diff --git "a/competition/15_InternLM_NV4090_test.ipynb" "b/competition/15_InternLM_NV4090_test.ipynb" new file mode 100644--- /dev/null +++ "b/competition/15_InternLM_NV4090_test.ipynb" @@ -0,0 +1 @@ +{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"executionInfo":{"elapsed":476,"status":"ok","timestamp":1720679526275,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"uWKRSV6eZsCn"},"outputs":[],"source":["%load_ext autoreload\n","%autoreload 2"]},{"cell_type":"code","execution_count":2,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"eb33b19f-1206-41ee-84e2-e6258a12eef7","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":2534,"status":"ok","timestamp":1720679529344,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"xwFh14uiZBrI","outputId":"d767799c-34c2-46a5-f052-378146a55321"},"outputs":[],"source":["from pathlib import Path\n","\n","try:\n"," from google.colab import drive\n","\n"," drive.mount(\"/content/drive\")\n"," workding_dir = \"/content/drive/MyDrive/logical-reasoning/\"\n","except ModuleNotFoundError:\n"," workding_dir = str(Path.cwd().parent)"]},{"cell_type":"code","execution_count":3,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"6d394937-6c99-4a7c-9d32-7600a280032f","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":5,"status":"ok","timestamp":1720679529345,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"G5pNu3zgZBrL","outputId":"160a554f-fb08-4aa0-bc00-0422fb7c1fac"},"outputs":[{"name":"stdout","output_type":"stream","text":["workding dir: /home/inflaton/code/logical-reasoning\n"]}],"source":["import os\n","import sys\n","from pathlib import Path\n","\n","os.chdir(workding_dir)\n","sys.path.append(workding_dir)\n","print(\"workding dir:\", workding_dir)"]},{"cell_type":"code","execution_count":4,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"9f67ec60-2f24-411c-84eb-0dd664b44775","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3,"status":"ok","timestamp":1720679529345,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"hPCC-6m7ZBrM","outputId":"c7aa2c96-5e99-440a-c148-201d79465ff9"},"outputs":[{"name":"stdout","output_type":"stream","text":["loading env vars from: /home/inflaton/code/logical-reasoning/.env\n"]},{"data":{"text/plain":["True"]},"execution_count":4,"metadata":{},"output_type":"execute_result"}],"source":["from dotenv import find_dotenv, load_dotenv\n","\n","found_dotenv = find_dotenv(\".env\")\n","\n","if len(found_dotenv) == 0:\n"," found_dotenv = find_dotenv(\".env.example\")\n","print(f\"loading env vars from: {found_dotenv}\")\n","load_dotenv(found_dotenv, override=True)"]},{"cell_type":"code","execution_count":5,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"f1597656-8042-4878-9d3b-9ebfb8dd86dc","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3,"status":"ok","timestamp":1720679529345,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"1M3IraVtZBrM","outputId":"29ab35f6-2970-4ade-d85d-3174acf8cda0"},"outputs":[{"name":"stdout","output_type":"stream","text":["internlm/internlm2_5-7b-chat-1m inflaton-ai/InternLM_2_5-7b_LoRA-Adapter False datasets/mgtv results/mgtv-results_nv4090.csv\n"]}],"source":["import os\n","\n","model_name = os.getenv(\"MODEL_NAME\")\n","adapter_name_or_path = os.getenv(\"ADAPTER_NAME_OR_PATH\")\n","load_in_4bit = os.getenv(\"LOAD_IN_4BIT\") == \"true\"\n","data_path = os.getenv(\"LOGICAL_REASONING_DATA_PATH\")\n","results_path = os.getenv(\"LOGICAL_REASONING_RESULTS_PATH\")\n","use_english_datasets = os.getenv(\"USE_ENGLISH_DATASETS\") == \"true\"\n","\n","print(model_name, adapter_name_or_path, load_in_4bit, data_path, results_path)"]},{"cell_type":"code","execution_count":6,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"b2a43943-9324-4839-9a47-cfa72de2244b","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":564,"status":"ok","timestamp":1720679529907,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"UgMvt6dIZBrM","outputId":"ce37581c-fd26-46c2-ad87-d933d99f68f7"},"outputs":[{"name":"stdout","output_type":"stream","text":["Python 3.11.9\n","\u001b[33mWARNING: Package(s) not found: torchaudio, torchvision\u001b[0m\u001b[33m\n","\u001b[0mName: transformers\n","Version: 4.41.2\n","Summary: State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow\n","Home-page: https://github.com/huggingface/transformers\n","Author: The Hugging Face team (past and future) with the help of all our contributors (https://github.com/huggingface/transformers/graphs/contributors)\n","Author-email: transformers@huggingface.co\n","License: Apache 2.0 License\n","Location: /home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages\n","Requires: filelock, huggingface-hub, numpy, packaging, pyyaml, regex, requests, safetensors, tokenizers, tqdm\n","Required-by: llamafactory, peft, trl\n","---\n","Name: torch\n","Version: 2.3.1\n","Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration\n","Home-page: https://pytorch.org/\n","Author: PyTorch Team\n","Author-email: packages@pytorch.org\n","License: BSD-3\n","Location: /home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages\n","Requires: filelock, fsspec, jinja2, networkx, nvidia-cublas-cu12, nvidia-cuda-cupti-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-runtime-cu12, nvidia-cudnn-cu12, nvidia-cufft-cu12, nvidia-curand-cu12, nvidia-cusolver-cu12, nvidia-cusparse-cu12, nvidia-nccl-cu12, nvidia-nvtx-cu12, sympy, triton, typing-extensions\n","Required-by: accelerate, bitsandbytes, peft, trl\n","CPU times: user 1.09 ms, sys: 16.8 ms, total: 17.9 ms\n","Wall time: 1.85 s\n"]}],"source":["%%time\n","!python --version\n","!pip show transformers torch torchvision torchaudio"]},{"cell_type":"code","execution_count":7,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1685,"status":"ok","timestamp":1720679531591,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"ZuS_FsLyZBrN","outputId":"2cba0105-c505-4395-afbd-2f2fee6581d0"},"outputs":[{"name":"stdout","output_type":"stream","text":["loading /home/inflaton/code/logical-reasoning/llm_toolkit/logical_reasoning_utils.py\n","CUDA is available, we have found 1 GPU(s)\n","NVIDIA GeForce RTX 4090\n","CUDA version: 12.1\n"]}],"source":["from llm_toolkit.llm_utils import *\n","from llm_toolkit.logical_reasoning_utils import *\n","\n","device = check_gpu()"]},{"cell_type":"code","execution_count":9,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["loading /home/inflaton/code/logical-reasoning/llm_toolkit/logical_reasoning_utils.py\n","Current Directory:\n","/home/inflaton/code/logical-reasoning\n","Tue Jul 23 12:39:15 2024 \n","+---------------------------------------------------------------------------------------+\n","| NVIDIA-SMI 535.54.04 Driver Version: 536.25 CUDA Version: 12.2 |\n","|-----------------------------------------+----------------------+----------------------+\n","| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |\n","| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |\n","| | | MIG M. |\n","|=========================================+======================+======================|\n","| 0 NVIDIA GeForce RTX 4090 On | 00000000:01:00.0 On | Off |\n","| 0% 46C P8 17W / 450W | 1004MiB / 24564MiB | 3% Default |\n","| | | N/A |\n","+-----------------------------------------+----------------------+----------------------+\n"," \n","+---------------------------------------------------------------------------------------+\n","| Processes: |\n","| GPU GI CI PID Type Process name GPU Memory |\n","| ID ID Usage |\n","|=======================================================================================|\n","| No running processes found |\n","+---------------------------------------------------------------------------------------+\n","Linux Gen-AI 5.15.133.1-microsoft-standard-WSL2 #1 SMP Thu Oct 5 21:02:42 UTC 2023 x86_64 x86_64 x86_64 GNU/Linux\n","PRETTY_NAME=\"Ubuntu 22.04.2 LTS\"\n","NAME=\"Ubuntu\"\n","VERSION_ID=\"22.04\"\n","VERSION=\"22.04.2 LTS (Jammy Jellyfish)\"\n","VERSION_CODENAME=jammy\n","ID=ubuntu\n","ID_LIKE=debian\n","HOME_URL=\"https://www.ubuntu.com/\"\n","SUPPORT_URL=\"https://help.ubuntu.com/\"\n","BUG_REPORT_URL=\"https://bugs.launchpad.net/ubuntu/\"\n","PRIVACY_POLICY_URL=\"https://www.ubuntu.com/legal/terms-and-policies/privacy-policy\"\n","UBUNTU_CODENAME=jammy\n","Architecture: x86_64\n"," CPU op-mode(s): 32-bit, 64-bit\n"," Address sizes: 39 bits physical, 48 bits virtual\n"," Byte Order: Little Endian\n","CPU(s): 32\n"," On-line CPU(s) list: 0-31\n","Vendor ID: GenuineIntel\n"," Model name: 13th Gen Intel(R) Core(TM) i9-13900KF\n"," CPU family: 6\n"," Model: 183\n"," Thread(s) per core: 2\n"," Core(s) per socket: 16\n"," Socket(s): 1\n"," Stepping: 1\n"," BogoMIPS: 5990.39\n"," Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mc\n"," a cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscal\n"," l nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopo\n"," logy tsc_reliable nonstop_tsc cpuid pni pclmulqdq vmx s\n"," sse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt tsc_dea\n"," dline_timer aes xsave avx f16c rdrand hypervisor lahf_l\n"," m abm 3dnowprefetch ssbd ibrs ibpb stibp ibrs_enhanced \n"," tpr_shadow vnmi ept vpid ept_ad fsgsbase tsc_adjust bmi\n"," 1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushop\n"," t clwb sha_ni xsaveopt xsavec xgetbv1 xsaves avx_vnni u\n"," mip waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64\n"," b fsrm md_clear serialize flush_l1d arch_capabilities\n","Virtualization features: \n"," Virtualization: VT-x\n"," Hypervisor vendor: Microsoft\n"," Virtualization type: full\n","Caches (sum of all): \n"," L1d: 768 KiB (16 instances)\n"," L1i: 512 KiB (16 instances)\n"," L2: 32 MiB (16 instances)\n"," L3: 36 MiB (1 instance)\n","Vulnerabilities: \n"," Gather data sampling: Not affected\n"," Itlb multihit: Not affected\n"," L1tf: Not affected\n"," Mds: Not affected\n"," Meltdown: Not affected\n"," Mmio stale data: Not affected\n"," Retbleed: Mitigation; Enhanced IBRS\n"," Spec rstack overflow: Not affected\n"," Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl\n"," and seccomp\n"," Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer\n"," sanitization\n"," Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB fillin\n"," g, PBRSB-eIBRS SW sequence\n"," Srbds: Not affected\n"," Tsx async abort: Not affected\n","MemTotal: 49330020 kB\n","Eval internlm/internlm2_5-7b-chat-1m with inflaton-ai/InternLM_2_5-7b_LoRA-Adapter\n","loading env vars from: /home/inflaton/code/logical-reasoning/.env\n","Adding /home/inflaton/code/logical-reasoning to sys.path\n","loading /home/inflaton/code/logical-reasoning/llm_toolkit/logical_reasoning_utils.py\n","internlm/internlm2_5-7b-chat-1m inflaton-ai/InternLM_2_5-7b_LoRA-Adapter False datasets/mgtv results/test_b-results.csv\n","(1) GPU = NVIDIA GeForce RTX 4090. Max memory = 23.988 GB.\n","0.0 GB of memory reserved.\n","loading model: internlm/internlm2_5-7b-chat-1m with adapter: inflaton-ai/InternLM_2_5-7b_LoRA-Adapter\n","[INFO|tokenization_utils_base.py:2108] 2024-07-23 12:39:23,767 >> loading file ./tokenizer.model from cache at /home/inflaton/.cache/huggingface/hub/models--internlm--internlm2_5-7b-chat-1m/snapshots/8d1a709a04d71440ef3df6ebbe204672f411c8b6/./tokenizer.model\n","[INFO|tokenization_utils_base.py:2108] 2024-07-23 12:39:23,767 >> loading file added_tokens.json from cache at None\n","[INFO|tokenization_utils_base.py:2108] 2024-07-23 12:39:23,767 >> loading file special_tokens_map.json from cache at /home/inflaton/.cache/huggingface/hub/models--internlm--internlm2_5-7b-chat-1m/snapshots/8d1a709a04d71440ef3df6ebbe204672f411c8b6/special_tokens_map.json\n","[INFO|tokenization_utils_base.py:2108] 2024-07-23 12:39:23,767 >> loading file tokenizer_config.json from cache at /home/inflaton/.cache/huggingface/hub/models--internlm--internlm2_5-7b-chat-1m/snapshots/8d1a709a04d71440ef3df6ebbe204672f411c8b6/tokenizer_config.json\n","[INFO|tokenization_utils_base.py:2108] 2024-07-23 12:39:23,767 >> loading file tokenizer.json from cache at None\n","07/23/2024 12:39:24 - INFO - llamafactory.data.template - Add <|im_end|> to stop words.\n","/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n"," warnings.warn(\n","[INFO|configuration_utils.py:733] 2024-07-23 12:39:24,401 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--internlm--internlm2_5-7b-chat-1m/snapshots/8d1a709a04d71440ef3df6ebbe204672f411c8b6/config.json\n","[INFO|configuration_utils.py:733] 2024-07-23 12:39:25,110 >> loading configuration file config.json from cache at /home/inflaton/.cache/huggingface/hub/models--internlm--internlm2_5-7b-chat-1m/snapshots/8d1a709a04d71440ef3df6ebbe204672f411c8b6/config.json\n","[INFO|configuration_utils.py:796] 2024-07-23 12:39:25,110 >> Model config InternLM2Config {\n"," \"_name_or_path\": \"internlm/internlm2_5-7b-chat-1m\",\n"," \"architectures\": [\n"," \"InternLM2ForCausalLM\"\n"," ],\n"," \"attn_implementation\": \"eager\",\n"," \"auto_map\": {\n"," \"AutoConfig\": \"internlm/internlm2_5-7b-chat-1m--configuration_internlm2.InternLM2Config\",\n"," \"AutoModel\": \"internlm/internlm2_5-7b-chat-1m--modeling_internlm2.InternLM2ForCausalLM\",\n"," \"AutoModelForCausalLM\": \"internlm/internlm2_5-7b-chat-1m--modeling_internlm2.InternLM2ForCausalLM\"\n"," },\n"," \"bias\": false,\n"," \"bos_token_id\": 1,\n"," \"eos_token_id\": 2,\n"," \"hidden_act\": \"silu\",\n"," \"hidden_size\": 4096,\n"," \"initializer_range\": 0.02,\n"," \"intermediate_size\": 14336,\n"," \"max_position_embeddings\": 262144,\n"," \"model_type\": \"internlm2\",\n"," \"num_attention_heads\": 32,\n"," \"num_hidden_layers\": 32,\n"," \"num_key_value_heads\": 8,\n"," \"pad_token_id\": 2,\n"," \"pretraining_tp\": 1,\n"," \"rms_norm_eps\": 1e-05,\n"," \"rope_scaling\": {\n"," \"factor\": 2.5,\n"," \"type\": \"dynamic\"\n"," },\n"," \"rope_theta\": 50000000,\n"," \"tie_word_embeddings\": false,\n"," \"torch_dtype\": \"bfloat16\",\n"," \"transformers_version\": \"4.41.2\",\n"," \"use_cache\": true,\n"," \"vocab_size\": 92544\n","}\n","\n","07/23/2024 12:39:25 - INFO - llamafactory.model.patcher - Using KV cache for faster generation.\n","[INFO|modeling_utils.py:3474] 2024-07-23 12:39:25,429 >> loading weights file model.safetensors from cache at /home/inflaton/.cache/huggingface/hub/models--internlm--internlm2_5-7b-chat-1m/snapshots/8d1a709a04d71440ef3df6ebbe204672f411c8b6/model.safetensors.index.json\n","[INFO|modeling_utils.py:1519] 2024-07-23 12:39:25,429 >> Instantiating InternLM2ForCausalLM model under default dtype torch.bfloat16.\n","[INFO|configuration_utils.py:962] 2024-07-23 12:39:25,429 >> Generate config GenerationConfig {\n"," \"bos_token_id\": 1,\n"," \"eos_token_id\": 2,\n"," \"pad_token_id\": 2\n","}\n","\n","Loading checkpoint shards: 100%|██████████████████| 8/8 [00:03<00:00, 2.61it/s]\n","[INFO|modeling_utils.py:4280] 2024-07-23 12:39:28,709 >> All model checkpoint weights were used when initializing InternLM2ForCausalLM.\n","\n","[INFO|modeling_utils.py:4288] 2024-07-23 12:39:28,709 >> All the weights of InternLM2ForCausalLM were initialized from the model checkpoint at internlm/internlm2_5-7b-chat-1m.\n","If your task is similar to the task the model of the checkpoint was trained on, you can already use InternLM2ForCausalLM for predictions without further training.\n","[INFO|configuration_utils.py:917] 2024-07-23 12:39:29,018 >> loading configuration file generation_config.json from cache at /home/inflaton/.cache/huggingface/hub/models--internlm--internlm2_5-7b-chat-1m/snapshots/8d1a709a04d71440ef3df6ebbe204672f411c8b6/generation_config.json\n","[INFO|configuration_utils.py:962] 2024-07-23 12:39:29,018 >> Generate config GenerationConfig {\n"," \"bos_token_id\": 1,\n"," \"eos_token_id\": [\n"," 2,\n"," 92542\n"," ],\n"," \"pad_token_id\": 2\n","}\n","\n","07/23/2024 12:39:29 - INFO - llamafactory.model.model_utils.attention - Using vanilla attention implementation.\n","07/23/2024 12:39:30 - INFO - llamafactory.model.adapter - Merged 1 adapter(s).\n","07/23/2024 12:39:30 - INFO - llamafactory.model.adapter - Loaded adapter(s): inflaton-ai/InternLM_2_5-7b_LoRA-Adapter\n","07/23/2024 12:39:30 - INFO - llamafactory.model.loader - all params: 7,737,708,544\n","(2) GPU = NVIDIA GeForce RTX 4090. Max memory = 23.988 GB.\n","14.818 GB of memory reserved.\n","loading train/test data files\n","Map: 100%|██████████████████████| 25000/25000 [00:00<00:00, 65211.21 examples/s]\n","Map: 100%|██████████████████████| 30000/30000 [00:00<00:00, 78167.21 examples/s]\n","DatasetDict({\n"," train: Dataset({\n"," features: ['text', 'label', 'answer', 'title', 'puzzle', 'truth', 'train_text', 'prompt'],\n"," num_rows: 25000\n"," })\n"," test: Dataset({\n"," features: ['text', 'label', 'answer', 'title', 'puzzle', 'truth', 'train_text', 'prompt'],\n"," num_rows: 30000\n"," })\n","})\n","--------------------------------------------------\n","text: 被人拿走喂给动物了吗\n","--------------------------------------------------\n","label: None\n","--------------------------------------------------\n","answer: nan\n","--------------------------------------------------\n","title: 午餐时间的不翼之谜\n","--------------------------------------------------\n","puzzle: 在学校的午餐时间，甄嘟把他的午餐放在了教室的桌子上，然后去了一趟洗手间。当他回来时，他的午餐却不见了。教室的门窗当时都是关闭的，而且教室里除了甄嘟外，没有其他人。甄嘟的午餐为什么会消失呢？\n","--------------------------------------------------\n","truth: 甄嘟的午餐被一只小老鼠偷走了。当他去洗手间时，小老鼠从一个小洞穴��溜进了教室，发现了放在桌子上的午餐，然后就把午餐吃掉了。当甄嘟回到教室时，发现午餐不见了，于是就产生了这个令人费解的谜团。\n","--------------------------------------------------\n","train_text: \n","--------------------------------------------------\n","prompt: <|im_start|>system\n","You are an expert in logical reasoning.<|im_end|>\n","<|im_start|>user\n","你是一个情景猜谜游戏的主持人。游戏规则如下：\n","\n","1. 参与者会得到一个谜面，谜面会描述一个简单又难以理解的事件。\n","2. 主持人知道谜底，谜底是谜面的答案。\n","3. 参与者可以询问任何封闭式问题来找寻事件的真相。\n","4. 对于每个问题，主持人将根据实际情况回答以下五个选项之一：是、不是、不重要、回答正确、问法错误。各回答的判断标准如下：\n"," - 若谜面和谜底能找到问题的答案，回答：是或者不是\n"," - 若谜面和谜底不能直接或者间接推断出问题的答案，回答：不重要\n"," - 若参与者提问不是一个封闭式问题或者问题难以理解，回答：问法错误\n"," - 若参与者提问基本还原了谜底真相，回答：回答正确\n","5. 回答中不能添加任何其它信息，也不能省略选项中的任何一个字。例如，不可以把“不是”省略成“不”。\n","\n","请严格按照这些规则回答参与者提出的问题。\n","\n","**谜面:** 在学校的午餐时间，甄嘟把他的午餐放在了教室的桌子上，然后去了一趟洗手间。当他回来时，他的午餐却不见了。教室的门窗当时都是关闭的，而且教室里除了甄嘟外，没有其他人。甄嘟的午餐为什么会消失呢？\n","\n","**谜底:** 甄嘟的午餐被一只小老鼠偷走了。当他去洗手间时，小老鼠从一个小洞穴里溜进了教室，发现了放在桌子上的午餐，然后就把午餐吃掉了。当甄嘟回到教室时，发现午餐不见了，于是就产生了这个令人费解的谜团。\n","\n","**参与者提出的问题:** 被人拿走喂给动物了吗\n","<|im_end|>\n","<|im_start|>assistant\n","\n","--------------------------------------------------\n","text: 文件\n","--------------------------------------------------\n","label: None\n","--------------------------------------------------\n","answer: nan\n","--------------------------------------------------\n","title: 车库之谜\n","--------------------------------------------------\n","puzzle: 在一个宁静的夜晚，甄富浩的车库里发生了一起离奇的盗窃案。被盗的物品不是珠宝、现金或其他贵重物品，而是一辆停放在车库里的普通汽车。更令人费解的是，车库的门并没有被撬开，也没有人看到有可疑人物进出。那么，盗贼是如何进入车库并将汽车偷走的呢？\n","--------------------------------------------------\n","truth: 原来，盗贼并不是通过车库的门进入的。他们在前一天晚上将车库的通风管道拆了下来，然后通过通风管道进入了车库。由于通风管道的大小刚好能容纳一个人通过，所以没有人注意到这个异常。在成功进入车库后，盗贼在内部通过开关打开了车库的门，顺利地将汽车偷走。\n","--------------------------------------------------\n","train_text: \n","--------------------------------------------------\n","prompt: <|im_start|>system\n","You are an expert in logical reasoning.<|im_end|>\n","<|im_start|>user\n","你是一个情景猜谜游戏的主持人。游戏规则如下：\n","\n","1. 参与者会得到一个谜面，谜面会描述一个简单又难以理解的事件。\n","2. 主持人知道谜底，谜底是谜面的答案。\n","3. 参与者可以询问任何封闭式问题来找寻事件的真相。\n","4. 对于每个问题，主持人将根据实际情况回答以下五个选项之一：是、不是、不重要、回答正确、问法错误。各回答的判断标准如下：\n"," - 若谜面和谜底能找到问题的答案，回答：是或者不是\n"," - 若谜面和谜底不能直接或者间接推断出问题的答案，回答：不重要\n"," - 若参与者提问不是一个封闭式问题或者问题难以理解，回答：问法错误\n"," - 若参与者提问基本还原了谜底真相，回答：回答正确\n","5. 回答中不能添加任何其它信息，也不能省略选项中的任何一个字。例如，不可以把“不是”省略成“不”。\n","\n","请严格按照这些规则回答参与者提出的问题。\n","\n","**谜面:** 在一个宁静的夜晚，甄富浩的车库里发生了一起离奇的盗窃案。被盗的物品不是珠宝、现金或其他贵重物品，而是一辆停放在车库里的普通汽车。更令人费解的是，车库的门并没有被撬开，也没有人看到有可疑人物进出。那么，盗贼是如何进入车库并将汽车偷走的呢？\n","\n","**谜底:** 原来，盗贼并不是通过车库的门进入的。他们在��一天晚上将车库的通风管道拆了下来，然后通过通风管道进入了车库。由于通风管道的大小刚好能容纳一个人通过，所以没有人注意到这个异常。在成功进入车库后，盗贼在内部通过开关打开了车库的门，顺利地将汽车偷走。\n","\n","**参与者提出的问题:** 文件\n","<|im_end|>\n","<|im_start|>assistant\n","\n","Evaluating model: internlm/internlm2_5-7b-chat-1m\n"," 0%| | 0/30000 [00:00\n","\n","\n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n","
textlabeltitlepuzzletruthanswer
0被人拿走喂给动物了吗NaN午餐时间的不翼之谜在学校的午餐时间，甄嘟把他的午餐放在了教室的桌子上，然后去了一趟洗手间。当他回来时，他的午餐...甄嘟的午餐被一只小老鼠偷走了。当他去洗手间时，小老鼠从一个小洞穴里溜进了教室，发现了放在桌子...不是
1教室里有个洞，从洞里进来把饭给吃掉了NaN午餐时间的不翼之谜在学校的午餐时间，甄嘟把他的午餐放在了教室的桌子上，然后去了一趟洗手间。当他回来时，他的午餐...甄嘟的午餐被一只小老鼠偷走了。当他去洗手间时，小老鼠从一个小洞穴里溜进了教室，发现了放在桌子...回答正确
2甑嘟去上了个洗手间，中途老鼠闻到了午餐的香味，把午餐给吃了NaN午餐时间的不翼之谜在学校的午餐时间，甄嘟把他的午餐放在了教室的桌子上，然后去了一趟洗手间。当他回来时，他的午餐...甄嘟的午餐被一只小老鼠偷走了。当他去洗手间时，小老鼠从一个小洞穴里溜进了教室，发现了放在桌子...回答正确
3是不是被他人吃了NaN午餐时间的不翼之谜在学校的午餐时间，甄嘟把他的午餐放在了教室的桌子上，然后去了一趟洗手间。当他回来时，他的午餐...甄嘟的午餐被一只小老鼠偷走了。当他去洗手间时，小老鼠从一个小洞穴里溜进了教室，发现了放在桌子...不是
4午饭被动物偷了？NaN午餐时间的不翼之谜在学校的午餐时间，甄嘟把他的午餐放在了教室的桌子上，然后去了一趟洗手间。当他回来时，他的午餐...甄嘟的午餐被一只小老鼠偷走了。当他去洗手间时，小老鼠从一个小洞穴里溜进了教室，发现了放在桌子...是
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29995被偷的车上有珠宝吗NaN车库之谜在一个宁静的夜晚，甄富浩的车库里发生了一起离奇的盗窃案。被盗的物品不是珠宝、现金或其他贵重物...原来，盗贼并不是通过车库的门进入的。他们在前一天晚上将车库的通风管道拆了下来，然后通过通风管...不是
29996车窗没关NaN车库之谜在一个宁静的夜晚，甄富浩的车库里发生了一起离奇的盗窃案。被盗的物品不是珠宝、现金或其他贵重物...原来，盗贼并不是通过车库的门进入的。他们在前一天晚上将车库的通风管道拆了下来，然后通过通风管...不重要
29997一个人吗NaN车库之谜在一个宁静的夜晚，甄富浩的车库里发生了一起离奇的盗窃案。被盗的物品不是珠宝、现金或其他贵重物...原来，盗贼并不是通过车库的门进入的。他们在前一天晚上将车库的通风管道拆了下来，然后通过通风管...是
29998车子里面有比较重要的东西吗NaN车库之谜在一个宁静的夜晚，甄富浩的车库里发生了一起离奇的盗窃案。被盗的物品不是珠宝、现金或其他贵重物...原来，盗贼并不是通过车库的门进入的。他们在前一天晚上将车库的通风管道拆了下来，然后通过通风管...不是
29999文件NaN车库之谜在一个宁静的夜晚，甄富浩的车库里发生了一起离奇的盗窃案。被盗的物品不是珠宝、现金或其他贵重物...原来，盗贼并不是通过车库的门进入的。他们在前一天晚上将车库的通风管道拆了下来，然后通过通风管...问法错误
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30000 rows × 6 columns

\n",""],"text/plain":[" text label title \\\n","0 被人拿走喂给动物了吗 NaN 午餐时间的不翼之谜 \n","1 教室里有个洞，从洞里进来把饭给吃掉了 NaN 午餐时间的不翼之谜 \n","2 甑嘟去上了个洗手间，中途老鼠闻到了午餐的香味，把午餐给吃了 NaN 午餐时间的不翼之谜 \n","3 是不是被他人吃了 NaN 午餐时间的不翼之谜 \n","4 午饭被动物偷了？ NaN 午餐时间的不翼之谜 \n","... ... ... ... \n","29995 被偷的车上有珠宝吗 NaN 车库之谜 \n","29996 车窗没关 NaN 车库之谜 \n","29997 一个人吗 NaN 车库之谜 \n","29998 车子里面有比较重要的东西吗 NaN 车库之谜 \n","29999 文件 NaN 车库之谜 \n","\n"," puzzle \\\n","0 在学校的午餐时间，甄嘟把他的午餐放在了教室的桌子上，然后去了一趟洗手间。当他回来时，他的午餐... \n","1 在学校的午餐时间，甄嘟把他的午餐放在了教室的桌子上，然后去了一趟洗手间。当他回来时，他的午餐... \n","2 在学校的午餐时间，甄嘟把他的午餐放在了教室的桌子上，然后去了一趟洗手间。当他回来时，他的午餐... \n","3 在学校的午餐时间，甄嘟把他的午餐放在了教室的桌子上，然后去了一趟洗手间。当他回来时，他的午餐... \n","4 在学校的午餐时间，甄嘟把他的午餐放在了教室的桌子上，然后去了一趟洗手间。当他回来时，他的午餐... \n","... ... \n","29995 在一个宁静的夜晚，甄富浩的车库里发生了一起离奇的盗窃案。被盗的物品不是珠宝、现金或其他贵重物... \n","29996 在一个宁静的夜晚，甄富浩的车库里发生了一起离奇的盗窃案。被盗的物品不是珠宝、现金或其他贵重物... \n","29997 在一个宁静的夜晚，甄富浩的车库里发生了一起离奇的盗窃案。被盗的物品不是珠宝、现金或其他贵重物... \n","29998 在一个宁静的夜晚，甄富浩的车库里发生了一起离奇的盗窃案。被盗的物品不是珠宝、现金或其他贵重物... \n","29999 在一个宁静的夜晚，甄富浩的车库里发生了一起离奇的盗窃案。被盗的物品不是珠宝、现金或其他贵重物... \n","\n"," truth answer \n","0 甄嘟的午餐被一只小老鼠偷走了。当他去洗手间时，小老鼠从一个小洞穴里溜进了教室，发现了放在桌子... 不是 \n","1 甄嘟的午餐被一只小老鼠偷走了。当他去洗手间时，小老鼠从一个小洞穴里溜进了教室，发现了放在桌子... 回答正确 \n","2 甄嘟的午餐被一只小老鼠偷走了。当他去洗手间时，小老鼠从一个小洞穴里溜进了教室，发现了放在桌子... 回答正确 \n","3 甄嘟的午餐被一只小老鼠偷走了。当他去洗手间时，小老鼠从一个小洞穴里溜进了教室，发现了放在桌子... 不是 \n","4 甄嘟的午餐被一只小老鼠偷走了。当他去洗手间时，小老鼠从一个小洞穴里溜进了教室，发现了放在桌子... 是 \n","... ... ... \n","29995 原来，盗贼并不是通过车库的门进入的。他们在前一天晚上将车库的通风管道拆了下来，然后通过通风管... 不是 \n","29996 原来，盗贼并不是通过车库的门进入的。他们在前一天晚上将车库的通风管道拆了下来，然后通过通风管... 不重要 \n","29997 原来，盗贼并不是通过车库的门进入的。他们在前一天晚上将车库的通风管道拆了下来，然后通过通风管... 是 \n","29998 原来，盗贼并不是通过车库的门进入的。他们在前一天晚上将车库的通风管道拆了下来，然后通过通风管... 不是 \n","29999 原来，盗贼并不是通过车库的门进入的。他们在前一天晚上将车库的通风管道拆了下来，然后通过通风管... 问法错误 \n","\n","[30000 rows x 6 columns]"]},"execution_count":10,"metadata":{},"output_type":"execute_result"}],"source":["import pandas as pd\n","\n","df = pd.read_csv(\"results/test_b-results.csv\")\n","df"]},{"cell_type":"code","execution_count":12,"metadata":{},"outputs":[],"source":["import matplotlib.pyplot as plt\n","from matplotlib import rcParams\n","\n","def plot_value_counts(df, column):\n"," font_family = rcParams[\"font.family\"]\n"," # Set the font to SimHei to support Chinese characters\n"," rcParams[\"font.family\"] = \"STHeiti\"\n"," rcParams[\"axes.unicode_minus\"] = False # This is to support the minus sign in Chinese.\n","\n"," plt.figure(figsize=(12, 6))\n"," df[column].value_counts().plot(kind=\"bar\")\n"," # add values on top of bars\n"," for i, v in enumerate(df[column].value_counts()):\n"," plt.text(i, v + 0.1, str(v), ha=\"center\")\n"," plt.show()\n"," \n"," rcParams[\"font.family\"] = font_family\n"]},{"cell_type":"code","execution_count":13,"metadata":{},"outputs":[{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"name":"stdout","output_type":"stream","text":["********** title **********\n","title\n","电梯之谜 7339\n","午餐时间的不翼之谜 6909\n","车库之谜 6234\n","马路奇遇 5448\n","空中之谜 1123\n","神秘的微波炉 627\n","商场的谜团 617\n","监狱的谜团 519\n","郊外的悲剧 504\n","神秘生物 389\n","神秘的纸条 291\n","Name: count, dtype: int64\n"]},{"name":"stderr","output_type":"stream","text":["/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 30005 (\\N{CJK UNIFIED IDEOGRAPH-7535}) missing from font(s) DejaVu Sans.\n"," fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 26799 (\\N{CJK UNIFIED IDEOGRAPH-68AF}) missing from font(s) DejaVu Sans.\n"," fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 20043 (\\N{CJK UNIFIED 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found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"data":{"image/png":"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","text/plain":["
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6234\n","在一条繁忙的马路中间，甄南仁站在那里，不顾周围的车辆喇叭声，他只是低头看着地面，脸上露出困惑和惊讶的表情。警察赶到现场后，甄南仁拒绝解释自己为何站在马路中央，只是反复说：“这不可能，这怎么可能呢？” 5448\n","在一架飞往纽约的飞机上，甄乘客突然倒下，全身抽搐。机长紧急广播，询问是否有医生在飞机上。经过检查，医生表示甄乘客已经死亡，但死因不明。飞机被迫降落，警方和疾控中心介入调查。 1123\n","在一家公司的茶水间里，有一台神秘的微波炉。每天中午，只要经理甄豪霄经过这台微波炉，他都会不由自主地笑出声来。然而，其他员工使用这台微波炉时，却从未发生过类似的情况。请问这是为什么？ 627\n","在一个繁华的商场里，甄男子突然倒地不起，周围的人都被这突如其来的情况吓到了。甄男子身上没有明显的伤口，但他的表情扭曲，看起来非常痛苦。警方到场后，也无法确定他的死因。请你发挥推理能力，找出甄男子真正的死因。 617\n","在一个寂静的夜晚，监狱内发生了一起离奇的死亡事件。甄囚犯在牢房内突然倒下，监狱工作人员发现时，他已经停止呼吸。现场没有明显的痕迹，也没有人听到任何异常的声音。警方调查后，排除了自杀和他杀的可能性，但这起事件仍然令人费解。 519\n","在郊区的一处废弃小屋里，发现了甄冒险的遗体。遗体呈痉挛状，身边散落着一些看似无关的物品：一部旧手机、一根断裂的电线和一个空水杯。初步调查显示，这里没有打斗痕迹，也没有其他人的踪迹。那么，甄冒险究竟是如何死亡的？ 504\n","在一个风和日丽的下午，甄悠闲在公园散步，发现湖边突然聚集了一大群人，他们围观着一只在湖中游弋的“��秘生物”。保安人员已经到场，但无论怎么驱赶，这只生物就是不肯离开。它究竟是什么呢？ 389\n","海边的一个晴朗下午，6岁的甄天真在沙滩上拼命地挖着什么，他的旁边放着一个奇怪的空罐头。突然，甄天真兴奋地跳起来，手里挥舞着一张神秘的纸条。请问发生了什么？ 291\n","Name: count, dtype: int64\n"]},{"data":{"image/png":"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"]},"metadata":{},"output_type":"display_data"},{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n"]},{"name":"stdout","output_type":"stream","text":["********** truth **********\n","truth\n","真相是，这名女子患有严重的幻想症，她误以为自己杀了人，实际上是她的幻觉。那天在电梯里，她把甄职工当成了追捕她的警察。电梯门开后，她进入了一个隐藏的紧急通道，通道内有一个临时休息室，她在那里躲藏了起来。而这个紧急通道由于设计巧妙，监控并未能捕捉到她的行踪，从而给人一种“消失”的错觉。 7339\n","甄嘟的午餐被一只小老鼠偷走了。当他去洗手间时，小老鼠从一个小洞穴里溜进了教室，发现了放在桌子上的午餐，然后就把午餐吃掉了。当甄嘟回到教室时，发现午餐不见了，于是就产生了这个令人费解的谜团。 6909\n","原来，盗贼并不是通过车库的门进入的。他们在前一天晚上将车库的通风管道拆了下来，然后通过通风管道进入了车库。由于通风管道的大小刚好能容纳一个人通过，所以没有人注意到这个异常。在成功进入车库后，盗贼在内部通过开关打开了车库的门，顺利地将汽车偷走。 6234\n","甄南仁几天前在马路边的树旁遗失了婚戒，今天他恰巧在马路对面等待过马路时，无意间看到一个小男孩在马路中间的地面上玩耍，手里正拿着他的婚戒。他感到极度震惊，因为那个地方正是他遗失婚戒的地方，但他无法理解婚戒如何会出现在小男孩手中。由于过于惊讶和困惑，他不顾危险地站在马路中间，试图弄清楚这一切。而小男孩实际上是在甄南仁遗失婚戒的位置附近捡到的，他完全不知道这个戒指对甄南仁来说意味着什么。 5448\n","甄乘客在飞行前曾遭到一只携带狂犬病毒的狗的咬伤。在飞机上，狂犬病发作，最终导致了他的死亡。 1123\n","原来，这台微波炉是公司一位热爱恶作剧的工程师设计的。他在微波炉的顶部安装了一个微型摄像头，并连接到了一个远程控制系统。每当经理甄豪霄靠近微波炉时，他就在远程控制系统中播放一段搞笑语音，使得甄豪霄笑出声来。至于其他员工，由于他们从未引起工程师的注意，所以从未成为恶作剧的对象。 627\n","实际上，甄男子是因为喝酒过量而导致酒精中毒死亡。在商场里的监控录像中，我们可以看到他在生前曾去过酒吧，喝了大量的酒。但由于他死时的症状不典型，没有明显的酒精中毒迹象，所以警方一开始并没有怀疑到这个原因。 617\n","真相是，甄囚犯在牢房内养了一只蜜蜂。他喜欢研究蜜蜂，并希望有一天能利用蜜蜂进行蜂蜜生产。然而，他不知道自己对蜜蜂过敏。在某个晚上，一只蜜蜂飞进了他的牢房，他试图抓住它，却不小心被蜜蜂蛰了一下。由于他对蜜蜂过敏，反应迅速加剧，导致过敏性休克，最终不幸死亡。这起事件在监狱内成为了谜团，直到警方调查后才揭示了真相 519\n","真相是，甄冒险触电身亡。他是一名探险爱好者，听说这废弃小屋曾发生过离奇事件，便独自前来探险。在探险过程中，他不慎碰到了裸露的电线，导致触电。由于身边无人，他无法及时得到救助，最终不幸身亡。旧手机和空水杯是他前来探险时携带的物品。断裂的电线则是他触电后因痉挛而导致的。 504\n","这只神秘的生物其实是一只被公园里的孩子们用彩色颜料涂得五彩斑斓的橡皮鸭子。原来，孩子们为了庆祝即将到来的儿童节，决定给公园里的所有橡皮鸭子来个“大变身”。这只鸭子因为在湖中游得太远，被保安人员发现时已经变得面目全非，让人误以为是什么神秘生物。得知真相的围观群众忍俊不禁，纷纷拿���手机拍照留念，把这个欢乐的场景分享给了更多的人。 389\n","原来，甄天真听说传说中的\"海神宝藏\"就藏在这片沙滩下，而那个空罐头是他自己做的\"宝藏探测器\"。他在沙滩上挖了老半天，终于找到了一张纸条，上面写着：\"宝藏就在你的屁股下面！\" 甄天真兴奋地跳起来，完全没意识到自己其实一直坐在宝藏的位置上——那是一张印刷着\"宝藏位置\"的沙滩椅垫子！这个欢乐的误会，让旁观者都忍俊不禁。而那张神秘的纸条，不过是他妈妈为了让他安静会儿，随意写下的玩笑话。 291\n","Name: count, dtype: int64\n"]},{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 30495 (\\N{CJK UNIFIED IDEOGRAPH-771F}) missing from font(s) DejaVu Sans.\n"," fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 30456 (\\N{CJK UNIFIED IDEOGRAPH-76F8}) missing from font(s) DejaVu Sans.\n"," fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 26159 (\\N{CJK UNIFIED IDEOGRAPH-662F}) missing from font(s) DejaVu Sans.\n"," fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 65292 (\\N{FULLWIDTH 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found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"data":{"image/png":"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","text/plain":["
"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["********** answer **********\n","answer\n","不是 17860\n","是 5561\n","不重要 5053\n","回答正确 1078\n","问法错误 448\n","Name: count, dtype: int64\n"]},{"name":"stderr","output_type":"stream","text":["findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 19981 (\\N{CJK UNIFIED IDEOGRAPH-4E0D}) missing from font(s) DejaVu Sans.\n"," fig.canvas.print_figure(bytes_io, **kw)\n","/home/inflaton/miniconda3/envs/llm-finetuning/lib/python3.11/site-packages/IPython/core/pylabtools.py:170: UserWarning: Glyph 26159 (\\N{CJK UNIFIED IDEOGRAPH-662F}) missing from font(s) DejaVu Sans.\n"," fig.canvas.print_figure(bytes_io, **kw)\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not 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found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n","findfont: Font family 'STHeiti' not found.\n"]},{"data":{"image/png":"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","text/plain":["
"]},"metadata":{},"output_type":"display_data"}],"source":["for col in df.columns[2:]:\n"," print(\"*\" * 10, col, \"*\" * 10)\n"," print(df[col].value_counts())\n"," plot_value_counts(df, col)"]}],"metadata":{"accelerator":"GPU","application/vnd.databricks.v1+notebook":{"dashboards":[],"environmentMetadata":null,"language":"python","notebookMetadata":{"mostRecentlyExecutedCommandWithImplicitDF":{"commandId":-1,"dataframes":["_sqldf"]},"pythonIndentUnit":4},"notebookName":"10_eval-lf-medium-py3.11","widgets":{}},"colab":{"gpuType":"L4","provenance":[]},"kernelspec":{"display_name":"Python 3","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":"3.11.9"}},"nbformat":4,"nbformat_minor":0}