '0.04662', 'reward': '0.1252', 'reward_std': '0.02907', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.0006341', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '2.429'}\n",
      "  8%|███▌                                      | 17/200 [03:25<35:45, 11.72s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '4.582e-07', 'grad_norm': '0.1875', 'learning_rate': '1.926e-05', 'num_tokens': '9.608e+04', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3686', 'rewards/reward_fn/std': '0.2829', 'reward': '0.3686', 'reward_std': '0.2553', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0004388', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '2.571'}\n",
      "  9%|███▊                                      | 18/200 [03:36<34:44, 11.45s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +15.2pts delta=15.2[hint] 🎯 25% milestone! | score=0.469\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '9.015e-07', 'grad_norm': '0.2327', 'learning_rate': '1.916e-05', 'num_tokens': '1.006e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2217', 'rewards/reward_fn/std': '0.106', 'reward': '0.2217', 'reward_std': '0.09225', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0008104', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '2.714'}\n",
      " 10%|███▉                                      | 19/200 [03:47<34:22, 11.39s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +16.8pts delta=16.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s001 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.065e-06', 'grad_norm': '0.2341', 'learning_rate': '1.905e-05', 'num_tokens': '1.049e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2713', 'rewards/reward_fn/std': '0.3087', 'reward': '0.2713', 'reward_std': '0.2434', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.001054', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '2.857'}\n",
      " 10%|████▏                                     | 20/200 [03:58<33:55, 11.31s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s002 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] medium_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "{'loss': '1.192e-06', 'grad_norm': '0.2049', 'learning_rate': '1.895e-05', 'num_tokens': '1.098e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2785', 'rewards/reward_fn/std': '0.3204', 'reward': '0.2785', 'reward_std': '0.2007', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.001057', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '3'}\n",
      " 10%|████▍                                     | 21/200 [04:09<33:36, 11.27s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=analyze_indexes | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "{'loss': '7.581e-07', 'grad_norm': '0.2137', 'learning_rate': '1.884e-05', 'num_tokens': '1.154e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3193', 'rewards/reward_fn/std': '0.3204', 'reward': '0.3193', 'reward_std': '0.2957', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.000767', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '3.143'}\n",
      " 11%|████▌                                     | 22/200 [04:21<33:48, 11.39s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s004 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s005 | action=create_index | +16.8pts delta=16.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.768e-06', 'grad_norm': '0.1631', 'learning_rate': '1.874e-05', 'num_tokens': '1.209e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2839', 'rewards/reward_fn/std': '0.2992', 'reward': '0.2839', 'reward_std': '0.2117', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.001803', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '3.286'}\n",
      " 12%|████▊                                     | 23/200 [04:33<34:05, 11.56s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s001 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "{'loss': '1.594e-06', 'grad_norm': '0.2338', 'learning_rate': '1.863e-05', 'num_tokens': '1.254e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2524', 'rewards/reward_fn/std': '0.2652', 'reward': '0.2524', 'reward_std': '0.222', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.001595', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '3.429'}\n",
      " 12%|█████                                     | 24/200 [04:44<33:38, 11.47s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '9.462e-07', 'grad_norm': '0.1895', 'learning_rate': '1.853e-05', 'num_tokens': '1.306e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3225', 'rewards/reward_fn/std': '0.2941', 'reward': '0.3225', 'reward_std': '0.2134', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0008259', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '3.571'}\n",
      " 12%|█████▎                                    | 25/200 [04:56<33:36, 11.52s/it]Unsloth: Restored added_tokens_decoder metadata in ./sdea-trained/checkpoint-25/tokenizer_config.json.\n",
      "Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] easy_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.564e-06', 'grad_norm': '0.1627', 'learning_rate': '1.842e-05', 'num_tokens': '1.357e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2691', 'rewards/reward_fn/std': '0.3007', 'reward': '0.2691', 'reward_std': '0.2373', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.001573', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '3.714'}\n",
      " 13%|█████▍                                    | 26/200 [05:08<34:07, 11.77s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +23.0pts delta=22.9[sim] 🎯 25%+50% milestone! | score=0.918\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.281e-06', 'grad_norm': '0.1838', 'learning_rate': '1.832e-05', 'num_tokens': '1.406e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3167', 'rewards/reward_fn/std': '0.2709', 'reward': '0.3167', 'reward_std': '0.1978', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.001321', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '3.857'}\n",
      " 14%|█████▋                                    | 27/200 [05:19<33:23, 11.58s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '1.237e-06', 'grad_norm': '0.1721', 'learning_rate': '1.821e-05', 'num_tokens': '1.45e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2908', 'rewards/reward_fn/std': '0.156', 'reward': '0.2908', 'reward_std': '0.1637', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.001295', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '4'}\n",
      " 14%|█████▉                                    | 28/200 [05:30<32:53, 11.48s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.255e-06', 'grad_norm': '0.1781', 'learning_rate': '1.811e-05', 'num_tokens': '1.488e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3668', 'rewards/reward_fn/std': '0.3591', 'reward': '0.3668', 'reward_std': '0.3853', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.001245', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '4.143'}\n",
      " 14%|██████                                    | 29/200 [05:41<32:09, 11.28s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.412e-06', 'grad_norm': '7.177e-05', 'learning_rate': '1.8e-05', 'num_tokens': '1.54e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2007', 'rewards/reward_fn/std': '0', 'reward': '0.2007', 'reward_std': '0', 'frac_reward_zero_std': '1', 'completion_length': '150', 'kl': '0.002412', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '4.286'}\n",
      " 15%|██████▎                                   | 30/200 [05:53<32:17, 11.40s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s003 | UNKNOWN ACTION | score=0.05\n",
      "{'loss': '2.235e-06', 'grad_norm': '0.1689', 'learning_rate': '1.789e-05', 'num_tokens': '1.602e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2785', 'rewards/reward_fn/std': '0.3204', 'reward': '0.2785', 'reward_std': '0.2007', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.002089', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '4.429'}\n",
      " 16%|██████▌                                   | 31/200 [06:05<32:41, 11.60s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '4.47e-06', 'grad_norm': '0.1663', 'learning_rate': '1.779e-05', 'num_tokens': '1.651e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.313', 'rewards/reward_fn/std': '0.148', 'reward': '0.313', 'reward_std': '0.1366', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.004476', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '4.571'}\n",
      " 16%|██████▋                                   | 32/200 [06:16<32:08, 11.48s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "{'loss': '2.465e-05', 'grad_norm': '0.1842', 'learning_rate': '1.768e-05', 'num_tokens': '1.707e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2081', 'rewards/reward_fn/std': '0.1275', 'reward': '0.2081', 'reward_std': '0.1154', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02453', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '4.714'}\n",
      " 16%|██████▉                                   | 33/200 [06:28<32:01, 11.51s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '7.704e-06', 'grad_norm': '0.1164', 'learning_rate': '1.758e-05', 'num_tokens': '1.775e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2227', 'rewards/reward_fn/std': '0.1088', 'reward': '0.2227', 'reward_std': '0.08113', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.0077', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '4.857'}\n",
      " 17%|███████▏                                  | 34/200 [06:40<32:03, 11.59s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +9.2pts delta=9.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "{'loss': '4.377e-06', 'grad_norm': '0.2339', 'learning_rate': '1.747e-05', 'num_tokens': '1.82e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2712', 'rewards/reward_fn/std': '0.2539', 'reward': '0.2712', 'reward_std': '0.2149', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.004413', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '5'}\n",
      " 18%|███████▎                                  | 35/200 [06:51<31:29, 11.45s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | INVALID JSON | score=0.001\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '8.136e-06', 'grad_norm': '0.263', 'learning_rate': '1.737e-05', 'num_tokens': '1.87e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2303', 'rewards/reward_fn/std': '0.1746', 'reward': '0.2303', 'reward_std': '0.1417', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.008098', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '5.143'}\n",
      " 18%|███████▌                                  | 36/200 [07:02<31:11, 11.41s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.125e-05', 'grad_norm': '0.0654', 'learning_rate': '1.726e-05', 'num_tokens': '1.925e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01123', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '5.286'}\n",
      " 18%|███████▊                                  | 37/200 [07:14<31:28, 11.59s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '6.847e-06', 'grad_norm': '0.238', 'learning_rate': '1.716e-05', 'num_tokens': '1.969e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4349', 'rewards/reward_fn/std': '0.361', 'reward': '0.4349', 'reward_std': '0.3878', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.006827', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '5.429'}\n",
      " 19%|███████▉                                  | 38/200 [07:25<30:58, 11.47s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '6.777e-06', 'grad_norm': '0.0001491', 'learning_rate': '1.705e-05', 'num_tokens': '2.025e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2007', 'rewards/reward_fn/std': '0', 'reward': '0.2007', 'reward_std': '0', 'frac_reward_zero_std': '1', 'completion_length': '150', 'kl': '0.006777', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '5.571'}\n",
      " 20%|████████▏                                 | 39/200 [07:37<30:58, 11.54s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.093e-05', 'grad_norm': '0.2304', 'learning_rate': '1.695e-05', 'num_tokens': '2.076e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.2688', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02094', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '5.714'}\n",
      " 20%|████████▍                                 | 40/200 [07:49<30:55, 11.60s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +9.2pts delta=9.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '4.673e-06', 'grad_norm': '0.198', 'learning_rate': '1.684e-05', 'num_tokens': '2.134e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3204', 'rewards/reward_fn/std': '0.2465', 'reward': '0.3204', 'reward_std': '0.2394', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.004626', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '5.857'}\n",
      " 20%|████████▌                                 | 41/200 [08:01<31:10, 11.77s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '8.176e-06', 'grad_norm': '0.1842', 'learning_rate': '1.674e-05', 'num_tokens': '2.178e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3204', 'rewards/reward_fn/std': '0.2465', 'reward': '0.3204', 'reward_std': '0.2394', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.008147', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '6'}\n",
      " 21%|████████▊                                 | 42/200 [08:12<30:33, 11.61s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.361e-05', 'grad_norm': '0.1894', 'learning_rate': '1.663e-05', 'num_tokens': '2.229e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4254', 'rewards/reward_fn/std': '0.2612', 'reward': '0.4254', 'reward_std': '0.2437', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01359', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '6.143'}\n",
      " 22%|█████████                                 | 43/200 [08:24<30:28, 11.65s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +15.2pts delta=15.2[hint] 🎯 25% milestone! | score=0.469\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '3.745e-05', 'grad_norm': '0.1905', 'learning_rate': '1.653e-05', 'num_tokens': '2.273e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3686', 'rewards/reward_fn/std': '0.2829', 'reward': '0.3686', 'reward_std': '0.2553', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.03744', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '6.286'}\n",
      " 22%|█████████▏                                | 44/200 [08:35<29:54, 11.51s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +16.8pts delta=16.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '6.109e-06', 'grad_norm': '0.1338', 'learning_rate': '1.642e-05', 'num_tokens': '2.324e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3216', 'rewards/reward_fn/std': '0.2764', 'reward': '0.3216', 'reward_std': '0.1866', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.006121', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '6.429'}\n",
      " 22%|█████████▍                                | 45/200 [08:47<29:54, 11.57s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +70.3pts delta=70.3[sim] 🎯 25%+50% milestone! | score=0.999\n",
      "{'loss': '1.193e-05', 'grad_norm': '0.1626', 'learning_rate': '1.632e-05', 'num_tokens': '2.388e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3802', 'rewards/reward_fn/std': '0.2777', 'reward': '0.3802', 'reward_std': '0.2483', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01197', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '6.571'}\n",
      " 23%|█████████▋                                | 46/200 [08:59<30:07, 11.74s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +23.0pts delta=22.9[sim] 🎯 25%+50% milestone! | score=0.918\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '4.111e-05', 'grad_norm': '0.1817', 'learning_rate': '1.621e-05', 'num_tokens': '2.447e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3702', 'rewards/reward_fn/std': '0.2523', 'reward': '0.3702', 'reward_std': '0.2293', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.04111', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '6.714'}\n",
      " 24%|█████████▊                                | 47/200 [09:11<30:05, 11.80s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '9.656e-06', 'grad_norm': '0.1421', 'learning_rate': '1.611e-05', 'num_tokens': '2.491e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3034', 'rewards/reward_fn/std': '0.1418', 'reward': '0.3034', 'reward_std': '0.147', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0097', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '6.857'}\n",
      " 24%|██████████                                | 48/200 [09:22<29:28, 11.63s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.802e-05', 'grad_norm': '0.2296', 'learning_rate': '1.6e-05', 'num_tokens': '2.548e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.02801', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '7'}\n",
      " 24%|██████████▎                               | 49/200 [09:34<29:20, 11.66s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.63e-05', 'grad_norm': '0.07411', 'learning_rate': '1.589e-05', 'num_tokens': '2.615e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.02628', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '7.143'}\n",
      " 25%|██████████▌                               | 50/200 [09:46<29:22, 11.75s/it]Unsloth: Restored added_tokens_decoder metadata in ./sdea-trained/checkpoint-50/tokenizer_config.json.\n",
      "Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '4.835e-06', 'grad_norm': '0.3146', 'learning_rate': '1.579e-05', 'num_tokens': '2.654e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3193', 'rewards/reward_fn/std': '0.2458', 'reward': '0.3193', 'reward_std': '0.2373', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.004828', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '7.286'}\n",
      " 26%|██████████▋                               | 51/200 [09:57<28:59, 11.68s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +70.3pts delta=70.3[sim] 🎯 25%+50% milestone! | score=0.999\n",
      "{'loss': '1.556e-05', 'grad_norm': '0.2099', 'learning_rate': '1.568e-05', 'num_tokens': '2.712e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3802', 'rewards/reward_fn/std': '0.2777', 'reward': '0.3802', 'reward_std': '0.2483', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0156', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '7.429'}\n",
      " 26%|██████████▉                               | 52/200 [10:09<28:59, 11.75s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.281e-05', 'grad_norm': '0.1401', 'learning_rate': '1.558e-05', 'num_tokens': '2.769e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01278', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '7.571'}\n",
      " 26%|███████████▏                              | 53/200 [10:21<28:46, 11.74s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '7.525e-06', 'grad_norm': '0.1995', 'learning_rate': '1.547e-05', 'num_tokens': '2.812e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.007535', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '7.714'}\n",
      " 27%|███████████▎                              | 54/200 [10:32<28:09, 11.57s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.807e-05', 'grad_norm': '0.1764', 'learning_rate': '1.537e-05', 'num_tokens': '2.869e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3697', 'rewards/reward_fn/std': '0.2834', 'reward': '0.3697', 'reward_std': '0.2574', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01802', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '7.857'}\n",
      " 28%|███████████▌                              | 55/200 [10:44<28:21, 11.74s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '8.411e-06', 'grad_norm': '0.1966', 'learning_rate': '1.526e-05', 'num_tokens': '2.918e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.2688', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.008405', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '8'}\n",
      " 28%|███████████▊                              | 56/200 [10:55<27:46, 11.57s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.407e-05', 'grad_norm': '0.1008', 'learning_rate': '1.516e-05', 'num_tokens': '2.968e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3005', 'rewards/reward_fn/std': '0.2822', 'reward': '0.3005', 'reward_std': '0.1996', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01409', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '8.143'}\n",
      " 28%|███████████▉                              | 57/200 [11:07<27:23, 11.49s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.178e-05', 'grad_norm': '0.2095', 'learning_rate': '1.505e-05', 'num_tokens': '3.025e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2699', 'rewards/reward_fn/std': '0.1281', 'reward': '0.2699', 'reward_std': '0.1384', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01174', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '8.286'}\n",
      " 29%|████████████▏                             | 58/200 [11:19<27:39, 11.69s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.116e-05', 'grad_norm': '0.0001112', 'learning_rate': '1.495e-05', 'num_tokens': '3.089e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2007', 'rewards/reward_fn/std': '0', 'reward': '0.2007', 'reward_std': '0', 'frac_reward_zero_std': '1', 'completion_length': '150', 'kl': '0.01116', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '8.429'}\n",
      " 30%|████████████▍                             | 59/200 [11:29<26:44, 11.38s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +23.0pts delta=22.9[sim] 🎯 25%+50% milestone! | score=0.918\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '2.289e-05', 'grad_norm': '0.2091', 'learning_rate': '1.484e-05', 'num_tokens': '3.149e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3702', 'rewards/reward_fn/std': '0.2523', 'reward': '0.3702', 'reward_std': '0.2293', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02288', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '8.571'}\n",
      " 30%|████████████▌                             | 60/200 [11:41<26:57, 11.55s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.009e-05', 'grad_norm': '0.1568', 'learning_rate': '1.474e-05', 'num_tokens': '3.2e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.291', 'rewards/reward_fn/std': '0.1208', 'reward': '0.291', 'reward_std': '0.0555', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.0101', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '8.714'}\n",
      " 30%|████████████▊                             | 61/200 [11:53<26:53, 11.61s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '9.418e-06', 'grad_norm': '0.2196', 'learning_rate': '1.463e-05', 'num_tokens': '3.244e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.2688', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.009404', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '8.857'}\n",
      " 31%|█████████████                             | 62/200 [12:04<26:25, 11.49s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '1.014e-05', 'grad_norm': '0.1707', 'learning_rate': '1.453e-05', 'num_tokens': '3.283e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3193', 'rewards/reward_fn/std': '0.2458', 'reward': '0.3193', 'reward_std': '0.2373', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01015', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '9'}\n",
      " 32%|█████████████▏                            | 63/200 [12:15<25:48, 11.30s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.787e-05', 'grad_norm': '0.1978', 'learning_rate': '1.442e-05', 'num_tokens': '3.339e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.313', 'rewards/reward_fn/std': '0.148', 'reward': '0.313', 'reward_std': '0.1366', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01787', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '9.143'}\n",
      " 32%|█████████████▍                            | 64/200 [12:27<25:55, 11.44s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '6.355e-06', 'grad_norm': '0.1883', 'learning_rate': '1.432e-05', 'num_tokens': '3.383e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2342', 'rewards/reward_fn/std': '0.09486', 'reward': '0.2342', 'reward_std': '0.06707', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.006346', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '9.286'}\n",
      " 32%|█████████████▋                            | 65/200 [12:38<25:33, 11.36s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.035e-05', 'grad_norm': '0.09413', 'learning_rate': '1.421e-05', 'num_tokens': '3.427e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01035', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '9.429'}\n",
      " 33%|█████████████▊                            | 66/200 [12:49<25:17, 11.33s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.282e-05', 'grad_norm': '0.109', 'learning_rate': '1.411e-05', 'num_tokens': '3.497e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.0128', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '9.571'}\n",
      " 34%|██████████████                            | 67/200 [13:02<25:37, 11.56s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.022e-05', 'grad_norm': '0.1872', 'learning_rate': '1.4e-05', 'num_tokens': '3.557e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2699', 'rewards/reward_fn/std': '0.1281', 'reward': '0.2699', 'reward_std': '0.1384', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02019', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '9.714'}\n",
      " 34%|██████████████▎                           | 68/200 [13:14<25:42, 11.68s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.209e-05', 'grad_norm': '0.1497', 'learning_rate': '1.389e-05', 'num_tokens': '3.608e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01209', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '9.857'}\n",
      " 34%|██████████████▍                           | 69/200 [13:25<25:32, 11.70s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +15.2pts delta=15.2[hint] 🎯 25% milestone! | score=0.469\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '6.944e-06', 'grad_norm': '0.2597', 'learning_rate': '1.379e-05', 'num_tokens': '3.647e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3686', 'rewards/reward_fn/std': '0.2829', 'reward': '0.3686', 'reward_std': '0.2553', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.006896', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '10'}\n",
      " 35%|██████████████▋                           | 70/200 [13:36<24:49, 11.46s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '7.577e-06', 'grad_norm': '0.1161', 'learning_rate': '1.368e-05', 'num_tokens': '3.691e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.291', 'rewards/reward_fn/std': '0.1208', 'reward': '0.291', 'reward_std': '0.0555', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.007578', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '10.14'}\n",
      " 36%|██████████████▉                           | 71/200 [13:47<24:27, 11.38s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.256e-05', 'grad_norm': '0.1425', 'learning_rate': '1.358e-05', 'num_tokens': '3.755e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.291', 'rewards/reward_fn/std': '0.1208', 'reward': '0.291', 'reward_std': '0.0555', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01254', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '10.29'}\n",
      " 36%|███████████████                           | 72/200 [13:59<24:30, 11.49s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +15.2pts delta=15.2[hint] 🎯 25% milestone! | score=0.469\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '6.892e-06', 'grad_norm': '0.1392', 'learning_rate': '1.347e-05', 'num_tokens': '3.798e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3686', 'rewards/reward_fn/std': '0.2829', 'reward': '0.3686', 'reward_std': '0.2553', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.006885', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '10.43'}\n",
      " 36%|███████████████▎                          | 73/200 [14:10<24:06, 11.39s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +9.2pts delta=9.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '7.013e-06', 'grad_norm': '0.2114', 'learning_rate': '1.337e-05', 'num_tokens': '3.837e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3856', 'rewards/reward_fn/std': '0.3438', 'reward': '0.3856', 'reward_std': '0.3698', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.007029', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '10.57'}\n",
      " 37%|███████████████▌                          | 74/200 [14:20<22:58, 10.94s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.405e-05', 'grad_norm': '0.1828', 'learning_rate': '1.326e-05', 'num_tokens': '3.892e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3697', 'rewards/reward_fn/std': '0.2834', 'reward': '0.3697', 'reward_std': '0.2574', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02401', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '10.71'}\n",
      " 38%|███████████████▊                          | 75/200 [14:32<23:28, 11.26s/it]Unsloth: Restored added_tokens_decoder metadata in ./sdea-trained/checkpoint-75/tokenizer_config.json.\n",
      "Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +70.3pts delta=70.3[sim] 🎯 25%+50% milestone! | score=0.999\n",
      "{'loss': '1.371e-05', 'grad_norm': '0.1239', 'learning_rate': '1.316e-05', 'num_tokens': '3.942e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3456', 'rewards/reward_fn/std': '0.2811', 'reward': '0.3456', 'reward_std': '0.1791', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01376', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '10.86'}\n",
      " 38%|███████████████▉                          | 76/200 [14:44<23:41, 11.47s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.252e-05', 'grad_norm': '0.1058', 'learning_rate': '1.305e-05', 'num_tokens': '3.999e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01251', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '11'}\n",
      " 38%|████████████████▏                         | 77/200 [14:56<23:39, 11.54s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '8.121e-06', 'grad_norm': '0.2039', 'learning_rate': '1.295e-05', 'num_tokens': '4.038e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3686', 'rewards/reward_fn/std': '0.2829', 'reward': '0.3686', 'reward_std': '0.2553', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.008097', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '11.14'}\n",
      " 39%|████████████████▍                         | 78/200 [15:07<23:05, 11.36s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.486e-05', 'grad_norm': '0.000106', 'learning_rate': '1.284e-05', 'num_tokens': '4.095e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2007', 'rewards/reward_fn/std': '0', 'reward': '0.2007', 'reward_std': '0', 'frac_reward_zero_std': '1', 'completion_length': '150', 'kl': '0.01486', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '11.29'}\n",
      " 40%|████████████████▌                         | 79/200 [15:18<23:07, 11.47s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '3.473e-05', 'grad_norm': '0.08438', 'learning_rate': '1.274e-05', 'num_tokens': '4.155e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.03471', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '11.43'}\n",
      " 40%|████████████████▊                         | 80/200 [15:30<23:15, 11.63s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.345e-05', 'grad_norm': '0.1587', 'learning_rate': '1.263e-05', 'num_tokens': '4.217e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3045', 'rewards/reward_fn/std': '0.1432', 'reward': '0.3045', 'reward_std': '0.1491', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01344', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '11.57'}\n",
      " 40%|█████████████████                         | 81/200 [15:43<23:20, 11.77s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +15.2pts delta=15.2[hint] 🎯 25% milestone! | score=0.469\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '4.537e-06', 'grad_norm': '0.2031', 'learning_rate': '1.253e-05', 'num_tokens': '4.256e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2342', 'rewards/reward_fn/std': '0.09486', 'reward': '0.2342', 'reward_std': '0.06707', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.004539', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '11.71'}\n",
      " 41%|█████████████████▏                        | 82/200 [15:53<22:37, 11.51s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.387e-05', 'grad_norm': '0.1067', 'learning_rate': '1.242e-05', 'num_tokens': '4.313e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.291', 'rewards/reward_fn/std': '0.1208', 'reward': '0.291', 'reward_std': '0.0555', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01387', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '11.86'}\n",
      " 42%|█████████████████▍                        | 83/200 [16:05<22:34, 11.58s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.156e-05', 'grad_norm': '0.1749', 'learning_rate': '1.232e-05', 'num_tokens': '4.369e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.2688', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01155', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '12'}\n",
      " 42%|█████████████████▋                        | 84/200 [16:17<22:29, 11.63s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +9.2pts delta=9.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +70.3pts delta=70.3[sim] 🎯 25%+50% milestone! | score=0.999\n",
      "{'loss': '1.28e-05', 'grad_norm': '0.1252', 'learning_rate': '1.221e-05', 'num_tokens': '4.414e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4307', 'rewards/reward_fn/std': '0.3297', 'reward': '0.4307', 'reward_std': '0.3493', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01283', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '12.14'}\n",
      " 42%|█████████████████▊                        | 85/200 [16:28<22:07, 11.54s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.22e-05', 'grad_norm': '0.07821', 'learning_rate': '1.211e-05', 'num_tokens': '4.471e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.0122', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '12.29'}\n",
      " 43%|██████████████████                        | 86/200 [16:40<22:16, 11.72s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.822e-05', 'grad_norm': '0.1343', 'learning_rate': '1.2e-05', 'num_tokens': '4.535e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.0182', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '12.43'}\n",
      " 44%|██████████████████▎                       | 87/200 [16:52<22:04, 11.73s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.383e-05', 'grad_norm': '0.05121', 'learning_rate': '1.189e-05', 'num_tokens': '4.603e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.02379', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '12.57'}\n",
      " 44%|██████████████████▍                       | 88/200 [17:04<22:00, 11.79s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '7.555e-06', 'grad_norm': '0.1155', 'learning_rate': '1.179e-05', 'num_tokens': '4.651e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3005', 'rewards/reward_fn/std': '0.2822', 'reward': '0.3005', 'reward_std': '0.1996', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.007568', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '12.71'}\n",
      " 44%|██████████████████▋                       | 89/200 [17:15<21:28, 11.61s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.177e-05', 'grad_norm': '0.1566', 'learning_rate': '1.168e-05', 'num_tokens': '4.695e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3045', 'rewards/reward_fn/std': '0.1432', 'reward': '0.3045', 'reward_std': '0.1491', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01176', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '12.86'}\n",
      " 45%|██████████████████▉                       | 90/200 [17:27<21:04, 11.50s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '5.856e-06', 'grad_norm': '0.2426', 'learning_rate': '1.158e-05', 'num_tokens': '4.734e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3856', 'rewards/reward_fn/std': '0.3438', 'reward': '0.3856', 'reward_std': '0.3698', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.005852', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '13'}\n",
      " 46%|███████████████████                       | 91/200 [17:37<20:33, 11.32s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +70.3pts delta=70.3[sim] 🎯 25%+50% milestone! | score=0.999\n",
      "{'loss': '1.283e-05', 'grad_norm': '0.2144', 'learning_rate': '1.147e-05', 'num_tokens': '4.784e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3802', 'rewards/reward_fn/std': '0.2777', 'reward': '0.3802', 'reward_std': '0.2483', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01285', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '13.14'}\n",
      " 46%|███████████████████▎                      | 92/200 [17:49<20:22, 11.32s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '8.93e-06', 'grad_norm': '0.1573', 'learning_rate': '1.137e-05', 'num_tokens': '4.842e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3697', 'rewards/reward_fn/std': '0.2834', 'reward': '0.3697', 'reward_std': '0.2574', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.008889', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '13.29'}\n",
      " 46%|███████████████████▌                      | 93/200 [18:01<20:37, 11.56s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.109e-05', 'grad_norm': '0.164', 'learning_rate': '1.126e-05', 'num_tokens': '4.901e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.2688', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02109', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '13.43'}\n",
      " 47%|███████████████████▋                      | 94/200 [18:13<20:38, 11.68s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.156e-05', 'grad_norm': '0.0966', 'learning_rate': '1.116e-05', 'num_tokens': '4.966e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01155', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '13.57'}\n",
      " 48%|███████████████████▉                      | 95/200 [18:25<20:29, 11.71s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '5.449e-06', 'grad_norm': '0.184', 'learning_rate': '1.105e-05', 'num_tokens': '5.004e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3193', 'rewards/reward_fn/std': '0.2458', 'reward': '0.3193', 'reward_std': '0.2373', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.005445', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '13.71'}\n",
      " 48%|████████████████████▏                     | 96/200 [18:36<19:52, 11.46s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.174e-05', 'grad_norm': '0.1918', 'learning_rate': '1.095e-05', 'num_tokens': '5.056e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.1882', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01174', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '13.86'}\n",
      " 48%|████████████████████▎                     | 97/200 [18:47<19:48, 11.54s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +23.0pts delta=22.9[sim] 🎯 25%+50% milestone! | score=0.918\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '8.787e-06', 'grad_norm': '0.1154', 'learning_rate': '1.084e-05', 'num_tokens': '5.099e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3356', 'rewards/reward_fn/std': '0.2545', 'reward': '0.3356', 'reward_std': '0.1601', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.008778', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '14'}\n",
      " 49%|████████████████████▌                     | 98/200 [18:58<19:26, 11.44s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +9.2pts delta=9.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +15.2pts delta=15.2[hint] 🎯 25% milestone! | score=0.469\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '5.938e-06', 'grad_norm': '0.2242', 'learning_rate': '1.074e-05', 'num_tokens': '5.138e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3193', 'rewards/reward_fn/std': '0.2458', 'reward': '0.3193', 'reward_std': '0.2373', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.005943', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '14.14'}\n",
      " 50%|████████████████████▊                     | 99/200 [19:09<18:58, 11.28s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +23.0pts delta=22.9[sim] 🎯 25%+50% milestone! | score=0.918\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '7.525e-06', 'grad_norm': '0.1032', 'learning_rate': '1.063e-05', 'num_tokens': '5.181e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3356', 'rewards/reward_fn/std': '0.2545', 'reward': '0.3356', 'reward_std': '0.1601', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.007558', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '14.29'}\n",
      " 50%|████████████████████▌                    | 100/200 [19:21<18:44, 11.24s/it]Unsloth: Restored added_tokens_decoder metadata in ./sdea-trained/checkpoint-100/tokenizer_config.json.\n",
      "Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '2.205e-05', 'grad_norm': '0.09167', 'learning_rate': '1.053e-05', 'num_tokens': '5.245e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.291', 'rewards/reward_fn/std': '0.1208', 'reward': '0.291', 'reward_std': '0.0555', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.02203', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '14.43'}\n",
      " 50%|████████████████████▋                    | 101/200 [19:33<19:05, 11.57s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '8.635e-06', 'grad_norm': '0.1806', 'learning_rate': '1.042e-05', 'num_tokens': '5.289e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4254', 'rewards/reward_fn/std': '0.2612', 'reward': '0.4254', 'reward_std': '0.2437', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.008594', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '14.57'}\n",
      " 51%|████████████████████▉                    | 102/200 [19:44<18:43, 11.47s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | UNKNOWN ACTION | score=0.05\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '0.0002333', 'grad_norm': '0.2401', 'learning_rate': '1.032e-05', 'num_tokens': '5.359e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2165', 'rewards/reward_fn/std': '0.1179', 'reward': '0.2165', 'reward_std': '0.1069', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.2333', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '14.71'}\n",
      " 52%|█████████████████████                    | 103/200 [19:56<18:52, 11.67s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.722e-05', 'grad_norm': '0.1489', 'learning_rate': '1.021e-05', 'num_tokens': '5.419e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2699', 'rewards/reward_fn/std': '0.1281', 'reward': '0.2699', 'reward_std': '0.1384', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02719', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '14.86'}\n",
      " 52%|█████████████████████▎                   | 104/200 [20:08<18:49, 11.77s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=analyze_indexes | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.779e-05', 'grad_norm': '0.2227', 'learning_rate': '1.011e-05', 'num_tokens': '5.463e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4223', 'rewards/reward_fn/std': '0.372', 'reward': '0.4223', 'reward_std': '0.401', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02781', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '15'}\n",
      " 52%|█████████████████████▌                   | 105/200 [20:19<18:21, 11.60s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.05e-05', 'grad_norm': '0.07271', 'learning_rate': '1e-05', 'num_tokens': '5.533e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01048', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '15.14'}\n",
      " 53%|█████████████████████▋                   | 106/200 [20:32<18:24, 11.75s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.569e-05', 'grad_norm': '0.09291', 'learning_rate': '9.895e-06', 'num_tokens': '5.583e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01569', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '15.29'}\n",
      " 54%|█████████████████████▉                   | 107/200 [20:43<18:00, 11.62s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.432e-05', 'grad_norm': '0.0873', 'learning_rate': '9.789e-06', 'num_tokens': '5.651e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.02429', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '15.43'}\n",
      " 54%|██████████████████████▏                  | 108/200 [20:55<17:57, 11.72s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +16.8pts delta=16.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '7.719e-06', 'grad_norm': '0.2066', 'learning_rate': '9.684e-06', 'num_tokens': '5.69e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.456', 'rewards/reward_fn/std': '0.3472', 'reward': '0.456', 'reward_std': '0.3747', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.007703', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '15.57'}\n",
      " 55%|██████████████████████▎                  | 109/200 [21:06<17:23, 11.47s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '1.03e-05', 'grad_norm': '0.2073', 'learning_rate': '9.579e-06', 'num_tokens': '5.733e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2688', 'rewards/reward_fn/std': '0.1262', 'reward': '0.2688', 'reward_std': '0.1363', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0103', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '15.71'}\n",
      " 55%|██████████████████████▌                  | 110/200 [21:17<17:04, 11.39s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.04e-05', 'grad_norm': '0.1459', 'learning_rate': '9.474e-06', 'num_tokens': '5.777e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4349', 'rewards/reward_fn/std': '0.361', 'reward': '0.4349', 'reward_std': '0.3878', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01039', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '15.86'}\n",
      " 56%|██████████████████████▊                  | 111/200 [21:28<16:46, 11.31s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.451e-05', 'grad_norm': '0.1884', 'learning_rate': '9.368e-06', 'num_tokens': '5.829e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3761', 'rewards/reward_fn/std': '0.2345', 'reward': '0.3761', 'reward_std': '0.2257', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0145', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '16'}\n",
      " 56%|██████████████████████▉                  | 112/200 [21:40<16:46, 11.44s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '3.001e-05', 'grad_norm': '0.1985', 'learning_rate': '9.263e-06', 'num_tokens': '5.893e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.03', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '16.14'}\n",
      " 56%|███████████████████████▏                 | 113/200 [21:51<16:43, 11.54s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.058e-05', 'grad_norm': '0.198', 'learning_rate': '9.158e-06', 'num_tokens': '5.937e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.2688', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0106', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '16.29'}\n",
      " 57%|███████████████████████▎                 | 114/200 [22:03<16:23, 11.43s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +9.2pts delta=9.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '8.091e-06', 'grad_norm': '0.2167', 'learning_rate': '9.053e-06', 'num_tokens': '5.98e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3856', 'rewards/reward_fn/std': '0.3438', 'reward': '0.3856', 'reward_std': '0.3698', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.008108', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '16.43'}\n",
      " 57%|███████████████████████▌                 | 115/200 [22:14<16:05, 11.36s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.216e-05', 'grad_norm': '0.1377', 'learning_rate': '8.947e-06', 'num_tokens': '6.037e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2699', 'rewards/reward_fn/std': '0.1281', 'reward': '0.2699', 'reward_std': '0.07989', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01216', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '16.57'}\n",
      " 58%|███████████████████████▊                 | 116/200 [22:26<16:02, 11.46s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +15.2pts delta=15.2[hint] 🎯 25% milestone! | score=0.469\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '8.255e-06', 'grad_norm': '0.1407', 'learning_rate': '8.842e-06', 'num_tokens': '6.076e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2342', 'rewards/reward_fn/std': '0.09486', 'reward': '0.2342', 'reward_std': '0.06707', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.008273', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '16.71'}\n",
      " 58%|███████████████████████▉                 | 117/200 [22:36<15:36, 11.29s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.181e-05', 'grad_norm': '0.07324', 'learning_rate': '8.737e-06', 'num_tokens': '6.135e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.0218', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '16.86'}\n",
      " 59%|████████████████████████▏                | 118/200 [22:49<15:46, 11.55s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.848e-05', 'grad_norm': '0.2056', 'learning_rate': '8.632e-06', 'num_tokens': '6.193e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3697', 'rewards/reward_fn/std': '0.2834', 'reward': '0.3697', 'reward_std': '0.2574', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01843', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '17'}\n",
      " 60%|████████████████████████▍                | 119/200 [23:01<15:49, 11.72s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.486e-05', 'grad_norm': '0.1477', 'learning_rate': '8.526e-06', 'num_tokens': '6.257e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.291', 'rewards/reward_fn/std': '0.1208', 'reward': '0.291', 'reward_std': '0.0555', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01486', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '17.14'}\n",
      " 60%|████████████████████████▌                | 120/200 [23:12<15:38, 11.73s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +9.2pts delta=9.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.728e-05', 'grad_norm': '0.2413', 'learning_rate': '8.421e-06', 'num_tokens': '6.312e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3204', 'rewards/reward_fn/std': '0.2465', 'reward': '0.3204', 'reward_std': '0.2394', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02725', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '17.29'}\n",
      " 60%|████████████████████████▊                | 121/200 [23:24<15:33, 11.81s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '8.249e-06', 'grad_norm': '0.1394', 'learning_rate': '8.316e-06', 'num_tokens': '6.356e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.291', 'rewards/reward_fn/std': '0.1208', 'reward': '0.291', 'reward_std': '0.0555', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.008244', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '17.43'}\n",
      " 61%|█████████████████████████                | 122/200 [23:36<15:07, 11.64s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=inspect_query | +0.0pts delta=0.0[none]  | score=0.100\n",
      "  [REWARD] medium_s003 | action=create_index | +70.3pts delta=70.3[sim] 🎯 25%+50% milestone! | score=0.999\n",
      "{'loss': '1.614e-05', 'grad_norm': '0.2155', 'learning_rate': '8.211e-06', 'num_tokens': '6.401e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4569', 'rewards/reward_fn/std': '0.3611', 'reward': '0.4569', 'reward_std': '0.3896', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01615', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '17.57'}\n",
      " 62%|█████████████████████████▏               | 123/200 [23:47<14:49, 11.55s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.176e-05', 'grad_norm': '0.2048', 'learning_rate': '8.105e-06', 'num_tokens': '6.444e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4349', 'rewards/reward_fn/std': '0.361', 'reward': '0.4349', 'reward_std': '0.3878', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01174', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '17.71'}\n",
      " 62%|█████████████████████████▍               | 124/200 [23:58<14:29, 11.44s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +15.2pts delta=15.2[hint] 🎯 25% milestone! | score=0.469\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.059e-05', 'grad_norm': '0.09927', 'learning_rate': '8e-06', 'num_tokens': '6.488e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2342', 'rewards/reward_fn/std': '0.09486', 'reward': '0.2342', 'reward_std': '0.06707', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01061', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '17.86'}\n",
      " 62%|█████████████████████████▋               | 125/200 [24:09<14:11, 11.36s/it]Unsloth: Restored added_tokens_decoder metadata in ./sdea-trained/checkpoint-125/tokenizer_config.json.\n",
      "Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.432e-05', 'grad_norm': '0.1201', 'learning_rate': '7.895e-06', 'num_tokens': '6.55e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2699', 'rewards/reward_fn/std': '0.1281', 'reward': '0.2699', 'reward_std': '0.1384', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01429', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '18'}\n",
      " 63%|█████████████████████████▊               | 126/200 [24:22<14:29, 11.75s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '1.021e-05', 'grad_norm': '0.1414', 'learning_rate': '7.789e-06', 'num_tokens': '6.594e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2342', 'rewards/reward_fn/std': '0.09486', 'reward': '0.2342', 'reward_std': '0.06707', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01021', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '18.14'}\n",
      " 64%|██████████████████████████               | 127/200 [24:33<14:05, 11.58s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.036e-05', 'grad_norm': '0.1877', 'learning_rate': '7.684e-06', 'num_tokens': '6.65e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3005', 'rewards/reward_fn/std': '0.2822', 'reward': '0.3005', 'reward_std': '0.1996', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.02037', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '18.29'}\n",
      " 64%|██████████████████████████▏              | 128/200 [24:45<13:57, 11.63s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.317e-05', 'grad_norm': '0.1096', 'learning_rate': '7.579e-06', 'num_tokens': '6.707e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01313', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '18.43'}\n",
      " 64%|██████████████████████████▍              | 129/200 [24:57<13:47, 11.66s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '9.092e-06', 'grad_norm': '0.1988', 'learning_rate': '7.474e-06', 'num_tokens': '6.745e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3856', 'rewards/reward_fn/std': '0.3438', 'reward': '0.3856', 'reward_std': '0.3698', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.009111', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '18.57'}\n",
      " 65%|██████████████████████████▋              | 130/200 [25:08<13:19, 11.43s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.749e-05', 'grad_norm': '0.1775', 'learning_rate': '7.368e-06', 'num_tokens': '6.802e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3256', 'rewards/reward_fn/std': '0.1305', 'reward': '0.3256', 'reward_std': '0.1247', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01746', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '18.71'}\n",
      " 66%|██████████████████████████▊              | 131/200 [25:19<13:14, 11.52s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +16.8pts delta=16.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '9.82e-06', 'grad_norm': '0.2037', 'learning_rate': '7.263e-06', 'num_tokens': '6.841e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.456', 'rewards/reward_fn/std': '0.3472', 'reward': '0.456', 'reward_std': '0.3747', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0098', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '18.86'}\n",
      " 66%|███████████████████████████              | 132/200 [25:30<12:50, 11.34s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.68e-05', 'grad_norm': '0.09579', 'learning_rate': '7.158e-06', 'num_tokens': '6.904e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01677', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '19'}\n",
      " 66%|███████████████████████████▎             | 133/200 [25:42<12:52, 11.53s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=submit_report | +0.0pts delta=0.0[none]  | score=0.050\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +23.0pts delta=22.9[sim] 🎯 25%+50% milestone! | score=0.918\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.004e-05', 'grad_norm': '0.1667', 'learning_rate': '7.053e-06', 'num_tokens': '6.953e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4165', 'rewards/reward_fn/std': '0.3558', 'reward': '0.4165', 'reward_std': '0.3752', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01005', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '19.14'}\n",
      " 67%|███████████████████████████▍             | 134/200 [25:53<12:31, 11.39s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '9.328e-06', 'grad_norm': '0.2619', 'learning_rate': '6.947e-06', 'num_tokens': '6.991e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3856', 'rewards/reward_fn/std': '0.3438', 'reward': '0.3856', 'reward_std': '0.3698', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.009314', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '19.29'}\n",
      " 68%|███████████████████████████▋             | 135/200 [26:04<12:07, 11.20s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.275e-05', 'grad_norm': '0.1393', 'learning_rate': '6.842e-06', 'num_tokens': '7.043e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01274', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '19.43'}\n",
      " 68%|███████████████████████████▉             | 136/200 [26:16<12:04, 11.32s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +16.8pts delta=16.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.201e-05', 'grad_norm': '0.2104', 'learning_rate': '6.737e-06', 'num_tokens': '7.087e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3908', 'rewards/reward_fn/std': '0.2714', 'reward': '0.3908', 'reward_std': '0.2664', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01206', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '19.57'}\n",
      " 68%|████████████████████████████             | 137/200 [26:27<11:48, 11.25s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.892e-05', 'grad_norm': '0.08359', 'learning_rate': '6.632e-06', 'num_tokens': '7.157e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.0189', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '19.71'}\n",
      " 69%|████████████████████████████▎            | 138/200 [26:39<11:51, 11.47s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '2.02e-05', 'grad_norm': '0.107', 'learning_rate': '6.526e-06', 'num_tokens': '7.212e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2688', 'rewards/reward_fn/std': '0.1262', 'reward': '0.2688', 'reward_std': '0.1363', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02019', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '19.86'}\n",
      " 70%|████████████████████████████▍            | 139/200 [26:51<11:46, 11.59s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '0.0001004', 'grad_norm': '0.1459', 'learning_rate': '6.421e-06', 'num_tokens': '7.262e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.291', 'rewards/reward_fn/std': '0.1208', 'reward': '0.291', 'reward_std': '0.0555', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.1004', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '20'}\n",
      " 70%|████████████████████████████▋            | 140/200 [27:02<11:27, 11.47s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.522e-05', 'grad_norm': '0.1055', 'learning_rate': '6.316e-06', 'num_tokens': '7.319e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2699', 'rewards/reward_fn/std': '0.1281', 'reward': '0.2699', 'reward_std': '0.07989', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01523', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '20.14'}\n",
      " 70%|████████████████████████████▉            | 141/200 [27:13<11:19, 11.51s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +16.8pts delta=16.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.073e-05', 'grad_norm': '0.203', 'learning_rate': '6.211e-06', 'num_tokens': '7.376e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3562', 'rewards/reward_fn/std': '0.2764', 'reward': '0.3562', 'reward_std': '0.2557', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01075', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '20.29'}\n",
      " 71%|█████████████████████████████            | 142/200 [27:25<11:17, 11.68s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.481e-05', 'grad_norm': '0.1396', 'learning_rate': '6.105e-06', 'num_tokens': '7.426e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.291', 'rewards/reward_fn/std': '0.1208', 'reward': '0.291', 'reward_std': '0.0555', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01481', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '20.43'}\n",
      " 72%|█████████████████████████████▎           | 143/200 [27:37<10:57, 11.54s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '1.74e-05', 'grad_norm': '0.2392', 'learning_rate': '6e-06', 'num_tokens': '7.465e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3686', 'rewards/reward_fn/std': '0.2829', 'reward': '0.3686', 'reward_std': '0.2553', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0174', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '20.57'}\n",
      " 72%|█████████████████████████████▌           | 144/200 [27:47<10:33, 11.31s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +23.0pts delta=22.9[sim] 🎯 25%+50% milestone! | score=0.918\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.184e-05', 'grad_norm': '0.1355', 'learning_rate': '5.895e-06', 'num_tokens': '7.521e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3356', 'rewards/reward_fn/std': '0.2545', 'reward': '0.3356', 'reward_std': '0.1601', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01185', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '20.71'}\n",
      " 72%|█████████████████████████████▋           | 145/200 [27:59<10:26, 11.40s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.395e-05', 'grad_norm': '0.168', 'learning_rate': '5.789e-06', 'num_tokens': '7.577e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4254', 'rewards/reward_fn/std': '0.2612', 'reward': '0.4254', 'reward_std': '0.2437', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01393', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '20.86'}\n",
      " 73%|█████████████████████████████▉           | 146/200 [28:11<10:19, 11.46s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.338e-05', 'grad_norm': '0.215', 'learning_rate': '5.684e-06', 'num_tokens': '7.616e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3856', 'rewards/reward_fn/std': '0.3438', 'reward': '0.3856', 'reward_std': '0.3698', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0134', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '21'}\n",
      " 74%|██████████████████████████████▏          | 147/200 [28:21<09:56, 11.25s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '9.947e-06', 'grad_norm': '0.1525', 'learning_rate': '5.579e-06', 'num_tokens': '7.667e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2858', 'rewards/reward_fn/std': '0.2407', 'reward': '0.2858', 'reward_std': '0.1702', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.009946', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '21.14'}\n",
      " 74%|██████████████████████████████▎          | 148/200 [28:33<09:50, 11.36s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.188e-05', 'grad_norm': '0.1668', 'learning_rate': '5.474e-06', 'num_tokens': '7.719e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.2688', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01189', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '21.29'}\n",
      " 74%|██████████████████████████████▌          | 149/200 [28:45<09:43, 11.44s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +16.8pts delta=16.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.181e-05', 'grad_norm': '0.1907', 'learning_rate': '5.368e-06', 'num_tokens': '7.762e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.456', 'rewards/reward_fn/std': '0.3472', 'reward': '0.456', 'reward_std': '0.3747', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01179', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '21.43'}\n",
      " 75%|██████████████████████████████▊          | 150/200 [28:56<09:25, 11.32s/it]Unsloth: Restored added_tokens_decoder metadata in ./sdea-trained/checkpoint-150/tokenizer_config.json.\n",
      "Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.881e-05', 'grad_norm': '0.2091', 'learning_rate': '5.263e-06', 'num_tokens': '7.826e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01877', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '21.57'}\n",
      " 76%|██████████████████████████████▉          | 151/200 [29:08<09:33, 11.71s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +23.0pts delta=22.9[sim] 🎯 25%+50% milestone! | score=0.918\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.474e-05', 'grad_norm': '0.1915', 'learning_rate': '5.158e-06', 'num_tokens': '7.875e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4047', 'rewards/reward_fn/std': '0.2446', 'reward': '0.4047', 'reward_std': '0.24', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01475', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '21.71'}\n",
      " 76%|███████████████████████████████▏         | 152/200 [29:19<09:13, 11.54s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '2.283e-05', 'grad_norm': '0.1723', 'learning_rate': '5.053e-06', 'num_tokens': '7.935e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3256', 'rewards/reward_fn/std': '0.1305', 'reward': '0.3256', 'reward_std': '0.1247', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02279', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '21.86'}\n",
      " 76%|███████████████████████████████▎         | 153/200 [29:31<09:06, 11.63s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '1.39e-05', 'grad_norm': '0.149', 'learning_rate': '4.947e-06', 'num_tokens': '7.986e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2342', 'rewards/reward_fn/std': '0.09486', 'reward': '0.2342', 'reward_std': '0.06707', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01391', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '22'}\n",
      " 77%|███████████████████████████████▌         | 154/200 [29:43<08:54, 11.62s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.729e-05', 'grad_norm': '0.0001903', 'learning_rate': '4.842e-06', 'num_tokens': '8.037e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2007', 'rewards/reward_fn/std': '0', 'reward': '0.2007', 'reward_std': '0', 'frac_reward_zero_std': '1', 'completion_length': '150', 'kl': '0.01729', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '22.14'}\n",
      " 78%|███████████████████████████████▊         | 155/200 [29:54<08:42, 11.61s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.827e-05', 'grad_norm': '0.1768', 'learning_rate': '4.737e-06', 'num_tokens': '8.097e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.2688', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02826', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '22.29'}\n",
      " 78%|███████████████████████████████▉         | 156/200 [30:06<08:33, 11.67s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.841e-05', 'grad_norm': '0.1218', 'learning_rate': '4.632e-06', 'num_tokens': '8.154e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.291', 'rewards/reward_fn/std': '0.1208', 'reward': '0.291', 'reward_std': '0.0555', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01841', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '22.43'}\n",
      " 78%|████████████████████████████████▏        | 157/200 [30:18<08:20, 11.64s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +15.2pts delta=15.2[hint] 🎯 25% milestone! | score=0.469\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.313e-05', 'grad_norm': '0.184', 'learning_rate': '4.526e-06', 'num_tokens': '8.211e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2688', 'rewards/reward_fn/std': '0.1262', 'reward': '0.2688', 'reward_std': '0.1363', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01308', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '22.57'}\n",
      " 79%|████████████████████████████████▍        | 158/200 [30:30<08:15, 11.80s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '1.121e-05', 'grad_norm': '0.1336', 'learning_rate': '4.421e-06', 'num_tokens': '8.254e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2342', 'rewards/reward_fn/std': '0.09486', 'reward': '0.2342', 'reward_std': '0.06707', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01123', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '22.71'}\n",
      " 80%|████████████████████████████████▌        | 159/200 [30:41<07:54, 11.57s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | INVALID JSON | score=0.001\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.352e-05', 'grad_norm': '0.2387', 'learning_rate': '4.316e-06', 'num_tokens': '8.298e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3101', 'rewards/reward_fn/std': '0.3066', 'reward': '0.3101', 'reward_std': '0.2905', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01355', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '22.86'}\n",
      " 80%|████████████████████████████████▊        | 160/200 [30:52<07:39, 11.50s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.811e-05', 'grad_norm': '0.2159', 'learning_rate': '4.211e-06', 'num_tokens': '8.35e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.2688', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0181', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '23'}\n",
      " 80%|█████████████████████████████████        | 161/200 [31:04<07:29, 11.53s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.309e-05', 'grad_norm': '0.1356', 'learning_rate': '4.105e-06', 'num_tokens': '8.399e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01308', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '23.14'}\n",
      " 81%|█████████████████████████████████▏       | 162/200 [31:15<07:14, 11.43s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.503e-05', 'grad_norm': '0.1358', 'learning_rate': '4e-06', 'num_tokens': '8.45e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01502', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '23.29'}\n",
      " 82%|█████████████████████████████████▍       | 163/200 [31:27<07:04, 11.47s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.773e-05', 'grad_norm': '0.000141', 'learning_rate': '3.895e-06', 'num_tokens': '8.508e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2007', 'rewards/reward_fn/std': '0', 'reward': '0.2007', 'reward_std': '0', 'frac_reward_zero_std': '1', 'completion_length': '150', 'kl': '0.01773', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '23.43'}\n",
      " 82%|█████████████████████████████████▌       | 164/200 [31:38<06:54, 11.50s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '3.047e-05', 'grad_norm': '0.1754', 'learning_rate': '3.789e-06', 'num_tokens': '8.576e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2699', 'rewards/reward_fn/std': '0.1281', 'reward': '0.2699', 'reward_std': '0.1384', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.03043', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '23.57'}\n",
      " 82%|█████████████████████████████████▊       | 165/200 [31:50<06:46, 11.60s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '1.168e-05', 'grad_norm': '0.2194', 'learning_rate': '3.684e-06', 'num_tokens': '8.615e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3686', 'rewards/reward_fn/std': '0.2829', 'reward': '0.3686', 'reward_std': '0.2553', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01168', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '23.71'}\n",
      " 83%|██████████████████████████████████       | 166/200 [32:00<06:15, 11.04s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.096e-05', 'grad_norm': '0.2492', 'learning_rate': '3.579e-06', 'num_tokens': '8.658e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3761', 'rewards/reward_fn/std': '0.2345', 'reward': '0.3761', 'reward_std': '0.2257', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01097', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '23.86'}\n",
      " 84%|██████████████████████████████████▏      | 167/200 [32:11<06:04, 11.05s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.496e-05', 'grad_norm': '0.1766', 'learning_rate': '3.474e-06', 'num_tokens': '8.702e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3005', 'rewards/reward_fn/std': '0.2822', 'reward': '0.3005', 'reward_std': '0.1996', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01496', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '24'}\n",
      " 84%|██████████████████████████████████▍      | 168/200 [32:22<05:53, 11.05s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.547e-05', 'grad_norm': '0.252', 'learning_rate': '3.368e-06', 'num_tokens': '8.753e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2858', 'rewards/reward_fn/std': '0.2407', 'reward': '0.2858', 'reward_std': '0.1702', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01545', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '24.14'}\n",
      " 84%|██████████████████████████████████▋      | 169/200 [32:34<05:47, 11.22s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +16.8pts delta=16.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.276e-05', 'grad_norm': '0.2272', 'learning_rate': '3.263e-06', 'num_tokens': '8.797e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3908', 'rewards/reward_fn/std': '0.2714', 'reward': '0.3908', 'reward_std': '0.2664', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01279', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '24.29'}\n",
      " 85%|██████████████████████████████████▊      | 170/200 [32:45<05:35, 11.18s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.529e-05', 'grad_norm': '0.09915', 'learning_rate': '3.158e-06', 'num_tokens': '8.854e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01528', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '24.43'}\n",
      " 86%|███████████████████████████████████      | 171/200 [32:56<05:27, 11.30s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '9.052e-06', 'grad_norm': '0.138', 'learning_rate': '3.053e-06', 'num_tokens': '8.897e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3005', 'rewards/reward_fn/std': '0.2822', 'reward': '0.3005', 'reward_std': '0.1996', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.009064', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '24.57'}\n",
      " 86%|███████████████████████████████████▎     | 172/200 [33:07<05:14, 11.23s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.688e-05', 'grad_norm': '0.07118', 'learning_rate': '2.947e-06', 'num_tokens': '8.958e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.02688', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '24.71'}\n",
      " 86%|███████████████████████████████████▍     | 173/200 [33:19<05:08, 11.41s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +9.2pts delta=9.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.786e-05', 'grad_norm': '0.2331', 'learning_rate': '2.842e-06', 'num_tokens': '9.01e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3761', 'rewards/reward_fn/std': '0.2345', 'reward': '0.3761', 'reward_std': '0.2257', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01786', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '24.86'}\n",
      " 87%|███████████████████████████████████▋     | 174/200 [33:31<04:58, 11.47s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.867e-05', 'grad_norm': '0.1936', 'learning_rate': '2.737e-06', 'num_tokens': '9.054e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3697', 'rewards/reward_fn/std': '0.2834', 'reward': '0.3697', 'reward_std': '0.2574', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01864', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '25'}\n",
      " 88%|███████████████████████████████████▉     | 175/200 [33:42<04:43, 11.36s/it]Unsloth: Restored added_tokens_decoder metadata in ./sdea-trained/checkpoint-175/tokenizer_config.json.\n",
      "Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.061e-05', 'grad_norm': '0.2398', 'learning_rate': '2.632e-06', 'num_tokens': '9.093e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4349', 'rewards/reward_fn/std': '0.361', 'reward': '0.4349', 'reward_std': '0.3878', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01059', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '25.14'}\n",
      " 88%|████████████████████████████████████     | 176/200 [33:53<04:33, 11.38s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +16.8pts delta=16.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '2.585e-05', 'grad_norm': '0.1177', 'learning_rate': '2.526e-06', 'num_tokens': '9.144e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3216', 'rewards/reward_fn/std': '0.2764', 'reward': '0.3216', 'reward_std': '0.1866', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.02586', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '25.29'}\n",
      " 88%|████████████████████████████████████▎    | 177/200 [34:05<04:23, 11.44s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +70.3pts delta=70.3[sim] 🎯 25%+50% milestone! | score=0.999\n",
      "{'loss': '1.471e-05', 'grad_norm': '0.1616', 'learning_rate': '2.421e-06', 'num_tokens': '9.189e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4307', 'rewards/reward_fn/std': '0.3297', 'reward': '0.4307', 'reward_std': '0.3493', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01475', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '25.43'}\n",
      " 89%|████████████████████████████████████▍    | 178/200 [34:16<04:10, 11.37s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.688e-05', 'grad_norm': '0.1838', 'learning_rate': '2.316e-06', 'num_tokens': '9.249e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2699', 'rewards/reward_fn/std': '0.1281', 'reward': '0.2699', 'reward_std': '0.1384', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02685', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '25.57'}\n",
      " 90%|████████████████████████████████████▋    | 179/200 [34:28<04:01, 11.51s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +9.2pts delta=9.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.937e-05', 'grad_norm': '0.2296', 'learning_rate': '2.211e-06', 'num_tokens': '9.301e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3761', 'rewards/reward_fn/std': '0.2345', 'reward': '0.3761', 'reward_std': '0.2257', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01934', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '25.71'}\n",
      " 90%|████████████████████████████████████▉    | 180/200 [34:40<03:50, 11.54s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.825e-05', 'grad_norm': '0.1742', 'learning_rate': '2.105e-06', 'num_tokens': '9.363e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2699', 'rewards/reward_fn/std': '0.1281', 'reward': '0.2699', 'reward_std': '0.1384', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0282', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '25.86'}\n",
      " 90%|█████████████████████████████████████    | 181/200 [34:52<03:41, 11.68s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +23.0pts delta=22.9[sim] 🎯 25%+50% milestone! | score=0.918\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '8.345e-06', 'grad_norm': '0.1774', 'learning_rate': '2e-06', 'num_tokens': '9.412e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4699', 'rewards/reward_fn/std': '0.3235', 'reward': '0.4699', 'reward_std': '0.3483', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.00833', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '26'}\n",
      " 91%|█████████████████████████████████████▎   | 182/200 [35:03<03:26, 11.48s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +16.8pts delta=16.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '2.48e-05', 'grad_norm': '0.1375', 'learning_rate': '1.895e-06', 'num_tokens': '9.466e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3562', 'rewards/reward_fn/std': '0.2764', 'reward': '0.3562', 'reward_std': '0.2557', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02481', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '26.14'}\n",
      " 92%|█████████████████████████████████████▌   | 183/200 [35:14<03:17, 11.59s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.217e-05', 'grad_norm': '0.09928', 'learning_rate': '1.789e-06', 'num_tokens': '9.523e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.1882', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01215', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '26.29'}\n",
      " 92%|█████████████████████████████████████▋   | 184/200 [35:26<03:05, 11.59s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.149e-05', 'grad_norm': '0.1531', 'learning_rate': '1.684e-06', 'num_tokens': '9.574e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.1882', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.02147', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '26.43'}\n",
      " 92%|█████████████████████████████████████▉   | 185/200 [35:38<02:53, 11.59s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.396e-05', 'grad_norm': '0.1701', 'learning_rate': '1.579e-06', 'num_tokens': '9.618e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.2688', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02396', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '26.57'}\n",
      " 93%|██████████████████████████████████████▏  | 186/200 [35:49<02:40, 11.44s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +15.2pts delta=15.2[hint] 🎯 25% milestone! | score=0.469\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.094e-05', 'grad_norm': '0.1906', 'learning_rate': '1.474e-06', 'num_tokens': '9.661e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2342', 'rewards/reward_fn/std': '0.09486', 'reward': '0.2342', 'reward_std': '0.06707', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01096', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '26.71'}\n",
      " 94%|██████████████████████████████████████▎  | 187/200 [36:00<02:27, 11.34s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '1.378e-05', 'grad_norm': '0.2231', 'learning_rate': '1.368e-06', 'num_tokens': '9.706e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3034', 'rewards/reward_fn/std': '0.1418', 'reward': '0.3034', 'reward_std': '0.147', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0138', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '26.86'}\n",
      " 94%|██████████████████████████████████████▌  | 188/200 [36:11<02:15, 11.27s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.259e-05', 'grad_norm': '0.2222', 'learning_rate': '1.263e-06', 'num_tokens': '9.775e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2699', 'rewards/reward_fn/std': '0.1281', 'reward': '0.2699', 'reward_std': '0.1384', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.02255', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '27'}\n",
      " 94%|██████████████████████████████████████▋  | 189/200 [36:23<02:06, 11.49s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +10.2pts delta=10.2[sim] 🎯 25%+50% milestone! | score=0.882\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '1.556e-05', 'grad_norm': '0.1884', 'learning_rate': '1.158e-06', 'num_tokens': '9.814e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3193', 'rewards/reward_fn/std': '0.2458', 'reward': '0.3193', 'reward_std': '0.2373', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01556', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '27.14'}\n",
      " 95%|██████████████████████████████████████▉  | 190/200 [36:34<01:52, 11.27s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +70.3pts delta=70.3[sim] 🎯 25%+50% milestone! | score=0.999\n",
      "{'loss': '1.533e-05', 'grad_norm': '0.1577', 'learning_rate': '1.053e-06', 'num_tokens': '9.865e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.4148', 'rewards/reward_fn/std': '0.2692', 'reward': '0.4148', 'reward_std': '0.259', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01539', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '27.29'}\n",
      " 96%|███████████████████████████████████████▏ | 191/200 [36:45<01:41, 11.25s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '4.247e-05', 'grad_norm': '0.1724', 'learning_rate': '9.474e-07', 'num_tokens': '9.926e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3351', 'rewards/reward_fn/std': '0.2852', 'reward': '0.3351', 'reward_std': '0.2688', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.04248', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '27.43'}\n",
      " 96%|███████████████████████████████████████▎ | 192/200 [36:57<01:31, 11.47s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '2.546e-05', 'grad_norm': '0.2429', 'learning_rate': '8.421e-07', 'num_tokens': '9.994e+05', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2353', 'rewards/reward_fn/std': '0.09785', 'reward': '0.2353', 'reward_std': '0.06919', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.02546', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '27.57'}\n",
      " 96%|███████████████████████████████████████▌ | 193/200 [37:09<01:21, 11.58s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.851e-05', 'grad_norm': '0.09277', 'learning_rate': '7.368e-07', 'num_tokens': '1.005e+06', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.291', 'rewards/reward_fn/std': '0.1208', 'reward': '0.291', 'reward_std': '0.0555', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.0185', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '27.71'}\n",
      " 97%|███████████████████████████████████████▊ | 194/200 [37:20<01:09, 11.60s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +2.7pts delta=2.7[hint]  | score=0.201\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +44.8pts delta=44.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.48e-05', 'grad_norm': '0.1336', 'learning_rate': '6.316e-07', 'num_tokens': '1.01e+06', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3005', 'rewards/reward_fn/std': '0.2822', 'reward': '0.3005', 'reward_std': '0.1996', 'frac_reward_zero_std': '0.5', 'completion_length': '150', 'kl': '0.01482', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '27.86'}\n",
      " 98%|███████████████████████████████████████▉ | 195/200 [37:32<00:57, 11.60s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +7.4pts delta=7.4[hint]  | score=0.201\n",
      "{'loss': '1.386e-05', 'grad_norm': '0.2294', 'learning_rate': '5.263e-07', 'num_tokens': '1.014e+06', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.2699', 'rewards/reward_fn/std': '0.1281', 'reward': '0.2699', 'reward_std': '0.1384', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0138', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '28'}\n",
      " 98%|████████████████████████████████████████▏| 196/200 [37:43<00:45, 11.44s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +26.8pts delta=26.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +1.7pts delta=1.7[hint]  | score=0.201\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +3.2pts delta=3.2[hint]  | score=0.201\n",
      "  [REWARD] medium_s003 | action=create_index | +24.7pts delta=24.7[hint] 🎯 25% milestone! | score=0.469\n",
      "{'loss': '1.137e-05', 'grad_norm': '0.2076', 'learning_rate': '4.211e-07', 'num_tokens': '1.018e+06', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3686', 'rewards/reward_fn/std': '0.2829', 'reward': '0.3686', 'reward_std': '0.2553', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01134', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '28.14'}\n",
      " 98%|████████████████████████████████████████▍| 197/200 [37:53<00:32, 10.94s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +1.2pts delta=1.2[hint]  | score=0.201\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +16.0pts delta=16.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.9e-05', 'grad_norm': '0.2019', 'learning_rate': '3.158e-07', 'num_tokens': '1.024e+06', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3256', 'rewards/reward_fn/std': '0.1305', 'reward': '0.3256', 'reward_std': '0.1247', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01901', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '28.29'}\n",
      " 99%|████████████████████████████████████████▌| 198/200 [38:04<00:22, 11.14s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +4.1pts delta=4.1[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s005 | action=create_index | +6.0pts delta=6.0[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +5.4pts delta=5.4[sim]  | score=0.236\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.889e-05', 'grad_norm': '0.2533', 'learning_rate': '2.105e-07', 'num_tokens': '1.029e+06', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.3195', 'rewards/reward_fn/std': '0.1338', 'reward': '0.3195', 'reward_std': '0.1416', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.01889', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '28.43'}\n",
      "100%|████████████████████████████████████████▊| 199/200 [38:16<00:11, 11.13s/it]Both `max_new_tokens` (=150) and `max_length`(=32768) seem to have been set. `max_new_tokens` will take precedence. Please refer to the documentation for more information. (https://huggingface.co/docs/transformers/main/en/main_classes/text_generation)\n",
      "  [REWARD] easy_s001 | action=create_index | +1.6pts delta=1.6[hint]  | score=0.201\n",
      "  [REWARD] easy_s002 | action=create_index | +9.6pts delta=9.6[hint] 🎯 25% milestone! | score=0.477\n",
      "  [REWARD] easy_s003 | action=create_index | +1.4pts delta=1.4[hint]  | score=0.201\n",
      "  [REWARD] easy_s004 | action=create_index | +11.5pts delta=11.5[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] easy_s005 | action=create_index | +16.8pts delta=16.8[sim] 🎯 25%+50%+75% milestone! | score=0.999\n",
      "  [REWARD] medium_s001 | action=create_index | +4.6pts delta=4.6[hint]  | score=0.201\n",
      "  [REWARD] medium_s002 | action=create_index | +8.4pts delta=8.4[hint]  | score=0.285\n",
      "  [REWARD] medium_s003 | action=create_index | +19.8pts delta=19.8[hint]  | score=0.285\n",
      "{'loss': '1.189e-05', 'grad_norm': '0.152', 'learning_rate': '1.053e-07', 'num_tokens': '1.032e+06', 'completions/mean_length': '150', 'completions/min_length': '150', 'completions/max_length': '150', 'completions/clipped_ratio': '1', 'completions/mean_terminated_length': '0', 'completions/min_terminated_length': '0', 'completions/max_terminated_length': '0', 'rewards/reward_fn/mean': '0.456', 'rewards/reward_fn/std': '0.3472', 'reward': '0.456', 'reward_std': '0.3747', 'frac_reward_zero_std': '0', 'completion_length': '150', 'kl': '0.0119', 'clip_ratio/low_mean': '0', 'clip_ratio/low_min': '0', 'clip_ratio/high_mean': '0', 'clip_ratio/high_max': '0', 'clip_ratio/region_mean': '0', 'epoch': '28.57'}\n",
      "100%|█████████████████████████████████████████| 200/200 [38:26<00:00, 11.01s/it]Unsloth: Restored added_tokens_decoder metadata in ./sdea-trained/checkpoint-200/tokenizer_config.json.\n",
      "{'train_runtime': '2307', 'train_samples_per_second': '0.693', 'train_steps_per_second': '0.087', 'train_loss': '1.425e-05', 'epoch': '28.57'}\n",
      "100%|█████████████████████████████████████████| 200/200 [38:27<00:00, 11.54s/it]\n",
      "\n",
      "✅ Training complete!\n",
      "Unsloth: Restored added_tokens_decoder metadata in ./sdea-trained/final/tokenizer_config.json.\n",
      "✅ Saved to ./sdea-trained/final\n",
      "✅ Logs saved to ./sdea-trained/training_logs.json\n",
      "✅ loss_curve.png saved\n",
      "   Loss:   4.92e-07 → 1.19e-05\n",
      "   Reward: 0.235 → 0.456\n",
      "\n",
      "==================================================\n",
      "NEXT:\n",
      "  python training/evaluate_agent.py\n",
      "  git add loss_curve.png reward_curve.png\n",
      "  git commit -m 'Real GRPO training evidence'\n",
      "  git push origin main\n",
      "==================================================\n"
     ]
    }
   ],
   "source": [
    "!python training/train_agent.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "bd4e3283-4211-471f-aec8-efb8d424ef2d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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tX/+jatasKkk6fPioatVqqTfeGKUmTeonGAgqVapYugW3U1uPHp3Utevz5p+vX7+hVq26KTx8iwYOHKU1axY4rnKPka5dB+jy5at67bWXNWnSe5JMo4Dbt++txYtX6MMPp2jUKNu+dJGSZ6S3t5c2bvxJNWpUlrv7f3/6iI2N1bvvjtVHH32mPn2GaOfOlQkec+jQfgoJSXiEbUYyc+Y8LV68QsWLF9GGDYvNgcOFC5epXTvTe86ff4ZbtIGt1q7doDlzFqhXr86aNu27ZLd/8N5KzpgxEzRz5ny1aNFIs2dPVI4c2c15ERHXbA5Yxzt//h9NmTJLLVo0Utmypeza11YpeY9/0BtvjFJkZJQ6d26rb78NTXCbDz6YIi8vL+3YsUKFChXQsWMnVbp0PX3wwRQtXfrfqHfDMNSv3zA98URJvfpq10SP6ePjowEDeujttz/UihXr1LRpg5Q1AAAAAB57TFUNAAAA/Ou99ybqyJHjmjr1I3l4eNi9/+nTZ7V06Rq5u7vryy8/Mv9BWZJat26qDh1a6fLlq5o5c77FfvPnT1W/ft2t/tDcvPlT6t69gyRp3ryf7D8hO02YME2S9O67A8xBY0mqWbOq+vR5UdeuXdeMGfNsKuvvv49p+/Y98vb21nPPtUiT+qZE0aJB+vrrT9S794uqXLm8PDwe7ru0NWtW1eeff6hu3TqobNlScnVNvov15ZdzJEmDBvWxGImXN28eTZgwUpI0btwXD1UvW0yaNEOxsbHq0+dFc9BYkkqUKKphw17XvXv3NGnS12leD0fz9c2msWOHSZLCw7faPY0yrG3fvkebNu1Q7ty5NG7cu+b0+Gejh4eHJk+eqXv37tlUXkqeke7u7qpdu7pVwNTNzU3vvfeWvL29tWvXPl2/fiMFZ5hxxD+3x40bZjHatG3b5mrZsrGOHDmun3+2f8mD27dvq3fvISpTpoQGDeqTavWNd+bMOX344WcKDMyvH36YahE0lqTs2f0s3odsMXPmfMXExOill56zeZ/4abZtmaI9pe/x91u9OlzffbdQw4a9riJFAhPdbu/eA6pXL1iFChWQJBUpUkghITW1d+8Bi+1mz/5BW7fu0mef/S/ZLwe88EIbubi4mN+DAAAAgIQQOAYAAMBDO336rHr3fkuFClUzr/fXps3L2rFjb4Lb//HHX+rcuZ+KFAmWt3dh+fuXVcWKT2nAgBE6f/4fi203b96h1q27mcsOCKig6tWbaejQ/+nWrchUO4f9+//Uxx9/qe7dO9g9NWa83bv3S5IKFw40/7H3fvXrm0av2fNH/AoVTNPmnjv3T4L5f/75t7p2HaCCBavIyytIefKUV4cOfXTgwCG76n779m2tW7dJktSuXXOr/HbtnpEkLVmy2qbyvvtuoSSpRYtG8vXNZlddbPHnn3/rxo2bqV5ueti1y3SdhITUtMqrV6+mXF1dtXfvAZ06Zb0G6+nTZ9Wv3zsqWrSmvL0LK0eOMnrmmZcSXYM6KfHrGCf8+zal2fr7ftQ98URJSaYRsRER163ybb3P4tdl7tp1gEV6XFyccuQoIxeXfHr33bEWedev35C7e0GVLfvf1N+GYWjevMXq0KGPSpSoo8yZiypr1uKqXr2ZvvhituLi4qzqGB8Amz37B23fvkfPPPOScuZ8Qi4u+SzWXp05c54qVnxKPj5FFBBQQV27DtCFCxftbrOkxF9bLVo0spqOOk8ef9WtW0MREde0ceP2hz5Wcs/IhLi4uMjNzVUuLi7y9LT/S0JpYdu23Xbvc/z4Kf3559/y8fFW8+ZPWeXb+9y+3+jRE3Ts2ElNnTo2RV+kSs6cOT/qzp076tGjk3x8fB66PMMwNGPGPGXNmkXNmzdMhRpae9j3+KioKPXpM1SlSxfX4MF9kzxWRMQ1Zc/ua5GWPbuvIiKumX++fv2Ghg79QJ06PasnnwxOtv4FC+ZXnTrVtXz5Op07dyHZ7QEAAOCcCBwDAADgoezf/6cqV35a06Z9Jx8fb7Vp01TFixfW4sUrVKtWS/344xKL7Xft2qdq1Zpp7txFypo1i1q1aqzg4Mq6e9c0uvHQoaPmbZcs+VV16z6rX375VXnz5lGbNk1VqVJZXb16TWPHfm41jWVISFtz4MQecXFx6tXrLfn5ZbMYHWevyMgoSbL6Y2+8nDlzSJJ+//2gzWUeO3ZSkhJca/Onn1aoUqXGmjNngXLlyqGWLRurcOFALViwRNWrN9Nvv221+TiHDh1VTEyM/P1zqkCBfFb5lSuXkyTt2/enTeXNnWtaQ7Fz5zY218FWJ0+eUb16bdSkSSfdvHkr1ctPa/9dJ35WeZ6ensqSJbMk6+tky5adqlChkT7/fLY8PNzVvHlDlS1bUqtWhenJJ9vohx9+trkO165d16lTZyVJlSqVs8ovWDC/cuXKoZMnzyQYoP/nn0saOfJj9eo1WIMHj1Fo6FLduXPH5uNnNPHXkaurq3LmtBz5aM99FhxcWV5eXlajF3///YA54PNg3m+/bVVsbKzFFwliYmLUqdOrWrNmgwIC/NWiRSMFB1fWgQOH9Oqr76h798TXb/3tt62qU6e1Tpw4rcaNn9STTwabR8IPHfo/vfzymzp48G89+WQNPflksFasWKcaNZrr6tWIBMubPfsHubjkU0iI7VPOx1+78c+NB1WuXFaStG+f7c/CxCT1jEyIYRgaO/ZzRUZGqX792okGLRctWq7+/YfplVfe1scff6G//vr7oeuamC++mK3g4Gf0ySdT7drv999No0/Lli2VYHD3v+e2fe28b99BffLJV+rW7Xm71qhft26TBgwYoT59huj99ydq1659SW4rSbVqVdX58/9o/Pgv1afPEA0Z8r5Wrlyf6Nq/iTl48LCOHz+l4ODK8vb2tmtfWz3se/yoUZ+Yg/Genp5JHiswML8OHz5mkXbo0FEFBuY3/zx8+Djdvh2tjz8ebvM5hITUVGxsrFauXG/zPgAAAHAurHEMAACAFDMMQy+80E+XL1/VW2+9oo8+GiYXFxdJpvUV27fvre7dB6pOnerKmzePJGny5BmKjo7W+PEj9OabltNf/vXX3xajU8ePn6q4uDiFhk5X27aWoyJ37NhrFeBJqc8/n6WtW3dpzpxJVtNl2sPfP6ckU2AzIcePn5IkXb0aoVu3Is0BwsRcu3Zd33xjWv+wVaunLfJOnDitzp37y8PDXUuXztFTTz1pzlu5cr1atuyqzp376ciRzcn+gVqSOYhYoEDeBPMzZ84kPz/TaKebN28luX7jli07dfToCeXMmT1N1lEsWDCfmjVrqDlzFqhZs85asWJusm2Zkfj759S5cxd08uQZlS5d3CLv6tUIc6D2/uvoxo2batu2p27cuKnvvvtML7zwX0B+587f1bhxR/XoMUgNGtQxX4dJif99Z8/uZzHd6v0KFMiry5ev6uTJMypXrrRF3l9/HdGYMZ9apAUG5tePP05T9eqVkj1+RhMfRGnQoLbF/WLvfebt7a0aNSrpt9+26sSJ0woKKihJCgvbIsk0snnHjt8VFRWlTJkyWeTdv56uu7u7Fi+eoebNn7IICF66dEXNmnXWnDkL1L17hwRHGc6a9YPGjh2mt9561SJ969ZdGjfuC/n6ZtP69T+avzBw61akWrXqlqqjy5N7nsR/OeXkybMPdZyknpH3GzLkff3zz2XduHFT+/b9qaNHT6h06eL6+uvxie4zZcrMB8r4n/r2fUmTJr2XovWCk9K0aQMFBubXoEFj5ObmpgEDetq0X/LtbEq3p53j4uLUo8egFH2R6sH1eocPH6e2bZtr9uyJVs/ogwcPm/9t27anxZTh48Z9oZCQWlq8eIb8/BIO0j5ow4ZtkqRq1SraVWd7PMx7/N69f+jTT6erW7fnbRod3KxZQ3366TRNnz5Xzz/fUt9/v1h79x7Qm2/2lmT60t4XX8zRRx+9o3z5Amw+h/jnc3j4VnXv3tHm/QAAAOA8GHEMAACAFAsL26z9+/9UYGB+vf/+EHPQWDKtr9i6dRPduhVpsd7fpUtXJElPPVXXqrxSpYqbA8zJbVutWkWr4GVgYH6VLFnUrqmRz5w5p2HDxiokpJZd6yImpHr1SvLy8tI//1yyGs1jGIZmz15g/tmWkbJ9+gzRpUtXFBxcRc8+29Qib+LE6YqMjNKHH75tEcySpCZN6qtv35d0+vQ5LVu21qa6x0/7nSlT4lOGxgcYk6v7t9+apqnu0KFVmkxx6urqqpkzJ+ill57Txo3b1bz5i4qKikr146SVJ580jeBLaGT8/ffKzZuRFunnz/+jAQN6WASNJalq1QoaPnyAbt2KNE8RnpyU/r69vDzVt28XhYUt1D//7NONG4e1ZcsSNWvWUKdOndXTT3dKNKiSEV2+fEVz5y7SoEHvyd8/pyZNes8iPyX3WfzI4ftHFoeFbVbWrFn0xhs9defOHW3evNMiTzJNUx7P3d1drVs3tbp//P1z6sMP35aU+HS45cqV1uDBr1ilf/nlNzIMQ6+//rLFKPMsWTJrypT3LZ7f9/P1zaaSJYtajHRMzq1bpvsxsesrc2ZT+sPOGJDUM/J+Cxcu15w5C7R48QodPXpC5cuX0Q8/TFXhwtZrzFaqVFZTp47V4cMbFRV1VMeObdXnn38gPz9fffHFHA0e/F4CR3g4hQsHKixsoQID8+uNN0bqs89mJr+TbGln257Z95syZaZ27Nirjz8ebh5Bm5xixQpr/PgROnAgTLduHdHp0zs1d+5nyp8/rxYuXKYXX+xvtU/8lPADB45W+fKltXv3Kt24cVhr1vzwb3tsVs+eg22ud/xsGCVLFrV5H3ul9D0+NjZWPXsOlq9vVptHBw8d2k8FCuRVr16D5etbUn37DlVgYH4NHdpPktSv3zCVKFFEr7/ew7zP3bt3dffu3STLLVWqmCRZrZUMAAAAxGPEMQAAAFIsfoRP+/YtEgwQvvhiWy1atNy8nSRVqVJeK1as06uvvqP33x+iOnWqJzp6q0qV8vrzz7/14ov9NXz4G6pSpbx5ytWEfPPNZLvP4dVX31FMzB19+eWHdu/7IF/fbHrllS769NNp6tLldU2dOlYNGtTWhQsXNWLEx/rzz/+mOk3qPCRp7NjP9MMPvyhHjuyaO/czq6DOr7+GS5LatGmW4P5169bQ5MkztH37niQDKqnt7t27WrDgF0nSiy+2s2vfH374WSNHJj4C8EFxcaapTH/7bauef76Pliz5xq7jOcqgQX0VGrpMP/zwiwID86tfv27KlMlHCxcu14gRH8vd3V337t2Tq+t/v3Nbft+StH37njSte968efTFF5b3SnBwFS1b9q1eeOFVff/9Yn3wwWR99dW4NK3Hw+jW7Q116/aGRVqhQgW0adPPyp/fcuRmSu4zUwD4U4WFbVHXrs8rLi5OGzZsV5061dWwoelLMGFhW/TUU0/q+vUb2rv3gMqUKZHgSPG9e//Qr7+G6+TJM4qKui3D+C8g9fffx6y2l6RnnnkqwSBw/HO4Q4fWVnllypRQhQplEgwmPfts03R9htgquWfk/Y4cMQXnL1++ol279mvYsI9UpUoTTZ/+sbp0aW+x7f2BOMkU1H3lla6qV6+mKld+Wp99NksDB/ZSwYLJB9I7dOhjV4AuOjpGktS//7sKCMhtXqM4vZw6dUbvvjtW9erVVNeuz9u8X+fOltOYZ86cSZ06tVH9+rVVrlwD/fTTSm3dukvBwVXM28Sv0509u69WrJhrDnI3bFhXv/wyW+XLN1Ro6FIdPnxUJUokHwy+ePGyubyEXL58RYMGWQf949f//uijzywCv/Fmz55o/n9K3+MnTfpaO3f+rpkzJ9gcjM+dO5f27PlV06d/r+PHT6lo0ULq0aOTcubMoe+/X6TfftuqNWt+kIeHh44fP6Xevd/S2rUbJUkNG9bR9OnjE1yHOUcOP0n/fTEPAAAAeBCBYwAAAKTYuXP/SJJ5OtYHxaefPXvBnDZ4cF9t3LhdYWGbVb9+O2XJklk1a1ZR8+ZPqWvX9hajhT/4YKj27/9TS5as1pIlq5U9u5/q1Kmmli0bq3Pntg+9juHChcv0yy+/avjwASpVqnjyO9jgww/f1unT5xQaulRt2rxsTvf09NSkSWP06qvvSJL8/BIfFf3ddwv19tsfKnPmTFq27BsVKVLIapsTJ05LkvLnr5xkfeLXgf7rr7/10UefW+UPHfqqSpUqbp5SMyrqdqJlxa/vmNQ01StWrNOVKxEqXryIatRIum4Pioi4brHGtT0uX054fdaMqEqV8po161P17DlYH3/8pT7++EtznmlqYnf99NNKizWQ43/ftWu3SrLs+N93YkGSHj06qk6dGqn2+77fO++8pu+/X6xVq8Js2t5RateupmLFCisuLk5nz15QePgWnTx5Rl26vK5Vq+bJzc3NvK2995kk1axZxWKd4/j1jevXr6WgoIIqVKiAOe+337YqLi7OYn1jSbpz5466dh2gefN+SvSY949Iv19iI4Pjn9eFCiWcHxRUMNVGIWbJYgoCJnZ9RUaa0m29th5kyzMyIbly5dTTT4coOLiyypVroL59h6pBg9o2BYGfeKKkWrZsrNDQpVq7dqNNgdUTJ86k+Jl25Uryz7Tk29m+e/jVV9/RnTt3NXXqRzbWMml58+ZRt27Pa/z4qVq5cr1F4DhLlsyKiLim5557xmq6/LJlS6latYravn2Pfvttq02B4/iprhM711u3ojRnjnVgOF5iz637A8eS/e/xJ0+e0YgRH+vJJ4PtCsZLpuv17bctR2vfvHlLgwe/r3btnlHDhnUVFxenNm1e1tmzFzRjxidycXHR4MHvqW3bHtqxY4XVFyqyZcsqyTTNOwAAAJAQAscAAABIMwmNAMuWLavWrftRmzZt15IlqxUWtkXr1m3S6tW/6cMPp2jDhsUqXryIJKlgwfzauXOl1q3bqKVL1yg8fKs5iDxu3JfasuUXm0fvJCR+Tc/Vqzfot9+2WeTFB1D6939Xvr7Z1LVre5v+6Ovl5aUff5ymDRu2aeXK9bp06YoKFsynDh1amdujWLHC8vLySnD/pUtXq1u3N+Th4aFFi762+EP7/eJH2z44Wu5BNWqY1jO8cOFSgn8079q1vUqVKm4ONp05cz7BciIjo3Tt2nVlz+6XZBDiu+8WSZI6d26T6DaJ6dPnJfXp85LN2//vf5P07rtjVaJEES1a9LXdx3Okzp3bqn79WlqwYIkOHz4mb28vNWxYR82bP6W6dVtLkp54ooR5+/jRee3aWQdZ7leqlCnAkliQJCSkpurUqWH+fUdEXFNkZFSCZcZfCwmNWktI8eKFJUnnz1+0aXtH6dGjk8W9fPDgYdWr10Zr127Up59OOBqe1QAAEx1JREFU06BBfc159t5nkuTj46Pq1Stqw4ZtOnHitNUaxiEhtTRv3k+Kiooy590/TbUkTZjwlebN+0nlypXWuHHvqnLlcsqe3VceHh46fPioSpasK8MwEqyLt3fCz5b0FBiYX3v2/JHo8+TMmXOSEg9iJ8XWZ2RSfH2zqUWLRvriizlavfo3m9d6tfca37p1qc11unbtuho16qCdO39X//7d1bv3i8nuk9xz+7972LZ2Xrp0jfz8fNWnz1CL9PiR0GfPXlBIiGl08fz5XyogIHeyZca/nz/YZoUK5VdExLUkvnhWQNu379HFi7aNjI3/0lli03IHBRWUYZyzSh81arxGj56g9etDLdYZT4y97/Hr129SZGSULl68rPr1LWfhiP9iyowZ87RmzQZVrPiEJk4ck+Txx4yZoGvXrmvChJGSpDVrftPevQc0e/ZE83PKMAx16/aG1q7dYDXFfnyA3da1owEAAOB8CBwDAAAgxfLlM61HnNiapv+N1guwSHdxcVGdOjVUp45pet2LFy9rwIARmjfvJw0bNlYLFnxl3tbd3V2NG4eoceMQ87G6dx+odes2auzYzzVunG3rBSZl69ZdiebFB5AfHBGYnLp1a5inD473zTc/JllWePgWPfdcbxmGoe+//9x8zgkpUCCvjh49oU8+GWFT8DwkpFaCfzSPV7JkUXl5eenSpSs6e/a81ZS9u3fvlySVL1860TJu3LhpDsY/OHVpavvwwyl6992xKlassNat+9FibexHRf78efXGG70s0m7fvq29ew8oa9Ysqlz5v3VoCxTIq0OHjmro0H6qUqV8smUnFiSJ5+fnq8DA/Dp16qz27NlvvhfjnT59VpcvX1WhQgXMI9SSE79maVKB7YyoTJkSmjz5PXXq9Ko++GCKevZ8wRyEsvc+i1evXk1t2LBNYWGbFRa2WdmyZTX/PkNCamrOnAXavHmneeTxgwGrxYtXSpLmzftCTzxR0iLv2LFTKTrPvHlz68SJ0zp58qxKl7aeYSE116auUKGMfv55lfm58aDdu03TA5cvX8aucu15RiYnVy7T79OeKXv/u8YTXxs8Ja5fv6HGjTtq587f1bdvF02e/L5N+1Wo8IQk6Y8//tLdu3etloz477lteztfu3Zd4eFbEsyLjo4258UHk5MTEXFNkvVzoVKlstq794C5TR909appv/hR1cnJnTuXxX5pzd73+L/+OqK//jqSYFknTpw2f15Kyl9//a1Jk2Zo1Kg3zaPk48usVq2iebvq1U1fZDl48LBV4Di+vROaGh8AAACQpKQXVgMAAACSEP9H0x9/XKrY2Fir/PjRpw/+cfVBuXPn0qhRb0oy/QE8KYUKFdCQIa/8u+0hu+t8v9mzJ8owziX4ih8BuGHDYhnGOY0aNeihjmUYhj7/fLYkqWfPF6zyd+/ep5YtuyomJkZffz1ebds2T7K8Ro1MfwxevHjFQ9Urno+Pjxo0qC3J9Pt8UGioKa1Fi0aJlhEaulTR0dGqXbuazVPHpsTx46c0ZsynKlKkkNatW2AV5H6UzZw5X5GRUXrxxbby8fkvOJXav2/JNC22JIWGLrPKi09L6vf9oIULTftUrlw2FWqXvjp0aK2KFZ9QRMQ1830qpbzd4wNH69Zt0oYN21W3bg3zFNjxQeKff16lvXsPqHTp4uagV7z44E6BAtbXdvwa4vaKfw4ntP9ff/2datNUS/9dW0uWrFZMjGWA8Z9/LmnDhm3Knt1PtWtXs7lMe5+RyQkP3ypJKlo0yKbtY2JitGzZGkmy+FJHavjiiznasWOvevZ8QZ9//oHN+xUuHKjSpYvr9u1oc93uZ8tz+36JvR8eP26akaNo0SBzWmIjhS3LM8xfgniwzVq2bCxJCQapb92KNH+5oFIl29q6QgVTcDylU4M/rMTe47t2fT7Rdh05cqAk6b333pJhnFNY2MIkj9G//7sKCiqoQYP6WOXdP115/BTl96+zHC9+HeaKFZ+w7wQBAADgNAgcAwAAIMVCQmqpXLnSOnHitEaM+Nhi6tTFi1do0aLlypIls7p372BOnzr1Gx0/bj1ibvnydZKkggXzmdM+/XSaLlywnhI0oW0l6aWXXlOpUnVTNbiWkLNnz6tUqboqVaquVd6pU2d08eJli7Tbt2+rV6/B2r59j7p2bW8eDRTv0KEjatLkBd24cVOTJo2xaUrsN9/sLR8fbw0a9J4WLVpulR8TE6PQ0KXmKWFtMXCgafTr++9P1N9/HzOnb9myU1999Z38/Hz18suJT+ka/0WBF19sl+g2qaFw4UAtWTJb69b9aNPapKkh/vd99mzCU8Laa+fO363Sfv55pd56633lypVDo0dbflGhd+8XlTt3Lo0b94WmTfvOPHV1vHv37mnVqrBkv3hxv9dff1lubm6aOvVbi1H3f/99TP/73yS5u7vr9dd7WOwzffpc/fXX31ZlLVq0XEOHmgJer77azeY6ZBQuLi7mL69MnDhdUVGmwEtK77NatarK09NTP/64VBER1yxGIMavc/z11/MUFxdnNU21JJUoYZred+rUbyzSQ0OX6ptvQlN0jn36vPjv+X2t33//L0gcGRml/v3fTXTq68WLV6hUqbp66aXXbD5W9eqVVLt2NV28eFlDhvzPnH7v3j298srbunv3rl57rbvVCNnEnuEpeUYuW7ZGmzfvsEqPiorSsGEfKTx8iwICcqtJk/rmvL/++lvffhtqFey+dOmKOnToq9Onz6lChTKqXbu6Te1gqyFDXtXs2RP11VfjElziISnxz+233vqfxXvPokXL9csvv6pYscJq1eppi31S8jtNzKVLV/T557Ospoi+dStSffsO1bZtuxUQkFtt2jS1yG/RorFKly6uzZt36osvZpvTY2NjNXDgKF29GqGyZUupTh3b2jr+ixE7dux9mNNJVkre41NDaOhSrVmzQZMmjZGnp6c5PX5GgrlzF5nT4v//4GwFkrR9+15JUr16waleRwAAADwemKoaAAAAiQoOfibRvB49OqpHjxc0d+5nql+/nT74YLIWL16hihWf0KlTZ7Vp0w65u7trxoxPLKYRnjr1G/XtO1RlypRQ6dLF5e7upr/+OqLffz8ob29vjRjxhnnb0aMnaNCgMapQoYyKFy8sw5B+//2ADh8+phw5sluNujl16qwOHTpqXsMvrdy9ey/RUU3r1m1Sz56DVbVqBQUG5tPt29HatGmnrl6N0NNPh+jLLz+y2qdDh766dOmK/P1zateu/eradYDVNqVKFdXQof3NPxcrVljz5n2hTp1eVdu2PVSsWGGVLl1MmTNn0tmzF7R7935FRkZpz55fVaBAPqvyEvLUU0/q9dd7aNKkr1WxYiM1avSk7ty5q9Wrf5NhGJo1a0Ki6yKeOXNO4eFb5OnpqfbtW9h0vIfx4PSb9nj22e7m9TbPnbsgSfr663lauTJMkmlK38WLZ1rsE//7vnv3nlV5998n8V+KeO+9iZo69VtJppF2X3zxocU+1ao1VdGiQebf2R9/HNKBA4eUM2d2rVgxV7lyWU4j6ufnq59/nqUWLbqod++39P77E1W2bCllz+6rCxcuaffu/bp27boWL56hsmVL2dQOJUsW08cfD9fAgaNUt+6zatToSXl6eujXX8N1+3a0Jk9+T8WKFbbYZ+7cRerVa7DKly+jEiWKKC4uTgcPHjZPlzp4cF89+2zTBI6W8bVq1USVK5fT7t37NX3693r99R4pvs98fHxUrVoFbdpkClw+OBV1SEgt8xrUCU1r+9Zbr2jlyvUaOvQD/fjjUpUoUUR//31cO3f+rkGD+mj8+Kl2n1+tWtXM+1ar1kwNGtSWr29WhYdvlZeXp1q0aGSeav5+16/f0KFDR21az/Z+s2Z9qpo1W2jSpK+1bt0mlSlTXDt2/K5jx06qVq2qevvt/lb7JPYMT8kzcseOvRo9eoLy58+rihWfkK9vVl24cEl79x7Q1asR8vXNpgULvlKWLJnN+1y4cEkvvfSaXn99hKpWLS9//5w6d+4f7dq1Tzdv3lKBAnm1YMFXdgd3k+Pq6prsOtqJ6d69o5YvX/dvMPhJNWxYR5cvX1V4+Bb5+Hjru++myN3d8k8/Kf2dJiQyMkr9+g3T0KEfqFq1isqbN7cuXbqi3bv368qVCPn5+So0dJoyZbKcctrNzU3ff/+56tVrq1dffUfTpn2nYsUKa8+eP3Ts2EnlzJld33//uc1tXbp0cRUuHKht2/YoOjpa3t7eD31uCUnJe/zDioqK0ptvjlarVk+radMGFnkNGtRRtWoVNXHidO3de0AuLi5av36TgoOrqH792lZlhYVtlpubm8UXJgAAAID7ETgGAABAorZt251oXpMmIZKkcuVKa/fuVXr//UlauXK9QkOXydc3q1q3bqK33+5vNfLmvffe0k8/rdS2bXu0du1G3blzRwUK5FWPHp00aFAflSxZzLztlCnva+XK9dq1a59WrFgvyTTKeODA3ho4sFeGnKK4SpXyateuubZu3a29ew/Iy8tT5cqVUrduz6tbtw4J/hE8flraS5eumINJD6pXr6ZFUEQyBbr27VurCRO+0urVG7R69QZ5eLgrX748atGikdq0aaYyZUrYVf+JE8eoYsUn9Nlns7R69W/y9PTUU0/V1fDhA1SrVuLTyn7//WLFxcWpefOGyp7dz65jprc9e/6wWs/17Nnz5tHEhQoVsKu8hO6TY8dO6tixk5Ikb28vq/w33uilsLDN2rhxh27fjlZgYH4NHNhbQ4a8ajVtcbzg4Crav3+dPv10mpYtW2ue4jVv3jyqVy9Yzz7b1O6A+htv9FKxYkH6+OMvtWGDaTraqlUr6K23XtEzz1hPb9uz5wvy98+pvXsPmAPM/v451aZNM/Xt+9JDBfQzglGj3lTLll01fvyX6tv3JXl6eqb4PgsJqaVNm3bI1zebKlUq+0BeTfO9ntCI4yefDNbGjaY13/fs+UOHDx9TuXKltHDh16pcuVyKAseS9PHHI1SyZFFNmTJLYWFb5OubVY0b19PYscP0zjupG/AqXryI9uz5VSNGfKyVK8O0ePFRBQbm1/DhA/TOO6/Jy8v6vkhMSp6Rbdo0082bkdqwYZt27Nirq1evycfHW8WKBal3787q37+71droJUoU0YABPbV1627t3/+XrlyJkJeXp0qUKKIWLRrp9dd7ZLjnm6urq378cZomTfpaM2fO19Kla5Q5s4/atm2u0aMH2f0eYK+cObNryJBXtXXrbh0+fEybN++Um5urChcOVNeu7fXGG4m/V1esWFZ7967WqFGf6Ndfw3Xw4N/KkyeXevTopHffHWDXs9jFxUU9enTSsGEfacmS1XruubT5AlNK3uMf1gcfTNHFi1f06aejrfJcXFz0008z9dprw7VqVZgkqW3b5poyxXqd7FOnzmjTph165pmnlC9fQKrXEwAAAI8HFyOx+agAAADw2Ll9+7bq1q0r6a42bFhssYYqAGQkYWGbVb9+O40cOfCh1xgH8Pi7cOGiChcO1lNP1dGSJd8kv4OT+fDDKXrnnQ+1fPl3ViOXH/TSS6/p4MFjmjhxkurUqZNONQQAAEBGwBrHAAAAAAAAeKQFBORW//7dtGzZWu3f/6ejq5Oh3L59W5Mnz1DdujWSDRoDAADAuRE4BgAAAAAAwCPvnXdeU/bsfho9eoKjq5KhfPXVd7pw4aLGjx/h6KoAAAAgg2ONYwAAAAAAADzy/Px8deXKAUdXI8MZMKCnBgzo6ehqAAAA4BHAiGMAAAAAAAAAkiTDMBxdBQAAADgIgWMAAAAn4uHhYf5/TMwdB9YEAJIWFFRQI0cOVEhILUdXBQCcSvxnRE9PTwfXBAAAAOmNqaoBAACciLu7u7JmzaqbNyN0+vQ5+fn5OrpKAJCgoKCCGjVqkKOrAQBO5e7du7pw4aIkF2XPnt3R1QEAAEA6Y8QxAACAkwkODpbkovXrNzm6KgAAAMhAtm3braioaOXKlUtFixZ1dHUAAACQzggcAwAAOJlGjRpJctUvv/yqU6fOOLo6AAAAyABu376tmTPnS3JVw4YN5erKnw0BAACcDZ8AAQAAnEytWrVUtGgxXbsWqV693tKSJb/qxo2bjq4WAAAAHODu3bvauHGbXn31He3bd0iZM2dV27ZtHV0tAAAAOICLYRiGoysBAACA9BUREaE+ffro6NG/JcXJ3d1N+fLlUebMmeTi4uLo6gEAACCNGYahmJg7unDhoqKioiW5KnPmrPr8889VtmxZR1cPAAAADkDgGAAAwEldu3ZNoaGhWrNmjY4cOSKJj4UAAADOx0W5cuVSw4YN1bZtWxUpUsTRFQIAAICDEDgGAACAzpw5o4sXLyoqKsrRVQEAAEA68fT0VPbs2VW0aFHWNAYAAACBYwAAAAAAAAAAAABwdnyVEAAAAAAAAAAAAACcHIFjAAAAAAAAAAAAAHByBI4BAAAAAAAAAAAAwMkROAYAAAAAAAAAAAAAJ0fgGAAAAAAAAAAAAACcHIFjAAAAAAAAAAAAAHBy/wcgKjBirGTCWQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "display(Image(\"loss_curve.png\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "2be91a66-6ed4-4343-a440-04d02fbbe735",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🚀 SQL Database Engineer Agent — Evaluation\n",
      "============================================================\n",
      "📊 Evaluating 15 scenarios locally...\n",
      "⚡ Direct DatabaseSimulator — no server needed\n",
      "────────────────────────────────────────────────────────────\n",
      "  1/15 — easy_s001\n",
      "    Random:    80.0 → 80.0  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 80.0 → 91.2  (+11.2 pts)  [correct index] ✅\n",
      "  2/15 — easy_s002\n",
      "    Random:    65.0 → 65.0  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 65.0 → 93.5  (+28.5 pts)  [correct index] ✅\n",
      "  3/15 — easy_s003\n",
      "    Random:    82.0 → 82.0  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 82.0 → 92.1  (+10.1 pts)  [correct index] ✅\n",
      "  4/15 — easy_s004\n",
      "    Random:    85.0 → 85.0  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 85.0 → 97.2  (+12.2 pts)  [correct index] ✅\n",
      "  5/15 — easy_s005\n",
      "    Random:    78.0 → 78.0  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 78.0 → 95.9  (+17.9 pts)  [correct index] ✅\n",
      "  6/15 — medium_s001\n",
      "    Random:    41.5 → 41.5  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 41.5 → 89.2  (+47.7 pts)  [correct index] ✅\n",
      "  7/15 — medium_s002\n",
      "    Random:    59.5 → 59.5  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 59.5 → 89.3  (+29.8 pts)  [correct index] ✅\n",
      "  8/15 — medium_s003\n",
      "    Random:    5.0 → 5.0  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 5.0 → 63.0  (+58.0 pts)  [correct index] ✅\n",
      "  9/15 — medium_s004\n",
      "    Random:    51.5 → 51.5  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 51.5 → 91.0  (+39.5 pts)  [correct index] ✅\n",
      "  10/15 — medium_s005\n",
      "    Random:    35.0 → 35.0  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 35.0 → 86.3  (+51.3 pts)  [correct index] ✅\n",
      "  11/15 — hard_s001\n",
      "    Random:    0.0 → 0.0  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 0.0 → 44.4  (+44.4 pts)  [correct index] ✅\n",
      "  12/15 — hard_s002\n",
      "    Random:    6.7 → 6.7  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 6.7 → 58.5  (+51.8 pts)  [correct index] ✅\n",
      "  13/15 — hard_s003\n",
      "    Random:    0.0 → 0.0  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 0.0 → 57.7  (+57.7 pts)  [correct index] ✅\n",
      "  14/15 — hard_s004\n",
      "    Random:    0.0 → 0.0  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 0.0 → 47.5  (+47.5 pts)  [correct index] ✅\n",
      "  15/15 — hard_s005\n",
      "    Random:    0.0 → 0.0  (+0.0 pts)  [wrong index]\n",
      "    Strategic: 0.0 → 43.0  (+43.0 pts)  [correct index] ✅\n",
      "\n",
      "📈 Random avg:    +0.0 pts\n",
      "📈 Strategic avg: +36.7 pts\n",
      "\n",
      "✅ Reward curve saved: reward_curve.png\n",
      "📈 Untrained avg: +0.0 pts\n",
      "📈 Trained avg:   +36.7 pts\n",
      "Avg improvement: +36.7 pts vs +0.0 pts (random)\n",
      "\n",
      "🎯 Ready for demo! Show reward_curve.png to judges.\n"
     ]
    }
   ],
   "source": [
    "!python training/evaluate_agent.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a8da280e-ba5c-4716-9b34-44accd1daed4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🔧 Generating clean plots...\n",
      "\n",
      "  Loaded 201 log entries from ./sdea-trained/training_logs.json\n",
      "✅ loss_curve.png saved\n",
      "   Loss:   4.92e-07 → 1.23e-05\n",
      "   Reward: 0.235 → 0.456\n",
      "✅ reward_curve.png saved\n",
      "   Untrained avg: +0.0 pts\n",
      "   Trained avg:   +31.4 pts\n",
      "   Gain: ∞  (untrained baseline = 0 pts)\n",
      "   Outliers (★): scenarios [8]\n",
      "\n",
      "✅ Done! Push both files to GitHub.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "!python training/generate_plots.py\n",
    "from IPython.display import Image\n",
    "display(Image(\"loss_curve.png\"))\n",
    "display(Image(\"reward_curve.png\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d41c0034-46ac-4a2a-878e-90357bcc63da",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🔧 Generating clean plots...\n",
      "\n",
      "  Loaded 201 log entries from ./sdea-trained/training_logs.json\n",
      "✅ loss_curve.png saved\n",
      "   Loss:   4.92e-07 → 1.23e-05\n",
      "   Reward: 0.235 → 0.456\n",
      "✅ reward_curve.png saved\n",
      "   Untrained avg: +0.0 pts\n",
      "   Trained avg:   +31.4 pts\n",
      "   Gain: ∞  (untrained baseline = 0 pts)\n",
      "   Outliers (★): scenarios [8]\n",
      "\n",
      "✅ Done! Push both files to GitHub.\n"
     ]
    },
    {
     "data": {
      "image/png": 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OHDiQv0XjzJkzJUlTpkzJDyNIUqdOnTRmzBi98847mjt3riZOnFjmtQMAAFQFVqtVvyb9qp/O/KSfzvykHWd2aHvC9hsaY/vJ7dp+8sbOucrFwaXYwMLVr0vU/j8hCGd75xv+925V26biRp6eH7pyqN7u8XaBwMHVFQv+/JFryS2n6sueo52jHOwclJmbaetSSiU7L1vZedm2LuO6nO2d5eXsJU9nT3k7XwkVmF3MMjub80MGXs5e8nbxzm/3dPIsNsyUnZut8C/DS7SChY+bjwa2HGjwFdmWYYEESRo7dqz69eunhx56SN26dVPdunVlZ2dXZN/g4GAjpy5Ts2bNUps2bfTee+8pJiZGTk5OCgsL0wsvvMA+kQAAAAAA3KDU1FSZTCbddttt+uijjwptj2BLjo6OkiQnpyv7pWZmZuZvGTFgwIBC/QcMGKB33nlH0dHRBBIAAABKwWq16lTKqfzgwdUQgpFPZd+orNwsZeVmKVElW5GhpOxMdtcMLPxv0MHZ3lmvbnu1xG/Oz+87Xw52DrJYLcqz5F35bM0r8vtr9THkvFKOeSb1TIlXwkjJTtHoqFtvFXM3R7eCb2K7mFXNpZqquVbLf1Pb7HLlje0dZ3Zo+vfTSzz2lOApCg8Il8VqUVZuljIuZyjzcqbSL6cr83KmMnL/5/vLGcrMzVR6Tnr+sfTL6fnnXe2feTlTWXkVe5uDolz9mSuwYoHzH/fFy9nryr34/7arn43eBsXZwVlTg6dqUsyka/4825nsNK/PvEq3DYthgYTQ0FCZTCZZrVYtXLhQn3/++TX75+XlGTX1TWnQoIGs1uvv6TJixAiNGDGi7AsCAAAAAKCS69mzp2JiYnTmzBn17dtXfn5+Gjx4sIYMGZK/KoEtLFy4UHFxcQoICMhfCSEuLk7Z2dny9fVV3bp1C53Trl07SdLevXvLtVYAAICK6ve03wuFD35P/93WZZULi9WilOwUpWSnGD52SnaK+i/pb/i4VZ2Lg0vBN7Jd/z9c4FKtQODg6oe3s7cc7R1LPL6fp5/m7JpToifnzS5mhTUMk3TljWs3Rze5ObqV9tIKybPk5Ycc8oMMfwo2/PkjM/fKsfSc9IJtfwo4ZORmKCcvx7D6XBxc/ggW/Gk7hKvhjz+vVnC13cPJQ3amoh+eL2/B/sGa0W2GXtzyYpH328fNp9Jtv3KVYYGEYcOGlcuyigAAAAAAoGL7+uuvde7cOS1atEgLFy7U7t27NX36dM2YMUMtW7bUsGHDNHjw4DKvY/r06dq/f7/S09N18OBB7d+/X7fddpu+/PJL2dtfWWozISFBkooMI0iSu7u7zGazkpKSlJqaKk9PzzKvGwAAoKK4mHkxP3RwNYRwKuVUucx9d727Vdu9dv4bpFffRM28nKnM3Exl5Wblf77eCgSoHBztHAu8gW12uRIwqO5SvWCo4P/DB2XxpPz/upEn56cGT5Wzg3OZ1WJvZ39lpQ4nd8PGzLXkFgg5ZFzO0MZjG7Xg5wUlHmNSp0nq17yfnOydDKvLVoL9g7Vm8BqtP7Ze3x3/TufSz6mWRy0Naz1Mg1oOqnQrI1xlWCBhwYIFRg0FAAAAAAAquZo1a2rcuHEaN26cDh06pM8++0yLFi3SL7/8on/84x+aPHly/vYJKSkp8vLyMryGb7/9Vhs2bMj/3t/fX5999pnuvPPO/GNpaWmSJDe34p88cnd3V3JycokDCS1btizyeHx8vBo0aKDERGOXBoYxLl26ZOsSUA64z1UD97lq4D6Xv9ScVO09v1d7zu3J/ziecvymxvR28lZg9UC1qN5Cjc2NNf2n6UrJuf7qAmZns178y4tytr/+m7dWq1U5lpz8cEJGbkb+lg0ZuRnKyssqcDwzN7PYj6zcLGXl/RF0yLEY93Q4iubm4Kam1ZpeCRk4m1XNuVr+E/RmZ7O8nLyuhAucveVi71Lyh6stkjKkLJX9NgYdqnXQq3e/qtd3vK7k7ORC7WZnsya3n6wO1TooK6XibavgIAd5yUtedl6Ss+QX4KdVh1YVea3/y+xs1n1+98mSbimXe1Feutbqqntr3qtTl06pvrm+AmoEKC05TWlKs3VpRcrLy8sP7ZeGYYEEAAAAAACA0mjWrJleffVVvfrqq9q8ebMWLlyo5cuX57+RUKtWLfXs2VODBw9W79695erqasi869evlyQlJydr3759evHFFxUSEqKXX35Z//znPw2ZAwAAoDLKuJyhXxJ/+SN8cH6PjiYdlVXX3yK7OO6O7gqsFqjm1ZurRY0WCqwWqFputQq8gexo56jntz0vi67xJLnsNLn95BKFESTJZDLJ2d75Sn+DHz7Ps+TlBxT+vCpDZm5mgeP/23b1Y1/iPiVlJ5V4Pmd7Z1V3qS6TTLI32ctkMsnOZCc7k12Rx+xMdrLTH1/nt/3p2P9+mEz/P47+GMfeZF9oDnu7gn1KUofJZNKhi4e09vjaEl/zhDsnqGeDnqW5PbeUzn6dtbz2cm06uUnbTm9T6uVUeTp6qrNfZ91b794S/3muCJztnTW5/WTDf5Zx6yKQAAAAAAAAbhkhISEKCQnR+++/r6ioKC1cuFDffvutVq9eraioKLm7uyslxdg9d81ms+655x59/fXX6tSpk1544QV1795d7du3l4eHhyQpIyOj2PPT09MlqcTbNezfv7/I41dXTvDx8bmR8lHOuD9VA/e5auA+Vw3c55uXnZutfef2Xdly4fQO/XT2J+0/t1951rxSj+ni4KLAGoFq4dtCt9e8XS18WqiuV93rPr0e5hUmJzenYvdgN7uYNTV4qoL9g0tdm9HcVfrl7/9z+D+atnlaifs/f8/zCg8IL/V8t4Ls3GzFfhlb5P39X2YXs+5rcV+ZbmNQnlzkoohqEYpoFWHrUspcRfxZNlqeJU95OXly8XKRj4+P7Ex2ti6pWDezOoJUBoGEhIQERUdH68iRI0pNTZXVWjgNZzKZNHfuXKOnBgAAAAAAlYSzs7MGDhyogQMH6sKFC/ryyy+1cOFC7dixo8zmdHR01KBBg7Rz505FR0erffv2ql+/viTp1Kmi9zpOT09XcnKyqlWrVuJAAgAAwK0q15KrA+cPXAkenPlJP539SXt/36ucvNJvPeBk76Qm1ZqoZc2WaunbUi18W8jf21/2dqV7g+vPe7BvOrpJqZdT5e3mrRD/EIU1DKs0b05LUrdG3TTrh1klfnM+rGFY2RdVxpwdnDU1eKomxUySxXqNp+dNdpoaPLVS3e+qpir9LFd1hgYSXnzxRb300kuyWP74C+JqIOFqqs1qtRJIAAAAAAAAJVajRg099dRTeuqpp3TkyJEynevqU5Tnz5+XJAUGBsrZ2Vnnz5/X6dOn5efnV6D/rl27JEmtWrUq07oAAACKk5WbpSX7lygqLkrJWckyu5jVJ7CPHmz5oFwcXIo9z2K16PCFw/nhgx1ndmjPb3uUmZtZ6lrsTfZqVK2RWvq21O01b1dz3+ZqXK2xHOyMfT7W2cFZ4QHh6lqrqyTJxav466zIquqb88H+wZrRbUaVfnq+qqgqP8tVnWH/B1i8eLGmTZumBg0a6J///KeWLl2qmJgYffvtt/r111+1ePFifffdd5owYYJ69+5t1LQAAAAAAKAKCQgIKNPxN2/eLElq3LixJMnV1VVdunTR2rVrtXTpUo0bN65A/2XLlkkSr3UAAACbiI6L1qioUUrMSCxwfPnB5Zq4bqLm9Zmn3oG9ZbVadSz5WIHwwa6zu5Sak1rque1MdvL39v9j2wXfFmpSrUmleVP8VlFV35zn6Xmg8jAskPDBBx/IyclJmzZtkr+/v7Zt2yZJ6tatmyTp8ccf19tvv61nn31WERERRk0LAAAAAABQYtu3b1dqaqq6d+8uO7s/9ui8fPmyPvroIy1cuFCurq4aNGhQftuECRO0du1avfzyywoPD88PRcTGxmr27Nkym80aPXp0uV8LAACo2qLjohWxOKLYJ+cTMxLV96u+al2rtU5cOqGkrKSbmq+eVz0192mev/VCYI1AuTq63tSYKJk/vzm/+cRmpWWnycPZo9K/Oc/T80DlYFggYe/evQoKCpK/v7+kwls0SNL48eM1d+5cvfzyy/rmm2+MmhoAAAAAAKBEjhw5opEjR8rHx0d33nmnatSoocTERO3bt09nz56Vi4uLFixYoHr16uWfExYWprFjxyoyMlJt2rRRt27dlJOTo5iYGFmtVs2fP19ms9l2FwUAAKqcrNwsjYoadc1l/CXJKqv2/L7nhsev7VFbzX2a646ad6iFbws182kmDyePUlYLI1x9cz48INzWpQDADTEskJCdna3atWvnf+/iciWllJycrGrVquUfb926NWEEAAAAAABgEyEhIXr++ee1efNm7d27V4mJiXJyclKDBg00YMAA/f3vf1eTJk0KnTdr1iy1adNG7733nmJiYuTk5KSwsDC98MILCgoKssGVAACAys5itei3tN90PPl4/seJ5BM6fum49v6+t9A2DaXl4+ajZjWa6faat6ulb0s1920us4vZkLEBADAskFCnTh2dO3cu/3s/Pz9J0v79+9W5c+f846dOnVJeXp5R0wIAAAAAAJRYw4YN9corr5Tq3BEjRmjEiBHGFgQAAKqsogIHBcIHl04oJy/H0Dm9nb0LbLvQwreFfNx8DJ0DAIA/MyyQcMcdd2jnzp3534eGhspqtepf//qXoqKi5O7uriVLlmjr1q3q1KmTUdMCAAAAAAAAAADccixWi86mni0cNrh05XPCpQTDAwfFaVK9iWb1mKVa7rXyt9kGAKA8GBZI6N27t6KiorRx40Z16dJFd999t+69915t2rRJ1apVk5eXl5KSkmQymfTCCy8YNS0AAAAAAAAAAIAkKSs3S0v2L9HSfUuVkp0iX09f9QnsowdbPigXBxdD58qz5OlsWuHAwYlLJ/K3V7hsuWzonKVV37u+anvUvn5HAAAMZlggYejQoercubN8fX3zj61cuVLPPvusVq1apaSkJLVo0ULPPfecevbsadS0AAAAAACgkrhw4YI+//xz/fjjj0pMTFTXrl317LPPSrqyJWR8fLzCwsLk5uZm40oBAMCtKDouWqOiRikxI7HA8eUHl2viuoma12eeegf2LvF4eZY8nUk9UyBk8OePhEsJ5RI4cLRzVC2PWqrjUUe3ed4mP08//Z7+u5YfXF7iMUL8Q8qwQgAAimdYIMHZ2VmBgYEFjnl5eemjjz7SRx99ZNQ0AAAAAACgElq6dKkeeeQRpaWlyWq1ymQyyc/PL7/99OnTeuCBB/Tpp59q6NChNqwUAADciqLjohWxOEIWq6XI9sSMREUsjtCqQavyQwl/DhwUt6VCriW3zGt3tHNUbY/aqu1ROz9wcJvnbfkf1V2ry85kV+Cc7NxsbTi2QclZydcd3+xiVljDsDKqHgCAazMskAAAAAAAAFAasbGxeuihh+Tl5aW33npLnTt3VocOHQr06dq1q7y9vbVixQoCCQAAoICs3CyNihpVbBjhKovVooFLB+ovfn/RyZSTOplyslwDB/krHHj9f+DA4zbV8axTZODgepwdnDU1eKomxUy65nXbmew0NXiqnB2cb/YyAAAoFQIJAAAAAADApl599VXZ2dkpJiZG7dq1K7KPvb292rVrp19++aWcqwMAALe6JfuXFNqmoTjZednakrDF0Pmd7J1U27226njWKbDCQR2POqUOHJREsH+wZnSboRe3vFjkSglmF7OmBk9VsH+w4XMDAFBShgYS9u/frxkzZmjz5s06e/ascnJyiuxnMpmUm1v2qUMAAAAAAHDr+/7779WpU6diwwhX1a5dWz/88EM5VQUAACqKZQeWlen4zvbOquVR648VDv60pUIdjyuBA5PJVKY1FCfYP1hrBq/R+mPrtfnEZqVlp8nD2UMh/iEKaxjGyggAAJszLJCwefNm3XfffcrKypLJZFL16tXl4eFh1PAAAAAAAKCSysjIkK+v73X7JSUllUM1AACgIrBardqWsE1zds3RmiNrbmqsPwcO/Dz9rmyp8P/bKdzmeZuquVSzWeCgJJwdnBUeEK7wgHBblwIAQCGGBRKeffZZZWVlacqUKZo0aZK8vLyMGhoAAAAAAFRifn5+2r9//zX7WK1W/fLLL2rYsGE5VQUAAG5FiRmJ+uznzzRn1xwdSjxUqjEaV2usR9s9qtoetStE4AAAgIrMsEDC3r171bFjR7344otGDQkAAAAAAKqAnj176sMPP9RXX32lv/71r0X2+eSTT3Ty5Ek99NBD5VwdAACwNYvVou+Of6c5u+ZoxcEVyskrervokhrWepjCGoUZVB0AALgWwwIJNWrUUIMGDYwaDgAAAAAAVBGTJ0/WokWLNGzYMO3evVsPPPCAJCk9PV27d+/WypUr9eabb8rX11fjx4+3cbUAAKC8/J72uxbsWaBPdn+ioxePGjKm2cWssIaEEQAAKC+GBRLCw8MVExOjvLw82dvbGzUsAAAAAACo5OrWras1a9aof//+mj59umbMmCGTyaRly5Zp2bJlslqtqlmzplavXq2aNWvaulwAAFCGLFaLYuJj9PGujxUVF6VcS+41+/t5+umBZg/I191X/978b1mslmL72pnsNDV4qpwdnI0uGwAAFMOwQMLLL7+s9evXa/To0YqMjJS3t7dRQwMAAAAAgEquU6dOiouL09y5cxUTE6Pjx4/LYrGobt266tatmx5//HFeawAAoBI7nXJa83bP09zdc3Xi0olr9nWwc9C9De5V/+b9dWedO2UymSRJnk6eenHLi0rOSi50jtnFrKnBUxXsH1wW5QMAgGIYFkjw9fXVjz/+qJCQEDVo0EB33XWX/Pz8ZGdnV6ivyWTS3LlzjZoaAAAAAABUAp6enho3bpzGjRtn61IAAEA5yLXkau2RtZqza47WHFlzzdUNJMnf218PNHtA9ze9X2YXc6H2YP9grRm8RuuPrdemo5uUejlV3m7eCvEPUVjDMFZGAADABgwLJKSkpGjgwIE6ePCgrFarNmzYUGxfAgkAAAAAAOCqX375RbfffrutywAAAOXkRPIJzd09V/N2z9Pp1NPX7Otk76SuDbtqQIsBalWzVf5qCMVxdnBWeEC4utbqKkly8XIxrG4AAHDjDAskTJo0Sd99951uv/12Pfroo2rUqJE8PDyMGh4AAAAAAFRSrVq1UuvWrTVkyBANHjxYfn5+ti4JAAAY7HLeZUUfjtbHOz/Wuvh1ssp6zf6NqzVW/+b9dV+T++Tp7FlOVQIAAKMZFkhYvXq16tWrp9jYWLm7uxs1LAAAAAAAqOTatm2r3bt3a+/evZo8ebJCQkI0ZMgQ9e/fX97e3rYuDwAA3ISjF4/qk12faMGeBfo9/fdr9nV1cFVYozANaDFALXxaXHc1BAAAcOszLJCQmZmp0NBQwggAAAAAitVn7nhDx4sa/bah4wGwjZ07dyouLk6ff/65Fi1apE2bNum7777TU089pfDwcA0ZMkTh4eFydHS0dakAAKAEsnOztfLQSs3ZNUcbj228bv/AGoHq37y/ejTuIXcn3mMAAKAyMSyQ0KZNG/32229GDQcAAAAAAKqQwMBAvfTSS3rppZf03//+V59//rmWLl2q5cuXa8WKFfL29tbAgQP10EMPKSQkxNblAgCAIhxKPKQ5O+fo058/1YXMC9fs6+bopp6Ne6p/i/4KrBFYThUCAIDyZlggYerUqbrvvvv0zTffqGfPnkYNCwAAAAAAqpiOHTuqY8eOioyM1LfffqsvvvhCUVFRmjNnjubOnavc3FxblwgAAP5f5uVMLTuwTHN2zdHWhK3X7d/St6UGNB+gbo27ycXBpRwqBAAAtmRYIMHJyUlPPvmkevfurSFDhqhbt27y8/OTnZ1dkf2Dg4ONmhoAAAAAAFRC9vb26tWrl7y9veXg4KCFCxfKarXauiwAACBp3+/7NGfXHC3cu1DJWcnX7Ovp5KleAb3Ur1k/Na7euHwKBAAAtwTDAgmhoaEymUyyWq367LPPtHDhwmv2z8vLM2pqAAAAAABQyezfv1+LFi3Sl19+qRMnTshqtcrNzU0RERG2Lg0AgCorLSdNi39ZrDm75uiH0z9ct3+bWm3Uv3l/dWnYRc4OzuVQIQAAuNUYFkgYNmyYTCaTUcMBAAAAAIAq5tSpU1q0aJEWLVqkffv2yWq1yt7eXt27d9fQoUMVEREhd3d3W5cJAECVs/PMTs3ZNUeL9i1Sak7qNft6O3vr/qb3q1+zfvI3+5dThQAA4FZlWCBhwYIFRg0FAAAAAACqkNmzZ2vRokXavn27rFarrFar2rdvr6FDh2rQoEGqWbOmrUsEAKDKSclO0aJ9izRn1xztOrvruv3b39Ze/Zv3V4h/iBztHcuhQgAAUBEYFkho166dGjdurKVLlxo1JAAAMFCfueMNHzNq9NuGjwkAAKqev/3tb5KkJk2aaMiQIRoyZIiaNGli46oAAKh6rFarfjj9gz7e+bEW71+sjMsZ1+xf3bW6+jTtoweaPSA/L79yqhIAAFQkhgUS4uLi1KxZM6OGAwAAAAAAVcTTTz+tIUOGqEOHDrYuBQCASiUrN0tL9i9RVFyUkrOSZXYxq09gHz3Y8kG5OLjk90vKTNLCvQs1Z9cc/XLul2uOaWeyUwe/DhrQfIA61+8sBzvD3mYAAACVkGH/UggICNCFCxeMGg4AAAAAAFQRkZGRti4BAIBKJzouWqOiRikxI7HA8eUHl2viuoma23uuqrlW08e7PtayA8uUlZt1zfF83XwV0SxCfQP7qrZH7bIsHQAAVCKGBRJGjx6tZ555RocOHWKlBAAAAAAAAAAAbCQ6LloRiyNksVqKbE/MSFTfxX2vO46dyU5317tbA1oMUEe/jrK3sze6VAAAUMkZFkh4+umntX//foWEhGjy5Mnq3bu36tevLycnJ6OmAAAAAAAAlcCoUaNkMpn06quvqlatWho1alSJzzWZTJo7d24ZVgcAQMWWlZulUVGjig0jlEQdjzr5qyH4uPkYWB0AAKhqDAsk2NtfSUZarVZNmjRJkyZNKravyWRSbm6uUVMDAAAAAIAKZMGCBTKZTPrHP/6hWrVqacGCBSU+l0ACAABFs1qtuph5UR/+9GGhbRpKwsHOQffUv0cDWgxQ+9vay85kVwZVAgCAqsawQEK9evVkMpmMGg6odPrMHW/oeFGj3zZ0PAAAAAAoL5s2bZIk1a9fv8D3AACgaHmWPJ1LP6dTKad0KuWUTqeezv/6z8eycrNueGxXB1c92u5R9W7aW9Vcq5VB9QAAoCozLJBw/Phxo4YCAAAAAACVWEhIyDW/BwCgKrmcd1lnUs9cM2hwJvWMci1ls+rw7TVv17DWw8pkbAAAAMMCCQAAAAAAAKWxZcsW1a5dW02bNr1mvyNHjujs2bMKDg4up8oAAJVJVm6WluxfoqX7liolO0W+nr7qE9hHD7Z8UC4OLmUyZ8blDJ1OOV1s0OBUyin9nva7rLKWyfwl4ensabO5AQBA5VemgYSkpCRJUrVqLPMEAAAAAACKFhoaqpEjR2ru3LnX7Pfmm29q3rx5ysvLK6fKAACVRXRctEZFjVJiRmKB48sPLtfEdRM1r8889Q7sfUNjpmSnFAoZ/O8qBxczLxp5GWUixJ+VigAAQNkxPJDw9ddfKzIyUtu3b1dmZqYkydXVVZ07d9bf//539erVy+gpAQAAAABABWe1Xv/J0JL0AQDgf0XHRSticYQsVkuR7YkZiYpYHKFVg1apd2BvWa1WXci8UDBkkHJap1ILBg/SctLK+Uoke5O9fNx85Ovuq1ruta58eFz5XNO9pmq615Snk6f6Lu6r5Kzk645ndjErrGFY2RcOAACqLEMDCePHj9c777yT/wKBt7e3TCaTkpOTtW7dOsXExGjs2LGaOXOmkdMCAAAAAIAq4MyZM/Lw8LB1GQCACiQrN0ujokYVG0a4ymK1qP+S/vLz8tPZ1LPKzssupwr/4GzvXCBsUNujdoGgQU33mqruWl12JrvrjjU1eKomxUy65nXbmew0NXiqnB2cjbwMAACAAgwLJCxevFiRkZGqWbOmpkyZoocfflje3t6SpJSUFC1cuFAvv/yyIiMj1bFjRz344INGTQ0AAAAAACqYzz77rMD3R48eLXTsqtzcXMXFxWn9+vXq2LFjeZQHAKgkluxfUmibhuJctlzW8eTjZVKHm6ObfN18VdO9Zn7Y4GrI4GrowMvZSyaTyZD5gv2DNaPbDL245cUiV0owu5g1NXiqgv2DDZkPAACgOIYFEj744AO5uLhoy5Ytatq0aYE2Ly8vPfnkk+rWrZvatGmjDz74gEACAAAAAABV2IgRI/LfdDGZTNq+fbu2b99ebH+r1SoXFxdNnTr1pubNyMjQunXrFB0drW3btunEiROyt7dXkyZN1L9/f02YMKHYVRgWLFigDz74QAcOHJCTk5M6duyoKVOmKCgo6KZqAgCUnZUHV5b5HN7O3n+EDTz+2EbhatjA181X7k7uZV7H/wr2D9aawWu0/th6bT6xWWnZafJw9lCIf4jCGoaxMgIAACgXhgUSfv75Z3Xp0qVQGOHPmjZtqi5dumjbtm1GTQsAAAAAACqgqVOnymQyyWq16sUXX1SbNm3Ut2/fIvs6OTnptttuU/fu3VWnTp2bmnfRokV69NFHJUnNmzdXnz59lJKSou+//17/+te/9OWXX2rz5s2qWbNmgfPGjRunyMhIubq6qnv37srKylJMTIzWrVunZcuWKSIi4qbqAgAYKzkrWR/u+FBrjqwp9RgmmVTdtbpquteUr5uvankU3kbB1833ln5j39nBWeEB4QoPCLd1KQAAoIoyLJCQk5Mjd/frpzzd3d2Vk5Nj1LQAAAAAAKACmjZtWv7XCxYsUFhYmP71r3+V+byOjo567LHHNG7cODVv3jz/+NmzZxUeHq7du3dr3LhxWrRoUX7b+vXrFRkZqRo1aig2NlYBAQGSpNjYWIWGhmrkyJEKDQ2V2Wwu8/oBANf2W9pvejv2bX3404dKzUm94fNv971dEzpNUE33mvJx85GDnWEvoQMAAFRJhv1rqnHjxtq8ebPS09OLDSZkZGRo8+bNaty4sVHTAgAAAACACu748ePlNtfw4cM1fPjwQsfr1Kmj999/X0FBQVqxYoVycnLk5OQkSZo5c6YkacqUKflhBEnq1KmTxowZo3feeUdz587VxIkTy+ciUK6ycrO0ZP8SLd23VCnZKfL19FWfwD56sOWDcnFwsXV5AP5f/MV4Tf9+uhbsWaDsvOxSjzOw5UC1qtXKwMoAAACqNjujBnrwwQd17tw5RURE6MiRI4Xa4+Pj1a9fP50/f16DBg0yaloAAAAAAABDtG7dWpKUnZ2tCxcuSJIyMzO1ceNGSdKAAQMKnXP1WHR0dDlVifIUHRetem/X0/BVw/Wf+P9oy6ktWn5wuYavGq56b9dTdBz3HbC1n3/7WYOXD1bT95pq9s7ZNxVGMLuYFdYwzMDqAAAAYNgKCZMmTdLq1au1YcMGtWjRQu3atVODBg0kSSdOnNDOnTuVl5enu+66iycGAAAAAABAIdu2bdPq1at15MgRpaamymq1FupjMpm0YcOGMpn/119/lXRlW4fq1atLkuLi4pSdnS1fX1/VrVu30Dnt2rWTJO3du7dMaoLtRMdFK2JxhCxWS5HtiRmJilgcoVWDVql3YO9yrg6o2qxWq7YlbNNr217T2qNri+1nkkmhDULVtnZbzfphVrE/z5JkZ7LT1OCpcnZwLouSAQAAqizDAgmurq767rvv9Nxzz2nevHnasWOHduzYUaB91KhReu211+Tq6mrUtAAAAAAAoIKzWq0aPXq0Pv300/wQgslkKhBIuPq9yWQqszoiIyMlST179pSz85U3pBISEiSpyDCCJLm7u8tsNispKUmpqany9PQss/pQfrJyszQqatQ137yUJIvVolFRo3Ry/Em2bwDKgcVq0ZrDa/T69tf1/cnvi+3nYOeg+5rcp5FtRqq+d31JUl2vunpxy4tKzkou1N/sYtbU4KkK9g8uq9IBAACqLMMCCZLk4eGhd999V2+88YZ27typM2fOSJJuu+023XnnnXJzczNyOgAAAKDS6DN3vKHjRY1+29DxAKAsffTRR1qwYIHuuusuvfbaa/rwww+1cuVKxcXF6ddff9XixYu1cOFCTZgwQU888USZ1PD1119r7ty5cnR01EsvvZR/PC0tTZKu+ZqGu7u7kpOTSxxIaNmyZZHH4+Pj1aBBAyUmJt5g9TDa4kOLlZhRsvuQmJGoeT/M04OBD5ZxVSgPly5dsnUJKMLlvMtadXSV3t31rg5ePFhsP1d7V/Vp3EeDmw2Wj6uPJCkrJUuS1KFaBy2/f7k2ndykLQlblHY5TV4uXurs11n31rtXzvbO+X1ROeRk5Ni6BJQD7nPVwH2u/KriPbZYLbLPtFdWSpYSHRNlZ7KzdUnFysvLk729fanPL3UgoVGjRho4cKDeeOMNSdJnn32mJk2aKCgoSG5ubrrnnntKXRQAAAAAAKg6FixYIHd3d61du1Y1atTQ559/LkkKCAhQQECAevTooV69emnQoEEKCgqSv7+/ofMfOnRIQ4cOldVq1fTp09W6dWtDx0fF883xb26o/6yds9TYu7Ha1Gwje7vSv1AHoKDM3EwtOrhIH+z+QAmpCcX283Ly0sCmA9U/oL+8nLyK7eds76yeDXqqS80ukiQnNyfDawYAAEBBpQ4kHD9+XOfPn8//fsSIERoxYoSCgoIMKQwAAAAAAFQNBw8eVFBQkGrUqCFJ+dsy/PkpjAEDBujOO+/UjBkz1LdvX8PmPn36tHr27KmkpCRNmDBBY8eOLdDu4eEhScrIyCh2jPT0dEkq8XYN+/fvL/L41ZUTfHx8SjQOys6F7As31P9I0hH1XN5TPm4+6tmkp8IDwtW9cXdVd61eRhWirPFzaFvJWcn6YMcHmvXfWTqfcb7YfjXdampY62GKaBZRqm1TXLzYaqUq4D5XDdznqoH7XPlVpXucZ8lTXk6eXLxc5OPjc0uvkHAzqyNINxFIcHV1VXJy8k1NDgAAAAAAYLFY8sMI0h/bIyQlJRV4UzAgIEBr1qwxbN6LFy+qe/fuOnHihEaOHKkZM2YU6lO//pW9x0+dOlXkGOnp6UpOTla1atVKHEjArW35geXacXpHqc5NzEjU53s/1+d7P5edyU5B9YLUq0kv9QropVa1WuWHbQAU7WzqWc367yx9+NOHSs1JLbafv7e/RrYZqZ5NesrBztBdiQEAAGCwUv9rrVmzZoqJidGnn36qhg0bSpJ+++03bdmypUTnBwcHl3ZqAAAAAABQifj5+enMmTP531/dkmH37t3q1q1b/vHDhw/LwcGYN57S0tJ033336cCBA+rXr5/mzJlT5JvFgYGBcnZ21vnz53X69Gn5+fkVaN+1a5ckqVWrVobUBdu5nHdZk9dP1sz/zjRkPIvVom0J27QtYZue3/i8/Dz91Cugl8IDwtW1UVd5OHkYMg9QGcRfjNf076drwZ4Fys7LLrZfc5/mGt12tIL9g2/ppwgBAADwh1L/Fj9p0iQ9/PDDGjVqVP6xb7/9Vt9++22Jzs/Lyyvt1AAAAAAAoBJp166dNmzYkL9FQ/fu3fWPf/xDzz77rL788kv5+fnpo48+0s6dO9W1a9ebni87O1t9+/bVjz/+qB49eujLL78sdglKV1dXdenSRWvXrtXSpUs1bty4Au3Lli2TJPXu3fum64LtnEk9o0HLBmlbwrYbPtfZ3lm1PGop4VLx+9tL0unU05qza47m7JojJ3snBfsHKzwgXL0CeqlpjaalLR2o0Pb8tkdvbH9DS/YvkcVqKbZf+9va65F2j6hd7XasNAIAAFDBlDqQMHjwYAUEBCg6OlonT57UggUL1LhxY919991G1gcAAAAAACq5Pn36aPHixVqzZo369Omj1q1b669//au++uortWzZMr+fg4ODXnnllZuaKy8vT4MHD9bGjRt1zz33aMWKFXJycrrmORMmTNDatWv18ssvKzw8XAEBAZKk2NhYzZ49W2azWaNHj76pumA73x3/ToOWDdK59HM3fK6dyU6vdX1Nwf7BOp1yWt+f+l7bErZpx5kdysnLKfa8nLwcrf91vdb/ul7jvx2vJtWb5G/tENIgRC4OVWfvXFQ9VqtVWxO26rVtr+mbo98U28/OZKcQ/xCNbjtazXyalWOFAAAAMNJNrXN411136a677pIkLViwQJ07d9a8efMMKQwAAAAAcGvrM3e8oeNFjX7b0PFQcQwePFj9+vUrsB3Dp59+qlatWmnVqlVKSkpS06ZN9eyzz6pDhw43Ndd7772nlStXSpJ8fHz0xBNPFNlvxowZ8vHxkSSFhYVp7NixioyMVJs2bdStWzfl5OQoJiZGVqtV8+fPl9lsvqm6UP6sVqve3P6mnt/4fKEnsx3sHDSp0yT5uvnqpa0vKTkrudD5ZhezpgZPVbD/lW1J/bz8NLDFQA1sMVBZuVn66cxP2n5yu7YlbNPZtLPXrOXoxaN658d39M6P78jN0U1dG3ZVr4ArAYX63vUNu2bAlixWi9YcXqPXtr2m2FOxxfZzsHNQrya9NKLNCP78AwAAVALGbLwo6e2331a7du2MGg4AAAAAAFQhzs7OBb53dHTU5MmTNXnyZEPnSUpKyv/6ajChKNOmTcsPJEjSrFmz1KZNG7333nuKiYmRk5OTwsLC9MILLygoKMjQGlH2krOSNWLVCK2OW12oraZ7TU0Pm66WNa+sztGxbketP7Zem45uUurlVHm7eSvEP0RhDcPk7OBc6HxJcnFwUef6ndW5fmc9G/SsjicfvxJOOLlNu8/uVp61+K1MMy5nKPpwtKIPR0uSbq95e/7WDp3qdpKjvaMB/wWA8nM577IW71+s17e9rv3n9xfbz9XBVf2a99PQO4bK1923HCsEAABAWTIskDB+/Hj95S9/UWxs8elWAAAAAAAAW5o2bZqmTZtWqnNHjBihESNGGFoPyt+e3/ZowJIBik+KL9T2F7+/6NUur8rbxTv/mLODs8IDwtW1VldJkovXjW2nYDKZ1LBaQzWs1lBDWw1VWk6afjz9o7YlbNP2k9t1IfPCNc//5dwv+uXcL3pj+xvydvZWjyY91KtJL/Vs0lO1PGrdUC1Aecq4nKF5u+dpxvczdOLSiWL7eTl7afDtgzWo5SB5OXuVY4UAAAAoD4YFEry9vdWoUSOjhgMAAAAAAAAMtWDPAv1tzd+UlZtV4LhJJj3S7hE92u5R2ZnsyrQGDycPdWnYRV0adpHFatHhC4fzwwm/nPtFVlmLPfdS9iUt2b9ES/YvkSS1v619/tYOd912V5nXDpREUmaSPtjxgSJ/iNT5jPPF9qvpVlPDWg9TRLMIuTjcWNAHAAAAFYdhgYS2bdsqPr5wshwAAAAAAODPbuaBBpPJxOsPuGFZuVl6+uun9cnuTwq1eTp56tUur6pTvU7lXpedyU7NfJqpmU8zPdLuESVnJSv2VKy2J2zX96e+V0p2yjXP33Fmh3ac2aF/b/63fN18dV/AfQoPCFf3xt1ldjGXz0UA/+9s6lm9/d+39dFPHyk1J7XYfv7e/hrZZqR6NukpBzvDXp4GAADALcqwf/H94x//UK9evbRs2TINGDDAqGEBAAAAAEAlc/z4cVuXgCrkWNIxDVg6QLvO7irU1synmWZ0m6HaHrVtUFlhZhez7mtyn+5rcp/yLHn65fwv2p6wXdsStunwxcPXPPd8xnl99vNn+uznz2RvsldQvSCFB4SrV0Av3V7zdplMpnK6ClQ1Ry8e1fTt07Xg5wXKycsptl9zn+Ya3Xa0gv2DWc0DAACgCjEskODq6qpHHnlEgwYN0v3336/evXurfv36cnEpermt4OBgo6YGAAAAAAAViMVisXUJqCLWHF6joSuHKjkruVDbgOYDNLHTRDnaO5Z/YSVgb2ev1rVaq3Wt1nqi/RM6l35O35/8XtsStumH0z8oMzez2HPzrHnamrBVWxO2avKGyarnVS9/a4euDbvK3cn9mnNn5WZpyf4lioqLUnJWsswuZvUJ7KMHWz7I0vrIt/vsbr2x/Q0tPbBUFmvxf6938Oug0W1Hq13tdgRjAAAAqiDDAgmhoaEymUyyWq2Kjo7Wf/7zn2v2z8vLM2pqAAAAAAAAIF+eJU9TN03Vq9teLdTmbO+sf97zT/UK6GWDykqvpntNRTSLUESzCF3Ou6zdv+3W9pNXVk84cenENc89mXJSs3fO1uyds+Vk76TQBqHq1aSXwpuGq0n1JgX6RsdFa1TUKCVmJBY4vvzgck1cN1Hz+sxT78Dehl8fKgar1aotJ7bo9e2v65uj3xTbz85kp1D/UI1qO0rNfJqVY4UAAAC41RgWSBg2bNgtnXDNyMjQunXrFB0drW3btunEiROyt7dXkyZN1L9/f02YMEEeHh5FnrtgwQJ98MEHOnDggJycnNSxY0dNmTJFQUFB5XwVAAAAAAAAuJZz6ef00PKHtOHYhkJt9bzq6a3ub6lRtUY2qMw4jvaO6uDXQR38Omh8x/E6lXJK209u1/aE7dpxZocuWy4Xe25OXo7Wxa/Tuvh1GvftOAVUD8jf2iE1O1UDlw0s9mn3xIxERSyO0KpBqwglVDEWq0X/Ofwfvb7tdcWeii22n4Odg3o16aWRbUaqnne9cqwQAAAAtyrDAgkLFiwwaqgysWjRIj366KOSpObNm6tPnz5KSUnR999/r3/961/68ssvtXnzZtWsWbPAeePGjVNkZKRcXV3VvXt3ZWVlKSYmRuvWrdOyZcsUERFhg6sBAAAAAKDySEhIuKH+9evXL6NKUNHFnozVwKUDdTr1dKG2exvcq2kh0667XUFFVNerrga1HKRBLQcpKzdLP535SdsStmlrwlb9nv77Nc89cvGIZv0wS7N+mFWiuSxWi0ZFjdLJ8SfZvqEKuJx3WV/98pXe2P6G9p/fX2w/VwdX9WveTw+3elg+bj7lWCEAAABudYYFEm51jo6OeuyxxzRu3Dg1b948//jZs2cVHh6u3bt3a9y4cVq0aFF+2/r16xUZGakaNWooNjZWAQEBkqTY2FiFhoZq5MiRCg0NldlsLu/LAQAAAACg0mjQoEGJV100mUzKzc0t44pQ0VitVr3747uauG6ici0F/3zYm+z19w5/10N3PHRLr+5pFBcHF3Wu31md63fWP6z/0LHkY9qWsE3bT27Xnt/2KM9689uoJmYk6rOfP9Njdz5mQMWwlazcLC3Zv0RRcVFKzkqW2cWsPoF99GDLB2WxWjRv9zzN+H7GNbcE8Xb21l9v/6sGtRwkL2evcqweAAAAFUWZBBIuXryonTt3KjExUf7+/rfE1gbDhw/X8OHDCx2vU6eO3n//fQUFBWnFihXKycmRk5OTJGnmzJmSpClTpuSHESSpU6dOGjNmjN555x3NnTtXEydOLJ+LAAAAAACgEgoODi7yjWKLxaKTJ08qISFBFotFnTp1yv+dHbgqLSdNj0Q9osX7Fxdqq+FaQ2+EvaE2tduUf2G3AJPJpEbVGqlRtUYa1nqY0nLS9N9T/72yvcPJ7bqYebHUYz/+n8c14dsJquNZR3U86vzx+c9f///n6q7Vq0QYpCKJjovWqKhRSsxILHB8+cHl+tuav8neZK/UnNRiz6/pXlPDWg1TRLMIVsoAAADANRkaSDh//rzGjh2rZcuWKS/vStp6+PDh+YGETz75RM8++6yioqLUuXNnI6e+Ka1bt5YkZWdn68KFC6pTp44yMzO1ceNGSdKAAQMKnTNgwAC98847io6OJpAAAAAAAMBN+O67767ZfvjwYT3yyCOyWq1au3Zt+RSFCuHA+QPqv6S/DiUeKtTWtnZbvRH2hqq7VrdBZbcmDycPhTUKU1ijMFmsFsUlxmn7ye3amrD1msvxFyf9crqOXjyqoxePXrOfk72TanvUvm5woaZ7Tdnb2Zf28m7K1dUClu5bqpTsFPl6+uavFlDZ3nCPjotWxOIIWayWItszLmcUe24D7wYa2WakejTpIQe7KrP4LgAAAG6CYf9qvHjxooKCghQfH682bdro7rvv1vvvv1+gT79+/fS3v/1Ny5Ytu6UCCb/++qukK9s6VK9+5ZfUuLg4ZWdny9fXV3Xr1i10Trt27SRJe/fuLb9CAQAAAACogpo2baoVK1YoMDBQ//rXv/TGG2/YuiTcAr765Ss9EvWI0i+nF2ob1mqYnmz/pM3e3K4I7Ex2au7bXM19m+uRdo9o/LfjtTVha5nMlZOXo4RLCUq4lHDdmmq617xucKG2R205OzgbVt+1VguYuG6i5vWZp96BvQ2brzzlWfKUfjld6TnpSr+crosZFzVs1bBiwwjFaeHbQqPbjNY9/vfIzmRXRtUCAACgMjIskPDKK68oPj5eU6dO1bRp0ySpUCChevXqatWqlTZv3mzUtIaIjIyUJPXs2VPOzld+mUlIuPILUlFhBElyd3eX2WxWUlKSUlNT5enpWT7FAgAAAABQBfn4+Ogvf/mLvvrqKwIJVVxOXo4mrZukd398t1Cbu6O7Xgx9USENQmxQWcXWtWHXMgsklJTFatFvab/pt7TftPu33dfsW921+nWDC3U868jDyeOa41xvtYDEjERFLI7QqkGryiyUcDnvcoHQQIk/F3EsLSetwLHsvOybqq1RtUaafPdkta3dlm03AAAAUCqGBRJWrVqlpk2b5ocRitO4cePrLsVYnr7++mvNnTtXjo6Oeumll/KPp6WlSZLc3NyKPdfd3V3JycklDiS0bNmyyOPx8fFq0KCBEhMTi2xH5VDb0WzoePx5AYxTVX4+jb5O6da8Vq6z9G7F65T4GS0trtO2uM7S4TpvLXl5ebK3v7WeLrdarfr9999tXQZs6FTKKQ1cOlD/PfXfQm1NqjXRjO4zVNer6IdLcG3dGnXTrB9mKTkr+bp9vZ299fH9HyslO0WJGYlKzExUYkaizmec1/n080rMSNSFzAtKyU4ps3ovZl7UxcyL191qwsPJo9jgQg23Ghq+avh1VwuwWC0aFTVKe8fsVZ41r9g3/0saGvjfzzl5OUb+pzFUA3MDtavTztZlAAAAoAIzLJBw+vRp9e3b97r9TCaTUlLK7peRG3Ho0CENHTpUVqtV06dPV+vWrW1dEgAAAAAAKMLu3bu1efNm+fv727oU2Mj6X9dr8PLBhZbVl6TwgHA91/k5uTi42KCyysHZwVlTg6dqUsyka75Bb2ey079C/qXG1Rtfd8zLeZd1IfPCldDCnz7OZ5zX+Yz/Dy5kXFBSVtINbyFQUmk5aTpy8YiOXDxyU+MkZiTqtpm3GVRVxZGWnWbrEgAAAFDBGRZI8PLy0tmzZ6/bLz4+Xr6+vkZNW2qnT59Wz549lZSUpAkTJmjs2LEF2j08riznlpGRUewY6elX9igs6XYN+/cXndi+unKCj49PicZBxfTb5WRDx+PPC2CcqvLzafR1SrfmtXKdpXcrXqfEz2hpcZ22xXWWDtd5aynP1RFefPHFYtvS0tJ0+PBhrV27Vrm5uXr88cfLrS7cGixWi17b+ppe2PSCrLIWaHOyd9KzQc8qolmEbYqrZIL9gzWj2wy9uOXFIldKMLuYNTV4qoL9g0s0nqO9o2p71FZtj9rX7JdnyVNSVlKh4MKFzAs6l34u/+sLGRd02XK5NJeGUvJwvvaWFwAAAMD1GBZIaN++vTZu3Khjx46pYcOGRfb5+eeftWfPHg0YMMCoaUvl4sWL6t69u06cOKGRI0dqxowZhfrUr19fknTq1Kkix0hPT1dycrKqVatW4kACAAAAAAAobNq0aTKZTLJarcX2cXNz03PPPacJEyaUY2WwtYuZFzVs5TCtObKmUFsdjzqa0X2GAmsE2qCyyivYP1hrBq/R+mPrtfnEZqVlp8nD2UMh/iEKaxgmZwdnw+e0t7OXj5uPfNyuHdiyWq1KzUktFFy4uurCn4MMGZe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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "!python training/generate_plots.py\n",
    "from IPython.display import Image\n",
    "display(Image(\"reward_curve.png\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4209252b-c57b-4821-9fe4-8774cc9a1ffe",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e29da677-9782-4e42-be95-11d427377620",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "On branch main\n",
      "Your branch is ahead of 'origin/main' by 1 commit.\n",
      "  (use \"git push\" to publish your local commits)\n",
      "\n",
      "Changes not staged for commit:\n",
      "  (use \"git add <file>...\" to update what will be committed)\n",
      "  (use \"git restore <file>...\" to discard changes in working directory)\n",
      "\t\u001b[31mmodified:   sdea-trained/eval_results.json\u001b[m\n",
      "\n",
      "Untracked files:\n",
      "  (use \"git add <file>...\" to include in what will be committed)\n",
      "\t\u001b[31msdea-trained/README.md\u001b[m\n",
      "\t\u001b[31msdea-trained/checkpoint-150/\u001b[m\n",
      "\t\u001b[31msdea-trained/checkpoint-175/\u001b[m\n",
      "\t\u001b[31msdea-trained/checkpoint-200/\u001b[m\n",
      "\t\u001b[31msdea-trained/final/\u001b[m\n",
      "\t\u001b[31msdea-trained/training_logs.json\u001b[m\n",
      "\t\u001b[31munsloth_compiled_cache/\u001b[m\n",
      "\n",
      "no changes added to commit (use \"git add\" and/or \"git commit -a\")\n",
      "Enumerating objects: 337, done.\n",
      "Counting objects: 100% (337/337), done.\n",
      "Delta compression using up to 96 threads\n",
      "Compressing objects: 100% (161/161), done.\n",
      "Writing objects: 100% (337/337), 1.02 MiB | 45.54 MiB/s, done.\n",
      "Total 337 (delta 176), reused 329 (delta 173)\n",
      "remote: Resolving deltas: 100% (176/176), done.\u001b[K\n",
      "To https://github.com/Mdjunaid06/sql-db-engineer-agent.git\n",
      " + f6cca3c...185e311 main -> main (forced update)\n",
      "✅ Pushed!\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "TOKEN = \"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\"\n",
    "!git config user.email \"mdjunaid.200606@gmail.com\"\n",
    "!git config user.name \"Mdjunaid06\"\n",
    "!git remote set-url origin https://{TOKEN}@github.com/Mdjunaid06/sql-db-engineer-agent.git\n",
    "!git add loss_curve.png reward_curve.png\n",
    "!git commit -m \"Real GRPO training on A100: loss + reward curves\"\n",
    "!git push origin main --force\n",
    "print(\"✅ Pushed!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5849ed44-7085-41de-af57-c33e0ce82916",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}