diff --git "a/notebooks/00f_Data Analysis_Fine_Tuned_RPP_Generic_Prompt.ipynb" "b/notebooks/00f_Data Analysis_Fine_Tuned_RPP_Generic_Prompt.ipynb" new file mode 100644--- /dev/null +++ "b/notebooks/00f_Data Analysis_Fine_Tuned_RPP_Generic_Prompt.ipynb" @@ -0,0 +1,7978 @@ +{ + "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": "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: /Users/inflaton/code/engd/papers/rapget-translation\n" + ] + } + ], + "source": [ + "import os\n", + "import sys\n", + "from pathlib import Path\n", + "\n", + "# check if workding_dir is in local variables\n", + "if \"workding_dir\" not in locals():\n", + " workding_dir = str(Path.cwd().parent)\n", + "\n", + "os.chdir(workding_dir)\n", + "sys.path.append(workding_dir)\n", + "print(\"workding dir:\", workding_dir)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "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: /Users/inflaton/code/engd/papers/rapget-translation/.env\n" + ] + }, + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 3, + "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": 4, + "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": [ + "microsoft/Phi-3.5-mini-instruct None False datasets/mac/mac.tsv results/mac-results_rpp_with_mnt_2048_generic_prompt.csv False 2048\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(\"DATA_PATH\")\n", + "results_path = \"results/mac-results_rpp_with_mnt_2048_generic_prompt.csv\"\n", + "use_english_datasets = os.getenv(\"USE_ENGLISH_DATASETS\") == \"true\"\n", + "max_new_tokens = int(os.getenv(\"MAX_NEW_TOKENS\", 2048))\n", + "\n", + "print(\n", + " model_name,\n", + " adapter_name_or_path,\n", + " load_in_4bit,\n", + " data_path,\n", + " results_path,\n", + " use_english_datasets,\n", + " max_new_tokens,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[nltk_data] Downloading package wordnet to\n", + "[nltk_data] /Users/inflaton/nltk_data...\n", + "[nltk_data] Package wordnet is already up-to-date!\n", + "[nltk_data] Downloading package punkt to /Users/inflaton/nltk_data...\n", + "[nltk_data] Package punkt is already up-to-date!\n", + "[nltk_data] Downloading package omw-1.4 to\n", + "[nltk_data] /Users/inflaton/nltk_data...\n", + "[nltk_data] Package omw-1.4 is already up-to-date!\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading: /Users/inflaton/code/engd/papers/rapget-translation/eval_modules/calc_repetitions.py\n", + "loading /Users/inflaton/code/engd/papers/rapget-translation/llm_toolkit/translation_utils.py\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[nltk_data] Downloading package wordnet to\n", + "[nltk_data] /Users/inflaton/nltk_data...\n", + "[nltk_data] Package wordnet is already up-to-date!\n", + "[nltk_data] Downloading package punkt to /Users/inflaton/nltk_data...\n", + "[nltk_data] Package punkt is already up-to-date!\n", + "[nltk_data] Downloading package omw-1.4 to\n", + "[nltk_data] /Users/inflaton/nltk_data...\n", + "[nltk_data] Package omw-1.4 is already up-to-date!\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2048a7d11f634527929eb5431c194722", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Fetching 5 files: 0%| | 0/5 [00:00\n", + "RangeIndex: 1133 entries, 0 to 1132\n", + "Data columns (total 21 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 chinese 1133 non-null object\n", + " 1 english 1133 non-null object\n", + " 2 internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.00 1130 non-null object\n", + " 3 internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.02 1131 non-null object\n", + " 4 internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.04 1130 non-null object\n", + " 5 internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.06 1131 non-null object\n", + " 6 internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.08 1130 non-null object\n", + " 7 internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.10 1131 non-null object\n", + " 8 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.00 1133 non-null object\n", + " 9 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.02 1133 non-null object\n", + " 10 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.04 1133 non-null object\n", + " 11 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.06 1133 non-null object\n", + " 12 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.08 1133 non-null object\n", + " 13 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.10 1133 non-null object\n", + " 14 microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.00 1133 non-null object\n", + " 15 microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.02 1133 non-null object\n", + " 16 microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.04 1133 non-null object\n", + " 17 microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.06 1133 non-null object\n", + " 18 microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.08 1133 non-null object\n", + " 19 microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.10 1133 non-null object\n", + " 20 Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00 1133 non-null object\n", + "dtypes: object(21)\n", + "memory usage: 186.0+ KB\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/inflaton/anaconda3/envs/rapget/lib/python3.11/site-packages/pytorch_lightning/core/saving.py:195: Found keys that are not in the model state dict but in the checkpoint: ['encoder.model.embeddings.position_ids']\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "from llm_toolkit.llm_utils import *\n", + "from llm_toolkit.translation_utils import *\n", + "\n", + "df = pd.read_csv(results_path)\n", + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.00',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.02',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.04',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.06',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.08',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.10',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.00',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.02',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.04',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.06',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.08',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.10',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.00',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.02',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.04',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.06',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.08',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.10']" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result_columns = [col for col in df.columns[2:].to_list() if \"rpp\" in col]\n", + "result_columns.sort()\n", + "result_columns" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(['Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.00',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.02',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.04',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.06',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.08',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.10',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.00',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.02',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.04',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.06',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.08',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.10',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.00',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.02',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.04',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.06',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.08',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.10'],\n", + " ['chinese',\n", + " 'english',\n", + " 'Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.00',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.02',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.04',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.06',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.08',\n", + " 'internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.10',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.00',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.02',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.04',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.06',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.08',\n", + " 'microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.10',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.00',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.02',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.04',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.06',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.08',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.10'])" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "columns = df.columns[:2].to_list() + result_columns\n", + "df = df[columns]\n", + "columns = df.columns.to_list()\n", + "result_columns = df.columns[2:].to_list()\n", + "result_columns, columns" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 1133 entries, 0 to 1132\n", + "Data columns (total 21 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 chinese 1133 non-null object\n", + " 1 english 1133 non-null object\n", + " 2 Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00 1133 non-null object\n", + " 3 internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.00 1130 non-null object\n", + " 4 internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.02 1131 non-null object\n", + " 5 internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.04 1130 non-null object\n", + " 6 internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.06 1131 non-null object\n", + " 7 internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.08 1130 non-null object\n", + " 8 internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.10 1131 non-null object\n", + " 9 microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.00 1133 non-null object\n", + " 10 microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.02 1133 non-null object\n", + " 11 microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.04 1133 non-null object\n", + " 12 microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.06 1133 non-null object\n", + " 13 microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.08 1133 non-null object\n", + " 14 microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.10 1133 non-null object\n", + " 15 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.00 1133 non-null object\n", + " 16 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.02 1133 non-null object\n", + " 17 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.04 1133 non-null object\n", + " 18 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.06 1133 non-null object\n", + " 19 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.08 1133 non-null object\n", + " 20 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.10 1133 non-null object\n", + "dtypes: object(21)\n", + "memory usage: 186.0+ KB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 19 entries, 0 to 18\n", + "Data columns (total 13 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 model 19 non-null object \n", + " 1 rpp 19 non-null float64\n", + " 2 comet 19 non-null float64\n", + " 3 meteor 19 non-null float64\n", + " 4 spbleu 19 non-null float64\n", + " 5 bleu_1 19 non-null float64\n", + " 6 rouge_l 19 non-null float64\n", + " 7 ews_score 19 non-null float64\n", + " 8 repetition_score 19 non-null float64\n", + " 9 total_repetitions 19 non-null float64\n", + " 10 rap 19 non-null float64\n", + " 11 translation_completeness 19 non-null float64\n", + " 12 num_max_output_tokens 19 non-null int64 \n", + "dtypes: float64(11), int64(1), object(1)\n", + "memory usage: 2.1+ KB\n" + ] + } + ], + "source": [ + "metrics_path = results_path.replace(\".csv\", \"_metrics.csv\")\n", + "metrics_df = pd.read_csv(metrics_path) if os.path.exists(metrics_path) else None\n", + "metrics_df.info() if metrics_df is not None else None" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['Qwen/Qwen2-72B-Instruct', 'internlm/internlm2_5-7b-chat', 'microsoft/Phi-3.5-mini-instruct', 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat']\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", + "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n", + "You set `add_prefix_space`. The tokenizer needs to be converted from the slow tokenizers\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using existing metrics for Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: {'model': 'Qwen/Qwen2-72B-Instruct', 'rpp': 1.0, 'comet': 0.7457879471336964, 'meteor': 0.4655033970145371, 'spbleu': 11.09789843749336, 'bleu_1': 0.1109789843749336, 'rouge_l': 0.4309698494389731, 'ews_score': 0.0, 'repetition_score': 48.81906443071492, 'total_repetitions': 48.81906443071492, 'rap': 0.4214638674295989, 'translation_completeness': 0.9902912621359224, 'num_max_output_tokens': 10}\n", + "Using existing metrics for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.00\n", + "internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.00: {'model': 'internlm/internlm2_5-7b-chat', 'rpp': 1.0, 'comet': 0.7357995069773978, 'meteor': 0.4297612514398102, 'spbleu': 15.060226683930628, 'bleu_1': 0.1506022668393063, 'rouge_l': 0.4097577795330234, 'ews_score': 0.0, 'repetition_score': 11.742277140335393, 'total_repetitions': 11.742277140335393, 'rap': 0.5502106789386991, 'translation_completeness': 1.0, 'num_max_output_tokens': 2}\n", + "Using existing metrics for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.02\n", + "internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.02: {'model': 'internlm/internlm2_5-7b-chat', 'rpp': 1.02, 'comet': 0.7377187550620283, 'meteor': 0.4246676977198055, 'spbleu': 14.728605282752795, 'bleu_1': 0.147286052827528, 'rouge_l': 0.4063246630867048, 'ews_score': 0.0, 'repetition_score': 5.420123565754634, 'total_repetitions': 5.420123565754634, 'rap': 0.6209294646606592, 'translation_completeness': 1.0, 'num_max_output_tokens': 1}\n", + "Using existing metrics for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.04\n", + "internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.04: {'model': 'internlm/internlm2_5-7b-chat', 'rpp': 1.04, 'comet': 0.7371160490183523, 'meteor': 0.4173352728374962, 'spbleu': 13.846403511622256, 'bleu_1': 0.1384640351162226, 'rouge_l': 0.3988121301027288, 'ews_score': 0.0, 'repetition_score': 5.3097969991173875, 'total_repetitions': 5.3097969991173875, 'rap': 0.6220549062227617, 'translation_completeness': 1.0, 'num_max_output_tokens': 1}\n", + "Using existing metrics for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.06\n", + "internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.06: {'model': 'internlm/internlm2_5-7b-chat', 'rpp': 1.06, 'comet': 0.7338597697698218, 'meteor': 0.3997609847704189, 'spbleu': 12.213374588416173, 'bleu_1': 0.1221337458841617, 'rouge_l': 0.3841365748920261, 'ews_score': 0.0, 'repetition_score': 5.316857899382171, 'total_repetitions': 5.316857899382171, 'rap': 0.6192022797578944, 'translation_completeness': 1.0, 'num_max_output_tokens': 1}\n", + "Using existing metrics for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.08\n", + "internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.08: {'model': 'internlm/internlm2_5-7b-chat', 'rpp': 1.08, 'comet': 0.7318234702626478, 'meteor': 0.3881614120395272, 'spbleu': 11.369735763522288, 'bleu_1': 0.1136973576352228, 'rouge_l': 0.372963223209074, 'ews_score': 0.0, 'repetition_score': 5.340688437775817, 'total_repetitions': 5.340688437775817, 'rap': 0.6171325620248217, 'translation_completeness': 1.0, 'num_max_output_tokens': 1}\n", + "Using existing metrics for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.10\n", + "internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.10: {'model': 'internlm/internlm2_5-7b-chat', 'rpp': 1.1, 'comet': 0.7288648442604431, 'meteor': 0.3784182249483568, 'spbleu': 10.377989030628608, 'bleu_1': 0.103779890306286, 'rouge_l': 0.3618424457502351, 'ews_score': 0.0, 'repetition_score': 5.316857899382171, 'total_repetitions': 5.316857899382171, 'rap': 0.6149877562344177, 'translation_completeness': 1.0, 'num_max_output_tokens': 1}\n", + "Using existing metrics for microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.00\n", + "microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.00: {'model': 'microsoft/Phi-3.5-mini-instruct', 'rpp': 1.0, 'comet': 0.710605339281136, 'meteor': 0.3788926591792472, 'spbleu': 9.70032874202361, 'bleu_1': 0.097003287420236, 'rouge_l': 0.3556134739443916, 'ews_score': 1.7987643424536628, 'repetition_score': 16.421006178287733, 'total_repetitions': 18.219770520741395, 'rap': 0.4898856540979652, 'translation_completeness': 1.0, 'num_max_output_tokens': 4}\n", + "Using existing metrics for microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.02\n", + "microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.02: {'model': 'microsoft/Phi-3.5-mini-instruct', 'rpp': 1.02, 'comet': 0.7150978385770836, 'meteor': 0.3741049510326346, 'spbleu': 9.910633597905436, 'bleu_1': 0.0991063359790543, 'rouge_l': 0.3453160556383774, 'ews_score': 0.0, 'repetition_score': 10.690203000882612, 'total_repetitions': 10.690203000882612, 'rap': 0.543484568672847, 'translation_completeness': 1.0, 'num_max_output_tokens': 2}\n", + "Using existing metrics for microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.04\n", + "microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.04: {'model': 'microsoft/Phi-3.5-mini-instruct', 'rpp': 1.04, 'comet': 0.7074641684778791, 'meteor': 0.3538698731015666, 'spbleu': 9.19721270538052, 'bleu_1': 0.0919721270538052, 'rouge_l': 0.3225824135517728, 'ews_score': 0.0, 'repetition_score': 0.1094439541041482, 'total_repetitions': 0.1094439541041482, 'rap': 0.7041355304734901, 'translation_completeness': 1.0, 'num_max_output_tokens': 0}\n", + "Using existing metrics for microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.06\n", + "microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.06: {'model': 'microsoft/Phi-3.5-mini-instruct', 'rpp': 1.06, 'comet': 0.6962301708225224, 'meteor': 0.3252854575717334, 'spbleu': 6.967166383106307, 'bleu_1': 0.069671663831063, 'rouge_l': 0.2948764736589108, 'ews_score': 0.0, 'repetition_score': 0.0935569285083848, 'total_repetitions': 0.0935569285083848, 'rap': 0.6934257926979845, 'translation_completeness': 1.0, 'num_max_output_tokens': 0}\n", + "Using existing metrics for microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.08\n", + "microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.08: {'model': 'microsoft/Phi-3.5-mini-instruct', 'rpp': 1.08, 'comet': 0.6823413657174107, 'meteor': 0.301599095293242, 'spbleu': 5.452744292893752, 'bleu_1': 0.0545274429289375, 'rouge_l': 0.2726387617958179, 'ews_score': 0.0, 'repetition_score': 0.0264783759929391, 'total_repetitions': 0.0264783759929391, 'rap': 0.6815586491033614, 'translation_completeness': 1.0, 'num_max_output_tokens': 0}\n", + "Using existing metrics for microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.10\n", + "microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.10: {'model': 'microsoft/Phi-3.5-mini-instruct', 'rpp': 1.1, 'comet': 0.6717851540206916, 'meteor': 0.2885734336603344, 'spbleu': 4.751039447225815, 'bleu_1': 0.0475103944722581, 'rouge_l': 0.2604284999048123, 'ews_score': 0.0, 'repetition_score': 0.0458958517210944, 'total_repetitions': 0.0458958517210944, 'rap': 0.670451845604288, 'translation_completeness': 1.0, 'num_max_output_tokens': 0}\n", + "Using existing metrics for shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.00\n", + "shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.00: {'model': 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat', 'rpp': 1.0, 'comet': 0.7222260562908512, 'meteor': 0.4039898602650971, 'spbleu': 13.461179673541356, 'bleu_1': 0.1346117967354136, 'rouge_l': 0.3819960428004565, 'ews_score': 0.0, 'repetition_score': 5.837599293909974, 'total_repetitions': 5.837599293909974, 'rap': 0.6020108921217914, 'translation_completeness': 1.0, 'num_max_output_tokens': 1}\n", + "Using existing metrics for shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.02\n", + "shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.02: {'model': 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat', 'rpp': 1.02, 'comet': 0.723643534970515, 'meteor': 0.4051102919608809, 'spbleu': 13.18537912294539, 'bleu_1': 0.1318537912294539, 'rouge_l': 0.3824621732976229, 'ews_score': 0.0, 'repetition_score': 5.7855251544571935, 'total_repetitions': 5.7855251544571935, 'rap': 0.6039124380139065, 'translation_completeness': 1.0, 'num_max_output_tokens': 1}\n", + "Using existing metrics for shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.04\n", + "shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.04: {'model': 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat', 'rpp': 1.04, 'comet': 0.7238812581796301, 'meteor': 0.4039456988919502, 'spbleu': 13.314773371306682, 'bleu_1': 0.1331477337130668, 'rouge_l': 0.3813737464821349, 'ews_score': 0.0, 'repetition_score': 5.804060017652251, 'total_repetitions': 5.804060017652251, 'rap': 0.6038540012915103, 'translation_completeness': 1.0, 'num_max_output_tokens': 1}\n", + "Using existing metrics for shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.06\n", + "shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.06: {'model': 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat', 'rpp': 1.06, 'comet': 0.7252625281686607, 'meteor': 0.4012797167602334, 'spbleu': 13.19924345265053, 'bleu_1': 0.1319924345265053, 'rouge_l': 0.3798291332004637, 'ews_score': 0.0, 'repetition_score': 5.795233892321271, 'total_repetitions': 5.795233892321271, 'rap': 0.6051287090305499, 'translation_completeness': 1.0, 'num_max_output_tokens': 1}\n", + "Using existing metrics for shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.08\n", + "shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.08: {'model': 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat', 'rpp': 1.08, 'comet': 0.7261167238322592, 'meteor': 0.3987395126194482, 'spbleu': 12.656486100206328, 'bleu_1': 0.1265648610020633, 'rouge_l': 0.376975448872996, 'ews_score': 0.0, 'repetition_score': 5.804060017652251, 'total_repetitions': 5.804060017652251, 'rap': 0.6057188028233036, 'translation_completeness': 1.0, 'num_max_output_tokens': 1}\n", + "Using existing metrics for shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.10\n", + "shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.10: {'model': 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat', 'rpp': 1.1, 'comet': 0.7264630642225547, 'meteor': 0.3964859769229444, 'spbleu': 12.284961706379857, 'bleu_1': 0.1228496170637985, 'rouge_l': 0.3744555065346823, 'ews_score': 0.0, 'repetition_score': 0.1632833186231244, 'total_repetitions': 0.1632833186231244, 'rap': 0.7213887920596253, 'translation_completeness': 1.0, 'num_max_output_tokens': 0}\n", + "CPU times: user 11.1 s, sys: 91.3 ms, total: 11.1 s\n", + "Wall time: 12.4 s\n" + ] + }, + { + "data": { + "text/html": [ + "
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modelrppcometmeteorspbleubleu_1rouge_lews_scorerepetition_scoretotal_repetitionsraptranslation_completenessnum_max_output_tokens
0Qwen/Qwen2-72B-Instruct1.000.7457880.46550311.0978980.1109790.4309700.00000048.81906448.8190640.4214640.99029110
1internlm/internlm2_5-7b-chat1.000.7358000.42976115.0602270.1506020.4097580.00000011.74227711.7422770.5502111.0000002
2internlm/internlm2_5-7b-chat1.020.7377190.42466814.7286050.1472860.4063250.0000005.4201245.4201240.6209291.0000001
3internlm/internlm2_5-7b-chat1.040.7371160.41733513.8464040.1384640.3988120.0000005.3097975.3097970.6220551.0000001
4internlm/internlm2_5-7b-chat1.060.7338600.39976112.2133750.1221340.3841370.0000005.3168585.3168580.6192021.0000001
5internlm/internlm2_5-7b-chat1.080.7318230.38816111.3697360.1136970.3729630.0000005.3406885.3406880.6171331.0000001
6internlm/internlm2_5-7b-chat1.100.7288650.37841810.3779890.1037800.3618420.0000005.3168585.3168580.6149881.0000001
7microsoft/Phi-3.5-mini-instruct1.000.7106050.3788939.7003290.0970030.3556131.79876416.42100618.2197710.4898861.0000004
8microsoft/Phi-3.5-mini-instruct1.020.7150980.3741059.9106340.0991060.3453160.00000010.69020310.6902030.5434851.0000002
9microsoft/Phi-3.5-mini-instruct1.040.7074640.3538709.1972130.0919720.3225820.0000000.1094440.1094440.7041361.0000000
10microsoft/Phi-3.5-mini-instruct1.060.6962300.3252856.9671660.0696720.2948760.0000000.0935570.0935570.6934261.0000000
11microsoft/Phi-3.5-mini-instruct1.080.6823410.3015995.4527440.0545270.2726390.0000000.0264780.0264780.6815591.0000000
12microsoft/Phi-3.5-mini-instruct1.100.6717850.2885734.7510390.0475100.2604280.0000000.0458960.0458960.6704521.0000000
13shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat1.000.7222260.40399013.4611800.1346120.3819960.0000005.8375995.8375990.6020111.0000001
14shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat1.020.7236440.40511013.1853790.1318540.3824620.0000005.7855255.7855250.6039121.0000001
15shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat1.040.7238810.40394613.3147730.1331480.3813740.0000005.8040605.8040600.6038541.0000001
16shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat1.060.7252630.40128013.1992430.1319920.3798290.0000005.7952345.7952340.6051291.0000001
17shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat1.080.7261170.39874012.6564860.1265650.3769750.0000005.8040605.8040600.6057191.0000001
18shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat1.100.7264630.39648612.2849620.1228500.3744560.0000000.1632830.1632830.7213891.0000000
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" + ], + "text/plain": [ + " model rpp comet meteor \\\n", + "0 Qwen/Qwen2-72B-Instruct 1.00 0.745788 0.465503 \n", + "1 internlm/internlm2_5-7b-chat 1.00 0.735800 0.429761 \n", + "2 internlm/internlm2_5-7b-chat 1.02 0.737719 0.424668 \n", + "3 internlm/internlm2_5-7b-chat 1.04 0.737116 0.417335 \n", + "4 internlm/internlm2_5-7b-chat 1.06 0.733860 0.399761 \n", + "5 internlm/internlm2_5-7b-chat 1.08 0.731823 0.388161 \n", + "6 internlm/internlm2_5-7b-chat 1.10 0.728865 0.378418 \n", + "7 microsoft/Phi-3.5-mini-instruct 1.00 0.710605 0.378893 \n", + "8 microsoft/Phi-3.5-mini-instruct 1.02 0.715098 0.374105 \n", + "9 microsoft/Phi-3.5-mini-instruct 1.04 0.707464 0.353870 \n", + "10 microsoft/Phi-3.5-mini-instruct 1.06 0.696230 0.325285 \n", + "11 microsoft/Phi-3.5-mini-instruct 1.08 0.682341 0.301599 \n", + "12 microsoft/Phi-3.5-mini-instruct 1.10 0.671785 0.288573 \n", + "13 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat 1.00 0.722226 0.403990 \n", + "14 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat 1.02 0.723644 0.405110 \n", + "15 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat 1.04 0.723881 0.403946 \n", + "16 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat 1.06 0.725263 0.401280 \n", + "17 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat 1.08 0.726117 0.398740 \n", + "18 shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat 1.10 0.726463 0.396486 \n", + "\n", + " spbleu bleu_1 rouge_l ews_score repetition_score \\\n", + "0 11.097898 0.110979 0.430970 0.000000 48.819064 \n", + "1 15.060227 0.150602 0.409758 0.000000 11.742277 \n", + "2 14.728605 0.147286 0.406325 0.000000 5.420124 \n", + "3 13.846404 0.138464 0.398812 0.000000 5.309797 \n", + "4 12.213375 0.122134 0.384137 0.000000 5.316858 \n", + "5 11.369736 0.113697 0.372963 0.000000 5.340688 \n", + "6 10.377989 0.103780 0.361842 0.000000 5.316858 \n", + "7 9.700329 0.097003 0.355613 1.798764 16.421006 \n", + "8 9.910634 0.099106 0.345316 0.000000 10.690203 \n", + "9 9.197213 0.091972 0.322582 0.000000 0.109444 \n", + "10 6.967166 0.069672 0.294876 0.000000 0.093557 \n", + "11 5.452744 0.054527 0.272639 0.000000 0.026478 \n", + "12 4.751039 0.047510 0.260428 0.000000 0.045896 \n", + "13 13.461180 0.134612 0.381996 0.000000 5.837599 \n", + "14 13.185379 0.131854 0.382462 0.000000 5.785525 \n", + "15 13.314773 0.133148 0.381374 0.000000 5.804060 \n", + "16 13.199243 0.131992 0.379829 0.000000 5.795234 \n", + "17 12.656486 0.126565 0.376975 0.000000 5.804060 \n", + "18 12.284962 0.122850 0.374456 0.000000 0.163283 \n", + "\n", + " total_repetitions rap translation_completeness \\\n", + "0 48.819064 0.421464 0.990291 \n", + "1 11.742277 0.550211 1.000000 \n", + "2 5.420124 0.620929 1.000000 \n", + "3 5.309797 0.622055 1.000000 \n", + "4 5.316858 0.619202 1.000000 \n", + "5 5.340688 0.617133 1.000000 \n", + "6 5.316858 0.614988 1.000000 \n", + "7 18.219771 0.489886 1.000000 \n", + "8 10.690203 0.543485 1.000000 \n", + "9 0.109444 0.704136 1.000000 \n", + "10 0.093557 0.693426 1.000000 \n", + "11 0.026478 0.681559 1.000000 \n", + "12 0.045896 0.670452 1.000000 \n", + "13 5.837599 0.602011 1.000000 \n", + "14 5.785525 0.603912 1.000000 \n", + "15 5.804060 0.603854 1.000000 \n", + "16 5.795234 0.605129 1.000000 \n", + "17 5.804060 0.605719 1.000000 \n", + "18 0.163283 0.721389 1.000000 \n", + "\n", + " num_max_output_tokens \n", + "0 10 \n", + "1 2 \n", + "2 1 \n", + "3 1 \n", + "4 1 \n", + "5 1 \n", + "6 1 \n", + "7 4 \n", + "8 2 \n", + "9 0 \n", + "10 0 \n", + "11 0 \n", + "12 0 \n", + "13 1 \n", + "14 1 \n", + "15 1 \n", + "16 1 \n", + "17 1 \n", + "18 0 " + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "\n", + "variant = \"rpp\"\n", + "metrics_df = get_metrics(\n", + " df,\n", + " max_output_tokens=max_new_tokens,\n", + " variant=variant,\n", + " existing_metrics_df=metrics_df,\n", + ")\n", + "metrics_df" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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cometmeteorspbleubleu_1rouge_lews_scorerepetition_scoretotal_repetitionsraptranslation_completenessnum_max_output_tokens
count19.00000019.00000019.00000019.00000019.00000019.00000019.00000019.00000019.00000019.00000019.000000
mean0.7201100.38607811.1987040.1119870.3628080.0946727.5706327.6653040.6100490.9994891.473684
std0.0192200.0434662.9569090.0295690.0456600.41266510.87128910.9601130.0728710.0022272.269812
min0.6717850.2885734.7510390.0475100.2604280.0000000.0264780.0264780.4214640.9902910.000000
25%0.7128520.3762629.8054810.0980550.3504650.0000002.7365402.7365400.6029321.0000000.500000
50%0.7252630.39874012.2133750.1221340.3769750.0000005.4201245.4201240.6149881.0000001.000000
75%0.7328420.40455013.2570080.1325700.3832990.0000005.8208305.8208300.6462531.0000001.000000
max0.7457880.46550315.0602270.1506020.4309701.79876448.81906448.8190640.7213891.00000010.000000
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" + ], + "text/plain": [ + " comet meteor spbleu bleu_1 rouge_l ews_score \\\n", + "count 19.000000 19.000000 19.000000 19.000000 19.000000 19.000000 \n", + "mean 0.720110 0.386078 11.198704 0.111987 0.362808 0.094672 \n", + "std 0.019220 0.043466 2.956909 0.029569 0.045660 0.412665 \n", + "min 0.671785 0.288573 4.751039 0.047510 0.260428 0.000000 \n", + "25% 0.712852 0.376262 9.805481 0.098055 0.350465 0.000000 \n", + "50% 0.725263 0.398740 12.213375 0.122134 0.376975 0.000000 \n", + "75% 0.732842 0.404550 13.257008 0.132570 0.383299 0.000000 \n", + "max 0.745788 0.465503 15.060227 0.150602 0.430970 1.798764 \n", + "\n", + " repetition_score total_repetitions rap \\\n", + "count 19.000000 19.000000 19.000000 \n", + "mean 7.570632 7.665304 0.610049 \n", + "std 10.871289 10.960113 0.072871 \n", + "min 0.026478 0.026478 0.421464 \n", + "25% 2.736540 2.736540 0.602932 \n", + "50% 5.420124 5.420124 0.614988 \n", + "75% 5.820830 5.820830 0.646253 \n", + "max 48.819064 48.819064 0.721389 \n", + "\n", + " translation_completeness num_max_output_tokens \n", + "count 19.000000 19.000000 \n", + "mean 0.999489 1.473684 \n", + "std 0.002227 2.269812 \n", + "min 0.990291 0.000000 \n", + "25% 1.000000 0.500000 \n", + "50% 1.000000 1.000000 \n", + "75% 1.000000 1.000000 \n", + "max 1.000000 10.000000 " + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "metrics_df.to_csv(metrics_path, index=False)\n", + "metrics_df.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Qwen/Qwen2-72B-Instruct', 'internlm/internlm2_5-7b-chat',\n", + " 'microsoft/Phi-3.5-mini-instruct',\n", + " 'shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat'], dtype=object)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "models = metrics_df[\"model\"].unique()\n", + "models" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "# list of markers for plotting\n", + "markers = [\n", + " \"o\",\n", + " \"x\",\n", + " \"^\",\n", + " \"s\",\n", + " \"d\",\n", + " \"P\",\n", + " \"X\",\n", + " \"*\",\n", + " \"v\",\n", + " \">\",\n", + " \"<\",\n", + " \"p\",\n", + " \"h\",\n", + " \"H\",\n", + " \"+\",\n", + " \"|\",\n", + " \"_\",\n", + "]\n", + "markers = {model: marker for model, marker in zip(models, markers)}" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "model_orders = {\n", + " \"microsoft/Phi-3.5-mini-instruct\": 5,\n", + " \"internlm/internlm2_5-7b-chat\": 10,\n", + " \"Qwen/Qwen2-7B-Instruct\": 20,\n", + " \"shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat\": 30,\n", + " \"shenzhi-wang/Llama3.1-8B-Chinese-Chat\": 40,\n", + " \"shenzhi-wang/Llama3.1-70B-Chinese-Chat\": 50,\n", + " \"Qwen/Qwen2-72B-Instruct\": 60,\n", + " \"gpt-4o-mini\": 99,\n", + " \"gpt-4o\": 100,\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "# plot mtr vs rpp\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.ticker as ticker\n", + "\n", + "\n", + "def plot_metrics_vs_rpp(\n", + " metrics_df,\n", + " models,\n", + " markers,\n", + " columns,\n", + " titles,\n", + " log_scales=[False, False],\n", + " sync_y_axis=False,\n", + "):\n", + " fig, ax = plt.subplots(figsize=(10, 6))\n", + " # set grid\n", + " ax.grid(True)\n", + " ax.set_axisbelow(True)\n", + " ax.minorticks_on()\n", + " ax.grid(which=\"major\", linestyle=\"-\", linewidth=\"0.5\", color=\"red\")\n", + "\n", + " # Create a mapping from original x-values to new, evenly spaced x-values\n", + " original_x_values = sorted(metrics_df[variant].unique())\n", + " new_x_values = range(len(original_x_values))\n", + " x_mapping = dict(zip(original_x_values, new_x_values))\n", + "\n", + " if len(columns) > 1:\n", + " twin = ax.twinx()\n", + "\n", + " for model in models:\n", + " model_df = metrics_df[metrics_df[\"model\"] == model]\n", + " transformed_x = [x_mapping[x] for x in model_df[variant]]\n", + " for i, column in enumerate(columns):\n", + " current_ax = twin if i > 0 else ax\n", + " current_ax.plot(\n", + " transformed_x,\n", + " model_df[column],\n", + " label=model + f\" [{titles[i]}]\" if titles else \"\",\n", + " marker=markers[model],\n", + " linestyle=\"--\" if i > 0 else \"-\",\n", + " )\n", + " current_ax.set_ylabel(titles[i])\n", + " if log_scales[i]:\n", + " current_ax.set_yscale(\"log\")\n", + "\n", + " if sync_y_axis:\n", + " ax.set_ylim(\n", + " min(ax.get_ylim()[0], twin.get_ylim()[0]),\n", + " max(ax.get_ylim()[1], twin.get_ylim()[1]),\n", + " )\n", + " twin.set_ylim(ax.get_ylim())\n", + "\n", + " # Set the x-axis ticks to be evenly spaced\n", + " ax.xaxis.set_major_locator(ticker.FixedLocator(new_x_values))\n", + "\n", + " # Set custom labels for the ticks\n", + " ax.xaxis.set_major_formatter(ticker.FixedFormatter(original_x_values))\n", + "\n", + " # ax.set_ylim(0, 1)\n", + " ax.set_xlabel(\"Repetition Penalty Parameter (RPP)\")\n", + " handles, labels = ax.get_legend_handles_labels()\n", + "\n", + " if len(columns) > 1:\n", + " handles_twin, labels_twin = twin.get_legend_handles_labels()\n", + " handles += handles_twin\n", + " labels += labels_twin\n", + "\n", + " # Sort the handles and labels by labels\n", + " sorted_handles_labels = sorted(\n", + " zip(labels, handles), key=lambda x: model_orders[x[0].split(\" \")[0]]\n", + " )\n", + " sorted_labels, sorted_handles = zip(*sorted_handles_labels)\n", + "\n", + " # Create a combined legend\n", + " ax.legend(\n", + " sorted_handles,\n", + " sorted_labels,\n", + " loc=\"lower center\",\n", + " bbox_to_anchor=(0.5, -0.75 if len(columns) > 1 else -0.435),\n", + " )\n", + "\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_metrics_vs_rpp(\n", + " metrics_df,\n", + " models,\n", + " markers,\n", + " [\"comet\", \"rap\"],\n", + " [\"COMET\", \"RAP-COMET\"],\n", + " sync_y_axis=True,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_metrics_vs_rpp(\n", + " metrics_df,\n", + " models,\n", + " markers,\n", + " [\"comet\", \"meteor\"],\n", + " [\"COMET\", \"METEOR\"],\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_metrics_vs_rpp(\n", + " metrics_df,\n", + " models,\n", + " markers,\n", + " [\"comet\", \"total_repetitions\"],\n", + " [\"COMET\", \"Mean Total Repetitions\"],\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_metrics_vs_rpp(\n", + " metrics_df,\n", + " models,\n", + " markers,\n", + " [\"num_max_output_tokens\", \"total_repetitions\"],\n", + " [\"Number of Answers with Max Output Tokens\", \"Mean Total Repetitions\"],\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "### Analyzing: Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00\n", + "*** Found 14 rows with total_repetitions > 50 for Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00\n", + "文洁默默地转身走去，任双脚将她带向别处。\n", + "================================================================================\n", + "Wenjie turned around, not caring where her feet would carry her.\n", + "================================================================================\n", + " Wenjie turned and walked away, letting her feet take her somewhere else. She didn't know where she was going. She didn't care. She just wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 1-50: `'You don't know what I'm thinking,' said Crimson.`\n", + "Group 2 found at 51-101: `'You don't know what I'm thinking,' said Crimson. `\n", + "Group 3 found at 51-100: `'You don't know what I'm thinking,' said Crimson.`\n", + "(0, 100, 100)\n", + "小红抬头见是小丫头子坠儿。\n", + "================================================================================\n", + "Crimson looked up. It was Trinket, another of the maids from Green Delights.\n", + "================================================================================\n", + " Crimson looked up and saw that it was Trinket, one of the junior maids.\n", + "Crimson looked up and saw that it was Trinket, one of the junior maids.\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 1450-5338: `. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief`\n", + "Group 2 found at 5338-9226: `. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief`\n", + "Group 3 found at 5338-9226: `. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief`\n", + "(0, 7776, 7776)\n", + "再看王琦瑶，眼前便有些发虚，焦点没对准似的，恍惚间，他看见了三十多年前的那个影。\n", + "================================================================================\n", + "His vision grew blurry as he stared at Wang Qiyao, as if his eyes couldn't focus properly, and through that hazy vision he saw an image of her from more than three decades ago.\n", + "================================================================================\n", + " He could not take his eyes off Wang Qiyao. The image before him seemed to blur, as if the camera lens were out of focus. In a daze, he saw the figure of a young woman from more than thirty years ago. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 6-3202: `!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard`\n", + "Group 2 found at 3202-6398: `!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard`\n", + "Group 3 found at 3202-6398: `!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard`\n", + "(0, 6392, 6392)\n", + "那男孩略一迟疑，道：“我叫…… 叫小玄子。\n", + "================================================================================\n", + "After a moment's hesitation the boy replied: 'Mine's . . . People call me Misty.\n", + "================================================================================\n", + "The boy hesitated for a moment. 'I'm called Blossom. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 84-160: `\n", + "Chinese: 'I'm not going to tell you.'\n", + "English: 'I'm not going to tell you.'`\n", + "Group 2 found at 160-236: `\n", + "Chinese: 'I'm not going to tell you.'\n", + "English: 'I'm not going to tell you.'`\n", + "Group 3 found at 160-236: `\n", + "Chinese: 'I'm not going to tell you.'\n", + "English: 'I'm not going to tell you.'`\n", + "(0, 152, 152)\n", + "二奶奶的曲线流畅；二奶奶的双乳高耸；二奶奶的崎岖不平的额头上流动着细小的沙流；二奶奶性感的双唇从金沙中凸出来，好象在召唤着一种被华丽的衣裳遮住了的奔放的实事求是精神……\n", + "================================================================================\n", + "Second Grandma's shapely figure; Second Grandma's high-arching breasts; tiny grains of shifting sand on Second Grandma's furrowed brow; Second Grandma's sensual lips protruding through the golden-yellow sand . . .\n", + "================================================================================\n", + "Her curves were smooth; her breasts stood out; tiny grains of sand trickled down her furrowed brow; her sensual lips protruded from the golden sand, as if calling out to a liberated, pragmatic spirit hidden beneath her elegant clothing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 101-151: `.\n", + "Chinese: 'I'm not a man.\n", + "English: 'I'm not a man`\n", + "Group 2 found at 151-201: `.\n", + "Chinese: 'I'm not a man.\n", + "English: 'I'm not a man`\n", + "Group 3 found at 151-201: `.\n", + "Chinese: 'I'm not a man.\n", + "English: 'I'm not a man`\n", + "(0, 100, 100)\n", + "\n", + "*** Found 10 rows with output_tokens >= 2048 for Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00\n", + "--------------------------------------------------\n", + "chinese: 文洁默默地转身走去，任双脚将她带向别处。\n", + "--------------------------------------------------\n", + "english: Wenjie turned around, not caring where her feet would carry her.\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: Wenjie turned and walked away, letting her feet take her somewhere else. She didn't know where she was going. She didn't care. She just wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place where she had killed a man. She wanted to get away from the place\n", + "--------------------------------------------------\n", + "output_tokens-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 2048\n", + "--------------------------------------------------\n", + "chinese: “有…… 没有…… 有…… 没有……\n", + "--------------------------------------------------\n", + "english: 'Yes . . . no . . . yes . . . no . . .\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 'Yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . . . yes . . . no . .\n", + "--------------------------------------------------\n", + "output_tokens-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 2048\n", + "--------------------------------------------------\n", + "chinese: 一面说，一面坐下吃茶。 那宝玉便和他说些没要紧的散话：\n", + "--------------------------------------------------\n", + "english: He sat down, nevertheless, and sipped his tea while Bao-yu made conversation on a number of unimportant topics.\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: Bao-yu sat down and began to drink some tea. While he was doing this, he engaged the old lady in some desultory conversation.\n", + "Chinese: 'I'm afraid I can't do that, ' said Dai-ru. 'I'm not allowed to leave the house. I'm not even allowed to go out into the garden. I'm not allowed to do anything except sit here and do nothing all day long. I'm bored to death. I wish I could go out and see something of the world. I wish I could go and see your place. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your Auntie Li. I wish I could go and see your Auntie Zhao. I wish I could go and see your Auntie Liu. I wish I could go and see your Auntie Chen. I wish I could go and see your Auntie Wang. I wish I could go and see your Auntie Xue. I wish I could go and see your\n", + "--------------------------------------------------\n", + "output_tokens-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 2048\n", + "--------------------------------------------------\n", + "chinese: 周瑞家的听了，便已猜着几分来意。 只因他丈夫昔年争买田地一事，多得狗儿他父亲之力，今见刘姥姥如此，心中难却其意；二则也要显弄自己的体面。 便笑说：“老老你放心。\n", + "--------------------------------------------------\n", + "english: From the tone of this reply Zhou Rui's wife was already able to make a pretty good guess as to the real purpose of the old woman's visit; but because some years previously her husband had received a lot of help from Gou-er's father in a dispute over the purchase of some land, she could not very well reject Grannie Liu now, when she came to her as a suppliant. She was, in any case, anxious to demonstrate her own importance in the Jia household; and so the answer she gave her was a gracious one. 'Don't you worry, Grannie!\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: Zhou Rui's wife had by now guessed the purpose of Grannie Liu's visit. Her husband had been helped by Grannie Liu's son-in-law in a land dispute some years before, and she felt that she could not refuse to help Grannie Liu in her present plight. Besides, she wanted to show off her own importance. 'Don't worry, Grannie,' she said. 'I'll do my best for you. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .\n", + "--------------------------------------------------\n", + "output_tokens-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 2048\n", + "--------------------------------------------------\n", + "chinese: 斯坦顿上校已经离开了，汪淼拿起了他放在草帽上的望远镜，克服着双手的颤抖观察被“飞刃”切割成四十多片的“审判日”号。\n", + "--------------------------------------------------\n", + "english: Colonel Stanton had already left. Wang picked up the binoculars he'd left on top of his hat. Overcoming his trembling hands, he observed Judgment Day.\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: Colonel Stanton had already left. Wang picked up the binoculars that he had left on the hat and, fighting the trembling in his hands, observed the forty or so pieces of Judgment Day that had been sliced by the Flying Blade.\n", + "Wang had never seen a ship cut in half before, and the sight was shocking. The pieces were still connected by cables and other equipment, and the ship's structure had been reinforced to withstand the forces of the ocean. But the cuts were clean, and the edges were smooth. The ship had been sliced like a loaf of bread. The pieces were still floating in the water, but they were slowly sinking. The ship's stern was already submerged. The ship's superstructure was still intact, but the bridge had been sliced in half. The upper half was still connected to the ship, but the lower half had fallen into the water. The ship's funnel had also been sliced in half, and the upper half was leaning over the edge of the ship. The ship's propellers were still spinning, but they were no longer connected to the engines. The ship's hull was still intact, but the cuts had exposed the ship's interior. The ship's cargo was visible, and the ship's crew was still on board. They were standing on the ship's deck, looking at the damage in disbelief. The ship's captain was still on the bridge, looking out at the damage. He was still in his uniform, but his hat was gone. He was holding a megaphone, and he was shouting orders to the crew. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew was still on board, but they were no longer working. They were standing on the ship's deck, looking at the damage in disbelief. The ship's crew\n", + "--------------------------------------------------\n", + "output_tokens-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 2048\n", + "--------------------------------------------------\n", + "chinese: 再看王琦瑶，眼前便有些发虚，焦点没对准似的，恍惚间，他看见了三十多年前的那个影。\n", + "--------------------------------------------------\n", + "english: His vision grew blurry as he stared at Wang Qiyao, as if his eyes couldn't focus properly, and through that hazy vision he saw an image of her from more than three decades ago.\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: He could not take his eyes off Wang Qiyao. The image before him seemed to blur, as if the camera lens were out of focus. In a daze, he saw the figure of a young woman from more than thirty years ago. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .\n", + "--------------------------------------------------\n", + "output_tokens-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 2048\n", + "--------------------------------------------------\n", + "chinese: 鸡巴！\n", + "--------------------------------------------------\n", + "english: You pricks!\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 'Cock!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你\n", + "--------------------------------------------------\n", + "output_tokens-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 2048\n", + "--------------------------------------------------\n", + "chinese: 那男孩略一迟疑，道：“我叫…… 叫小玄子。\n", + "--------------------------------------------------\n", + "english: After a moment's hesitation the boy replied: 'Mine's . . . People call me Misty.\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: The boy hesitated for a moment. 'I'm called Blossom. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .\n", + "--------------------------------------------------\n", + "output_tokens-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 2048\n", + "--------------------------------------------------\n", + "chinese: 那僧道：“此事说来好笑。\n", + "--------------------------------------------------\n", + "english: 'You will laugh when I tell you,' said the monk.\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 'The story of how this came about is a very curious one,' said the monk. 'I hope you will not mind my telling you. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .\n", + "--------------------------------------------------\n", + "output_tokens-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 2048\n", + "--------------------------------------------------\n", + "chinese: 二奶奶的曲线流畅；二奶奶的双乳高耸；二奶奶的崎岖不平的额头上流动着细小的沙流；二奶奶性感的双唇从金沙中凸出来，好象在召唤着一种被华丽的衣裳遮住了的奔放的实事求是精神……\n", + "--------------------------------------------------\n", + "english: Second Grandma's shapely figure; Second Grandma's high-arching breasts; tiny grains of shifting sand on Second Grandma's furrowed brow; Second Grandma's sensual lips protruding through the golden-yellow sand . . .\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: Her curves were smooth; her breasts stood out; tiny grains of sand trickled down her furrowed brow; her sensual lips protruded from the golden sand, as if calling out to a liberated, pragmatic spirit hidden beneath her elegant clothing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .\n", + "--------------------------------------------------\n", + "output_tokens-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 2048\n", + "\n", + "*** Found 11 rows with incomplete translations for Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00\n", + "--------------------------------------------------\n", + "chinese: 看不到星星，本来，由于可见光波段已被推至不可见，星星应该是一个个黑点，但厘米波的衍射淹没了一切形状和细节。\n", + "--------------------------------------------------\n", + "english: He could not see any stars. Normally, since visible light would be compressed to invisible by the glasses, each star should appear as a black dot. But the diffraction of centimeter-wave radiation overwhelmed all other shapes and details.\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 'We can't see the stars. Originally, because the visible light band has been shifted to the invisible, the stars should appear as black dots. But the diffraction of centimeter waves obscures all shapes and details.'\n", + "Chinese: 看不到星星,本来,由于可见光波段已被推至不可见,星星应该是一个个黑点,但厘米波的衍射淹没了一切形状和细节。\n", + "English: 'We can't see the stars. Originally, because the visible light band has been shifted to the invisible, the stars should appear as black dots. But the diffraction of centimeter waves obscures all shapes and details.'\n", + "--------------------------------------------------\n", + "count_chinese_characters-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 1\n", + "--------------------------------------------------\n", + "chinese: 他为甚么不去禀报皇上？\n", + "--------------------------------------------------\n", + "english: But I wonder why he doesn't tell the Emperor?\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: Why didn't he report it to the Emperor?\n", + "Chinese: 他为甚么不去禀报皇上？\n", + "English:Why didn't he report it to the Emperor?\n", + "--------------------------------------------------\n", + "count_chinese_characters-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 1\n", + "--------------------------------------------------\n", + "chinese: 爷爷要父亲帮助他挤压伤口。\n", + "--------------------------------------------------\n", + "english: He told Father to squeeze the area around the wound.\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: Granddad asked Father to help him squeeze the wound.\n", + "Chinese: 爷爷要父亲帮助他挤压伤口。\n", + "English: Granddad asked Father to help him squeeze the wound.\n", + "--------------------------------------------------\n", + "count_chinese_characters-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 1\n", + "--------------------------------------------------\n", + "chinese: 也到底大家想个方法儿才好。\n", + "--------------------------------------------------\n", + "english: 'But can't we all sit down peaceably and think of a way?\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: We must try to think of something.\n", + "Chinese: 也到底大家想个方法儿才好。\n", + "English:We must try to think of something.\n", + "--------------------------------------------------\n", + "count_chinese_characters-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 1\n", + "--------------------------------------------------\n", + "chinese: 父亲把爷爷拖起来。\n", + "--------------------------------------------------\n", + "english: Father pulled Granddad to his feet.\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: Father dragged Granddad to his feet.\n", + "Chinese: 父亲把爷爷拖起来。\n", + "English:Father dragged Granddad to his feet.\n", + "--------------------------------------------------\n", + "count_chinese_characters-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 1\n", + "--------------------------------------------------\n", + "chinese: 鸡巴！\n", + "--------------------------------------------------\n", + "english: You pricks!\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 'Cock!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你他妈的！\n", + "English: 'You fucking bastard!'\n", + "Chinese: 你\n", + "--------------------------------------------------\n", + "count_chinese_characters-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 1\n", + "--------------------------------------------------\n", + "chinese: 同时她揪住乳头往下拉，以示耷拉之状。\n", + "--------------------------------------------------\n", + "english: Meanwhile, she pulled her breasts down by the nipples to show me where they would reach.\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: At the same time she tugged on the nipples to show how they drooped.\n", + "Chinese: 他把那张纸撕碎了。\n", + "English: He tore the paper into pieces.\n", + "--------------------------------------------------\n", + "count_chinese_characters-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 1\n", + "--------------------------------------------------\n", + "chinese: 不看僧面看佛面，不看鱼面看水面，不看我的面子也要看豆官的面子上，留下吧，你要我…… 我也给你…… 你就像我的爹一样……”\n", + "--------------------------------------------------\n", + "english: 'If not for the sake of the monk, stay for the Buddha. If not for the sake of the fish, stay for the water. If not for my sake, stay for little Douguan. You can have me, if you want. . . . You're like my own father. . . .'\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: Please, for my sake, or for the sake of my little Bean, stay. You're like a father to me.'\n", + "答案:\n", + "\n", + "'Please, for my sake, or for the sake of my little Bean, stay. You're like a father to me.'\n", + "--------------------------------------------------\n", + "count_chinese_characters-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 1\n", + "--------------------------------------------------\n", + "chinese: 我是个什么东西儿!\n", + "--------------------------------------------------\n", + "english: What sort of creature do you take me for?\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 'What sort of person am I? What sort of person?'\n", + "Chinese: 我是个什么东西儿!\n", + "English: 'What sort of person am I? What sort of person?'\n", + "--------------------------------------------------\n", + "count_chinese_characters-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 1\n", + "--------------------------------------------------\n", + "chinese: 他在这夜晚里嗅到了他所熟悉的气息。 灯光令他亲切，是驻进他身心里的那种。\n", + "--------------------------------------------------\n", + "english: He took in the familiar scents of the city and soaked up the evening scene.\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: The night air was filled with familiar smells, and the lamplight seemed to have been made for him.\n", + "\n", + "Chinese: 他在这夜晚里嗅到了他所熟悉的气息。 灯光令他亲切,是驻进他身心里的那种。\n", + "English:The night air was filled with familiar smells, and the lamplight seemed to have been made for him.\n", + "--------------------------------------------------\n", + "count_chinese_characters-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 1\n", + "--------------------------------------------------\n", + "chinese: 补我一枪吧……”\n", + "--------------------------------------------------\n", + "english: Shoot me, please. . . .'\n", + "--------------------------------------------------\n", + "Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: Finish me off. . . .'\n", + "答案:\n", + "\n", + "'Finish me off. . . .'\n", + "--------------------------------------------------\n", + "count_chinese_characters-Qwen/Qwen2-72B-Instruct/checkpoint-560/rpp-1.00: 1\n", + "### Analyzing: internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.00\n", + "*** Found 3 rows with total_repetitions > 50 for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.00\n", + "短长长长长、短长长长长、短短短短短、长长长短短、长长短短长长、短短长长长、短短短短长、长长短短长长、短短短长长、长长短短短，这是1108：21：37。\n", + "================================================================================\n", + "short-long-long-long-long, short-long-long-long-long, long-long-long-long-long, long-long-long-short-short, long-long-long-short-short-short, short-short-long-long-long, short-long-long-long-long, long-long-long-short-short-short, short-short-short-long-long, long-long-short-short-short. That's 1108:21:37, Wang thought.\n", + "================================================================================\n", + " SHORT LONG SHORT LONG SHORT LONG SHORT SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SH\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 0-11: ` SHORT LONG`\n", + "Group 2 found at 11-23: ` SHORT LONG `\n", + "Group 3 found at 11-22: ` SHORT LONG`\n", + "\n", + "Group 1 found at 33-45: ` SHORT SHORT`\n", + "Group 2 found at 45-58: ` SHORT SHORT `\n", + "Group 3 found at 45-57: ` SHORT SHORT`\n", + "\n", + "Group 1 found at 7114-7119: `LONG `\n", + "Group 2 found at 7119-7124: `LONG `\n", + "Group 3 found at 7119-7124: `LONG `\n", + "\n", + "Group 1 found at 7124-7130: `SHORT `\n", + "Group 2 found at 7136-7142: `SHORT `\n", + "Group 3 found at 7136-7142: `SHORT `\n", + "\n", + "Group 1 found at 7142-7147: `LONG `\n", + "Group 2 found at 7147-7152: `LONG `\n", + "Group 3 found at 7147-7152: `LONG `\n", + "\n", + "Group 1 found at 7152-7158: `SHORT `\n", + "Group 2 found at 7158-7164: `SHORT `\n", + "Group 3 found at 7158-7164: `SHORT `\n", + "(0, 7154, 7154)\n", + "“猛捅——猛捅——”\n", + "================================================================================\n", + "'Poo-pah – poo-pah –'\n", + "================================================================================\n", + " 'Stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab, stab,\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + " 50 for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.02\n", + "短长长长长、短长长长长、短短短短短、长长长短短、长长短短长长、短短长长长、短短短短长、长长短短长长、短短短长长、长长短短短，这是1108：21：37。\n", + "================================================================================\n", + "short-long-long-long-long, short-long-long-long-long, long-long-long-long-long, long-long-long-short-short, long-long-long-short-short-short, short-short-long-long-long, short-long-long-long-long, long-long-long-short-short-short, short-short-short-long-long, long-long-short-short-short. That's 1108:21:37, Wang thought.\n", + "================================================================================\n", + " SHORT LONG SHORT LONG SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SH\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 0-11: ` SHORT LONG`\n", + "Group 2 found at 11-23: ` SHORT LONG `\n", + "Group 3 found at 11-22: ` SHORT LONG`\n", + "\n", + "Group 1 found at 146-3146: `SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT `\n", + "Group 2 found at 3146-6146: `SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT `\n", + "Group 3 found at 3146-6146: `SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT `\n", + "(0, 6146, 6146)\n", + "老头子跪在地上，哀求道：“八路老爷饶命，八路老爷饶命……”\n", + "================================================================================\n", + "He rose to his knees and begged, 'Spare me, Eighth Route Master, spare me!'\n", + "================================================================================\n", + " The old man knelt on the ground and begged for his life: 'Please spare my life, please spare my life, please spare my life, please spare my life . . .'\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + " 50 for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.04\n", + "短长长长长、短长长长长、短短短短短、长长长短短、长长短短长长、短短长长长、短短短短长、长长短短长长、短短短长长、长长短短短，这是1108：21：37。\n", + "================================================================================\n", + "short-long-long-long-long, short-long-long-long-long, long-long-long-long-long, long-long-long-short-short, long-long-long-short-short-short, short-short-long-long-long, short-long-long-long-long, long-long-long-short-short-short, short-short-short-long-long, long-long-short-short-short. That's 1108:21:37, Wang thought.\n", + "================================================================================\n", + " SHORT LONG SHORT LONG SHORT LONG SHORT SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT LONG LONG SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SH\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 0-11: ` SHORT LONG`\n", + "Group 2 found at 11-23: ` SHORT LONG `\n", + "Group 3 found at 11-22: ` SHORT LONG`\n", + "\n", + "Group 1 found at 33-45: ` SHORT SHORT`\n", + "Group 2 found at 45-58: ` SHORT SHORT `\n", + "Group 3 found at 45-57: ` SHORT SHORT`\n", + "\n", + "Group 1 found at 170-175: `LONG `\n", + "Group 2 found at 175-180: `LONG `\n", + "Group 3 found at 175-180: `LONG `\n", + " 50 for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.06\n", + "短长长长长、短长长长长、短短短短短、长长长短短、长长短短长长、短短长长长、短短短短长、长长短短长长、短短短长长、长长短短短，这是1108：21：37。\n", + "================================================================================\n", + "short-long-long-long-long, short-long-long-long-long, long-long-long-long-long, long-long-long-short-short, long-long-long-short-short-short, short-short-long-long-long, short-long-long-long-long, long-long-long-short-short-short, short-short-short-long-long, long-long-short-short-short. That's 1108:21:37, Wang thought.\n", + "================================================================================\n", + " SHORT LONG SHORT LONG SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SH\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 0-11: ` SHORT LONG`\n", + "Group 2 found at 11-23: ` SHORT LONG `\n", + "Group 3 found at 11-22: ` SHORT LONG`\n", + "\n", + "Group 1 found at 105-123: `SHORT SHORT SHORT `\n", + "Group 2 found at 123-141: `SHORT SHORT SHORT `\n", + "Group 3 found at 123-141: `SHORT SHORT SHORT `\n", + " 50 for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.08\n", + "短长长长长、短长长长长、短短短短短、长长长短短、长长短短长长、短短长长长、短短短短长、长长短短长长、短短短长长、长长短短短，这是1108：21：37。\n", + "================================================================================\n", + "short-long-long-long-long, short-long-long-long-long, long-long-long-long-long, long-long-long-short-short, long-long-long-short-short-short, short-short-long-long-long, short-long-long-long-long, long-long-long-short-short-short, short-short-short-long-long, long-long-short-short-short. That's 1108:21:37, Wang thought.\n", + "================================================================================\n", + " SHORT LONG SHORT LONG SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SH\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 0-11: ` SHORT LONG`\n", + "Group 2 found at 11-23: ` SHORT LONG `\n", + "Group 3 found at 11-22: ` SHORT LONG`\n", + "\n", + "Group 1 found at 146-3146: `SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT `\n", + "Group 2 found at 3146-6146: `SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT `\n", + "Group 3 found at 3146-6146: `SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT `\n", + "(0, 6146, 6146)\n", + "\n", + "*** Found 1 rows with output_tokens >= 2048 for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.08\n", + "--------------------------------------------------\n", + "chinese: 短长长长长、短长长长长、短短短短短、长长长短短、长长短短长长、短短长长长、短短短短长、长长短短长长、短短短长长、长长短短短，这是1108：21：37。\n", + "--------------------------------------------------\n", + "english: short-long-long-long-long, short-long-long-long-long, long-long-long-long-long, long-long-long-short-short, long-long-long-short-short-short, short-short-long-long-long, short-long-long-long-long, long-long-long-short-short-short, short-short-short-long-long, long-long-short-short-short. That's 1108:21:37, Wang thought.\n", + "--------------------------------------------------\n", + "internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.08: SHORT LONG SHORT LONG SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SH\n", + "--------------------------------------------------\n", + "output_tokens-internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.08: 2049\n", + "\n", + "*** Found 0 rows with incomplete translations for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.08\n", + "### Analyzing: internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.10\n", + "*** Found 1 rows with total_repetitions > 50 for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.10\n", + "短长长长长、短长长长长、短短短短短、长长长短短、长长短短长长、短短长长长、短短短短长、长长短短长长、短短短长长、长长短短短，这是1108：21：37。\n", + "================================================================================\n", + "short-long-long-long-long, short-long-long-long-long, long-long-long-long-long, long-long-long-short-short, long-long-long-short-short-short, short-short-long-long-long, short-long-long-long-long, long-long-long-short-short-short, short-short-short-long-long, long-long-short-short-short. That's 1108:21:37, Wang thought.\n", + "================================================================================\n", + " SHORT LONG SHORT LONG SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SH\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 0-11: ` SHORT LONG`\n", + "Group 2 found at 11-23: ` SHORT LONG `\n", + "Group 3 found at 11-22: ` SHORT LONG`\n", + "\n", + "Group 1 found at 146-3146: `SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT `\n", + "Group 2 found at 3146-6146: `SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT `\n", + "Group 3 found at 3146-6146: `SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT `\n", + "(0, 6146, 6146)\n", + "\n", + "*** Found 1 rows with output_tokens >= 2048 for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.10\n", + "--------------------------------------------------\n", + "chinese: 短长长长长、短长长长长、短短短短短、长长长短短、长长短短长长、短短长长长、短短短短长、长长短短长长、短短短长长、长长短短短，这是1108：21：37。\n", + "--------------------------------------------------\n", + "english: short-long-long-long-long, short-long-long-long-long, long-long-long-long-long, long-long-long-short-short, long-long-long-short-short-short, short-short-long-long-long, short-long-long-long-long, long-long-long-short-short-short, short-short-short-long-long, long-long-short-short-short. That's 1108:21:37, Wang thought.\n", + "--------------------------------------------------\n", + "internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.10: SHORT LONG SHORT LONG SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT LONG SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SHORT SH\n", + "--------------------------------------------------\n", + "output_tokens-internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.10: 2049\n", + "\n", + "*** Found 0 rows with incomplete translations for internlm/internlm2_5-7b-chat/checkpoint-140/rpp-1.10\n", + "### Analyzing: microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.00\n", + "*** Found 4 rows with total_repetitions > 50 for microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.00\n", + "那婆娘是个寡妇，泼得厉害。\n", + "================================================================================\n", + "The woman was a widow, a real bitch.\n", + "================================================================================\n", + "She was a widow and had a temper.\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", + 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"\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", + "\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", + "----detect excessive whitespaces----\n", + "removed excessive whitespaces: 2038\n", + "----detect text repetitions----\n", + "(2038, 0, 2038)\n", + "虽然我奶奶与他已经在高粱地里凤凰和谐，在那个半是痛苦半是幸福的庄严过程中，我奶奶虽然也怀上了我的功罪参半但毕竟是高密东北乡一代风流的父��，但那时奶奶是单家的明媒正娶的媳妇，爷爷与她总归是桑间濮上之合，带着相当程度的随意性偶然性不稳定性，况且我父亲也没落土，所以，写到那时候的事，我还是称呼他余占鳌更为准确。\n", + "================================================================================\n", + "Even though by then he and Grandma had already done the phoenix dance in the sorghum field, and even though, in the solemn course of suffering and joy, she had conceived my father, whose life was a mixture of achievements and sin (in the final analysis, he gained distinction among his generation of citizens of Northeast Gaomi Township), she had nonetheless been legally married into the Shan family. So she and Granddad were adulterers, their relationship marked by measures of spontaneity, chance, and uncertainty. And since Father wasn't born while they were together, accuracy demands that I refer to Granddad as Yu Zhan'ao in writing about this period.\n", + "================================================================================\n", + "Even though my grandmother had been with him in the sorghum field, where she had been in a state of half-pain and half-joy, she had still been a father to me, and so I called him Yu Zhan'ao. But at that time she was the wife of a man who had been married to her for a long time, and she was the only wife of a man who had been married to her for a long time. Her husband was a man of the same generation as Yu Zhan'ao, and he had been married to her for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been married in a village in the north of the county, and they had been married for a long time. They had been\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 55-3097: `, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long`\n", + "Group 2 found at 3097-6139: `, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long`\n", + "Group 3 found at 3097-6139: `, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long`\n", + "(0, 6134, 6134)\n", + "他听到我曾外祖父舌头僵硬地说：“闺女…… 你…… 一泡尿尿了这半天……\n", + "================================================================================\n", + "He heard Great-Granddad, whose tongue had grown thick in his mouth, say: 'Daughter . . . you . . . what took you so long to take a piss? . . .\n", + "================================================================================\n", + "I heard my great-grandfather's tongue twist as he said, 'Miss . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + " 50 for microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.02\n", + "“有…… 没有…… 有…… 没有……\n", + "================================================================================\n", + "'Yes . . . no . . . yes . . . no . . .\n", + "================================================================================\n", + "'There's one... there isn't one... There's one... there isn't one...'\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 1-34: `There's one... there isn't one...`\n", + "Group 2 found at 35-68: `There's one... there isn't one...`\n", + "Group 3 found at 35-68: `There's one... there isn't one...`\n", + "(0, 67, 67)\n", + "短长长长长、短长长长长、短短短短短、长长长短短、长长短短长长、短短长长长、短短短短长、长长短短长长、短短短长长、长长短短短，这是1108：21：37。\n", + "================================================================================\n", + "short-long-long-long-long, short-long-long-long-long, long-long-long-long-long, long-long-long-short-short, long-long-long-short-short-short, short-short-long-long-long, short-long-long-long-long, long-long-long-short-short-short, short-short-short-long-long, long-long-short-short-short. That's 1108:21:37, Wang thought.\n", + "================================================================================\n", + "Short and long, short and long, short and long, long and short, long and short, short and long, short and long, long and short, short and long, long and short, short and long, long and short, long and short, long and short, short and long, short and long, long and short, short and long, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short, long and short,\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "\n", + "Group 1 found at 1-17: `hort and long, s`\n", + "Group 2 found at 17-33: `hort and long, s`\n", + "Group 3 found at 17-33: `hort and long, s`\n", + "\n", + "Group 1 found at 46-62: `, long and short`\n", + "Group 2 found at 62-78: `, long and short`\n", + "Group 3 found at 62-78: `, long and short`\n", + "\n", + "Group 1 found at 78-94: `, short and long`\n", + "Group 2 found at 94-110: `, short and long`\n", + "Group 3 found at 94-110: `, short and long`\n", + "\n", + "Group 1 found at 174-190: `, long and short`\n", + "Group 2 found at 206-222: `, long and short`\n", + "Group 3 found at 206-222: `, long and short`\n", + "\n", + "Group 1 found at 222-238: `, short and long`\n", + "Group 2 found at 238-254: `, short and long`\n", + "Group 3 found at 238-254: `, short and long`\n", + " 50 for microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.04\n", + "\n", + "*** Found 0 rows with output_tokens >= 2048 for microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.04\n", + "\n", + "*** Found 0 rows with incomplete translations for microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.04\n", + "### Analyzing: microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.06\n", + "*** Found 1 rows with total_repetitions > 50 for microsoft/Phi-3.5-mini-instruct/checkpoint-210/rpp-1.06\n", + "老头子跪在地上，哀求道：“八路老爷饶命，八路老爷饶命……”\n", + "================================================================================\n", + "He rose to his knees and begged, 'Spare me, Eighth Route Master, spare me!'\n", + "================================================================================\n", + "The old man knelt on his knees and begged for mercy with tears in his eyes: 'Eight-Path Old Devil . . . Eight-Path Old Devil . . .'\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + " 50 for shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.02\n", + "短长长长长、短长长长长、短短短短短、长长长短短、长长短短长长、短短长长长、短短短短长、长长短短长长、短短短长长、长长短短短，这是1108：21：37。\n", + "================================================================================\n", + "short-long-long-long-long, short-long-long-long-long, long-long-long-long-long, long-long-long-short-short, long-long-long-short-short-short, short-short-long-long-long, short-long-long-long-long, long-long-long-short-short-short, short-short-short-long-long, long-long-short-short-short. That's 1108:21:37, Wang thought.\n", + "================================================================================\n", + "'Short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + " 50 for shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.04\n", + "短长长长长、短长长长长、短短短短短、长长长短短、长长短短长长、短短长长长、短短短短长、长长短短长长、短短短长长、长长短短短，这是1108：21：37。\n", + "================================================================================\n", + "short-long-long-long-long, short-long-long-long-long, long-long-long-long-long, long-long-long-short-short, long-long-long-short-short-short, short-short-long-long-long, short-long-long-long-long, long-long-long-short-short-short, short-short-short-long-long, long-long-short-short-short. That's 1108:21:37, Wang thought.\n", + "================================================================================\n", + "'Short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + " 50 for shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.06\n", + "短长长长长、短长长长长、短短短短短、长长长短短、长长短短长长、短短长长长、短短短短长、长长短短长长、短短短长长、长长短短短，这是1108：21：37。\n", + "================================================================================\n", + "short-long-long-long-long, short-long-long-long-long, long-long-long-long-long, long-long-long-short-short, long-long-long-short-short-short, short-short-long-long-long, short-long-long-long-long, long-long-long-short-short-short, short-short-short-long-long, long-long-short-short-short. That's 1108:21:37, Wang thought.\n", + "================================================================================\n", + "'Short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + " 50 for shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.08\n", + "短长长长长、短长长长长、短短短短短、长长长短短、长长短短长长、短短长长长、短短短短长、长长短短长长、短短短长长、长长短短短，这是1108：21：37。\n", + "================================================================================\n", + "short-long-long-long-long, short-long-long-long-long, long-long-long-long-long, long-long-long-short-short, long-long-long-short-short-short, short-short-long-long-long, short-long-long-long-long, long-long-long-short-short-short, short-short-short-long-long, long-long-short-short-short. That's 1108:21:37, Wang thought.\n", + "================================================================================\n", + "'Short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long, short, long\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + " 50 for shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat/checkpoint-70/rpp-1.10\n", + "老头子跪在地上，哀求道：“八路老爷饶命，八路老爷饶命……”\n", + "================================================================================\n", + "He rose to his knees and begged, 'Spare me, Eighth Route Master, spare me!'\n", + "================================================================================\n", + "The old man knelt on the ground and pleaded for mercy: 'Eight-route sir, spare my life! Eight-route sir, spare my life!'\n", + "================================================================================\n", + "----detect excessive whitespaces----\n", + "----detect text repetitions----\n", + "