{"cells":[{"cell_type":"code","execution_count":24,"metadata":{"executionInfo":{"elapsed":476,"status":"ok","timestamp":1720679526275,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"uWKRSV6eZsCn"},"outputs":[{"name":"stdout","output_type":"stream","text":["The autoreload extension is already loaded. To reload it, use:\n"," %reload_ext autoreload\n"]}],"source":["%load_ext autoreload\n","%autoreload 2"]},{"cell_type":"code","execution_count":25,"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":26,"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":26,"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":27,"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":["Qwen/Qwen2-7B-Instruct None False datasets/mac/mac.tsv results/mac-results_greedy_decoding.csv\n"]}],"source":["import os\n","\n","model_name = os.getenv(\"MODEL_NAME\")\n","adapter_name_or_path = os.getenv(\"ADAPTER_NAME_OR_PATH\")\n","load_in_4bit = os.getenv(\"LOAD_IN_4BIT\") == \"true\"\n","data_path = os.getenv(\"DATA_PATH\")\n","results_path = \"results/mac-results_greedy_decoding.csv\" # os.getenv(\"RESULTS_PATH\")\n","use_english_datasets = os.getenv(\"USE_ENGLISH_DATASETS\") == \"true\"\n","\n","print(model_name, adapter_name_or_path, load_in_4bit, data_path, results_path)"]},{"cell_type":"code","execution_count":28,"metadata":{"application/vnd.databricks.v1+cell":{"cellMetadata":{"byteLimit":2048000,"rowLimit":10000},"inputWidgets":{},"nuid":"b2a43943-9324-4839-9a47-cfa72de2244b","showTitle":false,"title":""},"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":564,"status":"ok","timestamp":1720679529907,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"UgMvt6dIZBrM","outputId":"ce37581c-fd26-46c2-ad87-d933d99f68f7"},"outputs":[{"name":"stdout","output_type":"stream","text":["Python 3.11.9\n","Name: torch\n","Version: 2.4.0\n","Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration\n","Home-page: https://pytorch.org/\n","Author: PyTorch Team\n","Author-email: packages@pytorch.org\n","License: BSD-3\n","Location: /Users/inflaton/anaconda3/envs/rapget/lib/python3.11/site-packages\n","Requires: filelock, fsspec, jinja2, networkx, sympy, typing-extensions\n","Required-by: accelerate, peft, torchaudio, torchvision\n","---\n","Name: transformers\n","Version: 4.43.3\n","Summary: State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow\n","Home-page: https://github.com/huggingface/transformers\n","Author: The Hugging Face team (past and future) with the help of all our contributors (https://github.com/huggingface/transformers/graphs/contributors)\n","Author-email: transformers@huggingface.co\n","License: Apache 2.0 License\n","Location: /Users/inflaton/anaconda3/envs/rapget/lib/python3.11/site-packages\n","Requires: filelock, huggingface-hub, numpy, packaging, pyyaml, regex, requests, safetensors, tokenizers, tqdm\n","Required-by: peft\n","CPU times: user 8.7 ms, sys: 12.4 ms, total: 21.1 ms\n","Wall time: 1.9 s\n"]}],"source":["%%time\n","os.environ[\"TOKENIZERS_PARALLELISM\"] = \"true\"\n","\n","!python --version\n","!pip show torch transformers"]},{"cell_type":"code","execution_count":29,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":1685,"status":"ok","timestamp":1720679531591,"user":{"displayName":"HUANG DONGHAO _","userId":"00977795705617022768"},"user_tz":-480},"id":"ZuS_FsLyZBrN","outputId":"2cba0105-c505-4395-afbd-2f2fee6581d0"},"outputs":[{"name":"stdout","output_type":"stream","text":["MPS is available\n"]}],"source":["from llm_toolkit.llm_utils import *\n","from llm_toolkit.translation_utils import *\n","\n","device = check_gpu()"]},{"cell_type":"code","execution_count":30,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["\n","RangeIndex: 1133 entries, 0 to 1132\n","Data columns (total 25 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/Qwen2-7B-Instruct/rpp-1.00 1133 non-null object\n"," 3 Qwen/Qwen2-7B-Instruct/rpp-1.02 1133 non-null object\n"," 4 Qwen/Qwen2-7B-Instruct/rpp-1.04 1133 non-null object\n"," 5 Qwen/Qwen2-7B-Instruct/rpp-1.06 1133 non-null object\n"," 6 Qwen/Qwen2-7B-Instruct/rpp-1.08 1133 non-null object\n"," 7 Qwen/Qwen2-7B-Instruct/rpp-1.10 1133 non-null object\n"," 8 Qwen/Qwen2-7B-Instruct/rpp-1.12 1133 non-null object\n"," 9 Qwen/Qwen2-7B-Instruct/rpp-1.14 1133 non-null object\n"," 10 Qwen/Qwen2-7B-Instruct/rpp-1.16 1133 non-null object\n"," 11 Qwen/Qwen2-7B-Instruct/rpp-1.18 1133 non-null object\n"," 12 Qwen/Qwen2-7B-Instruct/rpp-1.20 1133 non-null object\n"," 13 Qwen/Qwen2-7B-Instruct/rpp-1.22 1133 non-null object\n"," 14 Qwen/Qwen2-7B-Instruct/rpp-1.24 1133 non-null object\n"," 15 Qwen/Qwen2-7B-Instruct/rpp-1.26 1133 non-null object\n"," 16 Qwen/Qwen2-7B-Instruct/rpp-1.28 1133 non-null object\n"," 17 Qwen/Qwen2-7B-Instruct/rpp-1.30 1133 non-null object\n"," 18 internlm/internlm2_5-7b-chat-1m/rpp-1.00 1133 non-null object\n"," 19 internlm/internlm2_5-7b-chat-1m/rpp-1.02 1133 non-null object\n"," 20 Qwen/Qwen2-72B-Instruct/rpp-1.00 1133 non-null object\n"," 21 shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.00 1133 non-null object\n"," 22 shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.02 1133 non-null object\n"," 23 shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.04 1133 non-null object\n"," 24 shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.06 1133 non-null object\n","dtypes: object(25)\n","memory usage: 221.4+ KB\n"]}],"source":["import pandas as pd\n","\n","df = pd.read_csv(results_path)\n","df.info()"]},{"cell_type":"code","execution_count":31,"metadata":{},"outputs":[{"data":{"text/plain":["['chinese',\n"," 'english',\n"," 'Qwen/Qwen2-72B-Instruct/rpp-1.00',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.00',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.02',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.04',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.06',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.08',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.10',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.12',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.14',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.16',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.18',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.20',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.22',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.24',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.26',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.28',\n"," 'Qwen/Qwen2-7B-Instruct/rpp-1.30',\n"," 'internlm/internlm2_5-7b-chat-1m/rpp-1.00',\n"," 'internlm/internlm2_5-7b-chat-1m/rpp-1.02',\n"," 'shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.00',\n"," 'shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.02',\n"," 'shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.04',\n"," 'shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.06']"]},"execution_count":31,"metadata":{},"output_type":"execute_result"}],"source":["columns = df.columns[2:].to_list()\n","columns.sort()\n","columns = df.columns[:2].to_list() + columns\n","columns"]},{"cell_type":"code","execution_count":32,"metadata":{},"outputs":[],"source":["df = df[columns]"]},{"cell_type":"code","execution_count":33,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Qwen/Qwen2-72B-Instruct/rpp-1.00: {'meteor': 0.39496912014495184, 'bleu_scores': {'bleu': 0.12294894050451377, 'precisions': [0.42391407360606537, 0.1626695498329074, 0.079349416448331, 0.041761041902604754], 'brevity_penalty': 1.0, 'length_ratio': 1.048526001987413, 'translation_length': 31655, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.44242617045618315, 'rouge2': 0.19166824249542752, 'rougeL': 0.3835643396648639, 'rougeLsum': 0.3844919778233326}, 'accuracy': 0.0, 'correct_ids': []}\n","Qwen/Qwen2-7B-Instruct/rpp-1.00: {'meteor': 0.3757937058055942, 'bleu_scores': {'bleu': 0.11257687997946404, 'precisions': [0.4221057489451477, 0.15152552819915763, 0.07046669041681511, 0.03563738956121464], 'brevity_penalty': 1.0, 'length_ratio': 1.004836038423319, 'translation_length': 30336, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.4241235957669323, 'rouge2': 0.17433830983598061, 'rougeL': 0.3642501836106533, 'rougeLsum': 0.364584190239183}, 'accuracy': 0.00088261253309797, 'correct_ids': [364]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.02: {'meteor': 0.3768162203335968, 'bleu_scores': {'bleu': 0.11553860771639841, 'precisions': [0.421923611570795, 0.15446511467968776, 0.07288535852297123, 0.03751491646778043], 'brevity_penalty': 1.0, 'length_ratio': 1.0007949652202717, 'translation_length': 30214, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.4273577053163239, 'rouge2': 0.1800744214940156, 'rougeL': 0.3695393969769755, 'rougeLsum': 0.36955057550298287}, 'accuracy': 0.00176522506619594, 'correct_ids': [364, 659]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.04: {'meteor': 0.3715147429622351, 'bleu_scores': {'bleu': 0.11311605625702598, 'precisions': [0.41758205508824014, 0.15180590775135358, 0.07144639737602053, 0.036148159155923766], 'brevity_penalty': 1.0, 'length_ratio': 1.0041404438555812, 'translation_length': 30315, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.41870140882606066, 'rouge2': 0.17377238271646123, 'rougeL': 0.3637109748338643, 'rougeLsum': 0.3636218000079854}, 'accuracy': 0.00264783759929391, 'correct_ids': [240, 364, 533]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.06: {'meteor': 0.3721614566005243, 'bleu_scores': {'bleu': 0.10986034422062402, 'precisions': [0.41770767752410615, 0.14848860428286167, 0.06846272346218608, 0.03435399551904406], 'brevity_penalty': 0.9996355745538857, 'length_ratio': 0.9996356409407089, 'translation_length': 30179, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.41850128527699093, 'rouge2': 0.17078364572425722, 'rougeL': 0.36087822210596066, 'rougeLsum': 0.36118431102497384}, 'accuracy': 0.00264783759929391, 'correct_ids': [240, 364, 659]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.08: {'meteor': 0.3712966405354824, 'bleu_scores': {'bleu': 0.10809530671609749, 'precisions': [0.41541684679591634, 0.14717672264842077, 0.06768566804531559, 0.033518296340731855], 'brevity_penalty': 0.9960505187431468, 'length_ratio': 0.9960582974494866, 'translation_length': 30071, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.4182834195898706, 'rouge2': 0.17246572493226453, 'rougeL': 0.3594012849048782, 'rougeLsum': 0.35954397088231455}, 'accuracy': 0.00264783759929391, 'correct_ids': [240, 364, 659]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.10: {'meteor': 0.3713527017404089, 'bleu_scores': {'bleu': 0.10809698094017595, 'precisions': [0.4147023571713943, 0.145728817077812, 0.06795102628736047, 0.03393775575327552], 'brevity_penalty': 0.9948859408394681, 'length_ratio': 0.9948989731699238, 'translation_length': 30036, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.41773046267654856, 'rouge2': 0.17260745480056372, 'rougeL': 0.3594686692074592, 'rougeLsum': 0.35936406339125093}, 'accuracy': 0.00264783759929391, 'correct_ids': [364, 533, 659]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.12: {'meteor': 0.36820419885143935, 'bleu_scores': {'bleu': 0.10505573355971856, 'precisions': [0.4098240955857949, 0.14277339035072595, 0.06492248062015504, 0.03232202311922487], 'brevity_penalty': 0.9980106107363413, 'length_ratio': 0.9980125869493209, 'translation_length': 30130, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.41529417030158233, 'rouge2': 0.16878067248558315, 'rougeL': 0.3583796005764026, 'rougeLsum': 0.3583877478177061}, 'accuracy': 0.00176522506619594, 'correct_ids': [364, 659]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.14: {'meteor': 0.36307746488229864, 'bleu_scores': {'bleu': 0.10051614663163566, 'precisions': [0.4013952416992991, 0.13692917692097348, 0.06165771788216051, 0.030122267506483884], 'brevity_penalty': 1.0, 'length_ratio': 1.0065915866180855, 'translation_length': 30389, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.40811191571085215, 'rouge2': 0.16172547308011448, 'rougeL': 0.34960574280699774, 'rougeLsum': 0.3496392100850815}, 'accuracy': 0.00264783759929391, 'correct_ids': [240, 364, 658]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.16: {'meteor': 0.36060381551154586, 'bleu_scores': {'bleu': 0.09572351387840275, 'precisions': [0.3943648240226187, 0.13195897159052566, 0.05795474478161726, 0.027838667251205613], 'brevity_penalty': 1.0, 'length_ratio': 1.019244783040742, 'translation_length': 30771, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.40695948021161266, 'rouge2': 0.16078136792998138, 'rougeL': 0.35054008230260014, 'rougeLsum': 0.35063402472045585}, 'accuracy': 0.00176522506619594, 'correct_ids': [364, 533]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.18: {'meteor': 0.36078545841521914, 'bleu_scores': {'bleu': 0.09571300097111912, 'precisions': [0.3949360480292352, 0.13088260206674573, 0.05813543795363258, 0.027927630371756763], 'brevity_penalty': 1.0, 'length_ratio': 1.0151705862868499, 'translation_length': 30648, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.404989374187655, 'rouge2': 0.15814652869870766, 'rougeL': 0.34417758327892045, 'rougeLsum': 0.3446171215887235}, 'accuracy': 0.00264783759929391, 'correct_ids': [240, 364, 659]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.20: {'meteor': 0.3567548354175595, 'bleu_scores': {'bleu': 0.0912485469982839, 'precisions': [0.3872236189002772, 0.12631719800622218, 0.05570236439499304, 0.025445200521210368], 'brevity_penalty': 1.0, 'length_ratio': 1.0276912885061278, 'translation_length': 31026, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.40377684729404284, 'rouge2': 0.1571965940862049, 'rougeL': 0.34423642973720203, 'rougeLsum': 0.3445297239478309}, 'accuracy': 0.00176522506619594, 'correct_ids': [364, 658]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.22: {'meteor': 0.3510044718361491, 'bleu_scores': {'bleu': 0.08350689777294566, 'precisions': [0.3702997530709843, 0.11766040181464679, 0.050021865644027316, 0.02231237322515213], 'brevity_penalty': 1.0, 'length_ratio': 1.059721762172905, 'translation_length': 31993, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.3959486722874449, 'rouge2': 0.1528521180014643, 'rougeL': 0.3366921385756027, 'rougeLsum': 0.3373639725516262}, 'accuracy': 0.00264783759929391, 'correct_ids': [364, 658, 659]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.24: {'meteor': 0.3465600044661264, 'bleu_scores': {'bleu': 0.07954262823239741, 'precisions': [0.3656348982343902, 0.11231059374390323, 0.04652104925559569, 0.020954720954720955], 'brevity_penalty': 1.0, 'length_ratio': 1.056210665783372, 'translation_length': 31887, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.3936141020749143, 'rouge2': 0.14925954755118478, 'rougeL': 0.3330877244705648, 'rougeLsum': 0.333560266399453}, 'accuracy': 0.00264783759929391, 'correct_ids': [364, 658, 659]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.26: {'meteor': 0.3435165661403993, 'bleu_scores': {'bleu': 0.07858780987337025, 'precisions': [0.35780525502318394, 0.1090751833936637, 0.04563887780880202, 0.02141475545730865], 'brevity_penalty': 1.0, 'length_ratio': 1.0715468698244452, 'translation_length': 32350, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.39019940101936945, 'rouge2': 0.1481484713673767, 'rougeL': 0.3302144332821232, 'rougeLsum': 0.33045625596891903}, 'accuracy': 0.00353045013239188, 'correct_ids': [240, 364, 658, 659]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.28: {'meteor': 0.34053363547339577, 'bleu_scores': {'bleu': 0.07203840378380885, 'precisions': [0.3451020592757862, 0.10142348754448399, 0.0418756674541277, 0.018374202216996975], 'brevity_penalty': 1.0, 'length_ratio': 1.0986088108645247, 'translation_length': 33167, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.38636745171321535, 'rouge2': 0.1431996521188323, 'rougeL': 0.3260958081203139, 'rougeLsum': 0.3272219000106166}, 'accuracy': 0.00264783759929391, 'correct_ids': [364, 658, 659]}\n","Qwen/Qwen2-7B-Instruct/rpp-1.30: {'meteor': 0.33446931317267503, 'bleu_scores': {'bleu': 0.062148408497464926, 'precisions': [0.3152004454342984, 0.08905625664759824, 0.035419266654781005, 0.015004765858008178], 'brevity_penalty': 1.0, 'length_ratio': 1.1897979463398476, 'translation_length': 35920, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.38245854011919, 'rouge2': 0.1427848839089301, 'rougeL': 0.3218688387965617, 'rougeLsum': 0.322593189811201}, 'accuracy': 0.00264783759929391, 'correct_ids': [240, 364, 659]}\n","internlm/internlm2_5-7b-chat-1m/rpp-1.00: {'meteor': 0.3715346402699926, 'bleu_scores': {'bleu': 0.1059772684959813, 'precisions': [0.39683339104158144, 0.1431975453714584, 0.06656950140663662, 0.03334508283397956], 'brevity_penalty': 1.0, 'length_ratio': 1.0523020867837032, 'translation_length': 31769, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.41974392291556095, 'rouge2': 0.17056433452207728, 'rougeL': 0.36313270123673597, 'rougeLsum': 0.3632694308153429}, 'accuracy': 0.0, 'correct_ids': []}\n","internlm/internlm2_5-7b-chat-1m/rpp-1.02: {'meteor': 0.352901317633597, 'bleu_scores': {'bleu': 0.08697903417673139, 'precisions': [0.3666595931730682, 0.11979657185910718, 0.05260074213918365, 0.024771882392700235], 'brevity_penalty': 1.0, 'length_ratio': 1.0926465717124876, 'translation_length': 32987, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.39945641283002464, 'rouge2': 0.1518373201584628, 'rougeL': 0.33999857134039985, 'rougeLsum': 0.34085417765557335}, 'accuracy': 0.00088261253309797, 'correct_ids': [511]}\n","shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.00: {'meteor': 0.38168584246814397, 'bleu_scores': {'bleu': 0.11518296996672078, 'precisions': [0.42672642762284196, 0.15593196950357058, 0.07280560043080236, 0.036672529281892005], 'brevity_penalty': 0.9976786612989592, 'length_ratio': 0.9976813514408744, 'translation_length': 30120, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.42528503521639993, 'rouge2': 0.17637973566560697, 'rougeL': 0.3705723503547834, 'rougeLsum': 0.37026767128935023}, 'accuracy': 0.00176522506619594, 'correct_ids': [77, 531]}\n","shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.02: {'meteor': 0.381084663579427, 'bleu_scores': {'bleu': 0.11434064727385712, 'precisions': [0.42645298576938423, 0.15516705248246554, 0.07212973283952392, 0.03635818433974287], 'brevity_penalty': 0.996216776830359, 'length_ratio': 0.9962239152037098, 'translation_length': 30076, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.4245877414493061, 'rouge2': 0.17555464152945213, 'rougeL': 0.3698762430021683, 'rougeLsum': 0.3695464753833268}, 'accuracy': 0.00176522506619594, 'correct_ids': [77, 531]}\n","shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.04: {'meteor': 0.38019108433175514, 'bleu_scores': {'bleu': 0.11353152954579881, 'precisions': [0.42572246637368494, 0.15441303670899215, 0.0716574844262, 0.03599984984421337], 'brevity_penalty': 0.9948859408394681, 'length_ratio': 0.9948989731699238, 'translation_length': 30036, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.4238319064139158, 'rouge2': 0.17523970074952674, 'rougeL': 0.3693886253078722, 'rougeLsum': 0.36906425269244736}, 'accuracy': 0.00176522506619594, 'correct_ids': [77, 531]}\n","shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.06: {'meteor': 0.37862157681270814, 'bleu_scores': {'bleu': 0.11220469680226439, 'precisions': [0.42524207011686144, 0.15293056182114723, 0.07094094274878093, 0.03547621737656762], 'brevity_penalty': 0.9920186657513808, 'length_ratio': 0.9920503477972838, 'translation_length': 29950, 'reference_length': 30190}, 'rouge_scores': {'rouge1': 0.42330817492734973, 'rouge2': 0.1739818636031837, 'rougeL': 0.3689343348685089, 'rougeLsum': 0.36845353949593573}, 'accuracy': 0.00176522506619594, 'correct_ids': [77, 531]}\n"]},{"data":{"text/html":["
\n","\n","\n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n","
modelrppmeteorbleu_1rouge_lews_scorerepetition_scoretotal_repetitionsnum_entries_with_max_output_tokens
0Qwen/Qwen2-72B-Instruct1.000.3949690.1229490.3835640.0000000.3609890.3609890
1Qwen/Qwen2-7B-Instruct1.000.3757940.1125770.3642500.0000000.2656660.2656660
2Qwen/Qwen2-7B-Instruct1.020.3768160.1155390.3695390.0000000.2559580.2559580
3Qwen/Qwen2-7B-Instruct1.040.3715150.1131160.3637110.0000000.2683140.2683140
4Qwen/Qwen2-7B-Instruct1.060.3721610.1098600.3608780.0000000.2815530.2815530
5Qwen/Qwen2-7B-Instruct1.080.3712970.1080950.3594010.0000000.2118270.2118270
6Qwen/Qwen2-7B-Instruct1.100.3713530.1080970.3594690.0000000.2533100.2533100
7Qwen/Qwen2-7B-Instruct1.120.3682040.1050560.3583800.0000000.4404240.4404240
8Qwen/Qwen2-7B-Instruct1.140.3630770.1005160.3496060.0000000.2806710.2806710
9Qwen/Qwen2-7B-Instruct1.160.3606040.0957240.3505400.0000000.2656660.2656660
10Qwen/Qwen2-7B-Instruct1.180.3607850.0957130.3441780.0000000.2859660.2859660
11Qwen/Qwen2-7B-Instruct1.200.3567550.0912490.3442360.0000000.2912620.2912620
12Qwen/Qwen2-7B-Instruct1.220.3510040.0835070.3366920.0000000.2691970.2691970
13Qwen/Qwen2-7B-Instruct1.240.3465600.0795430.3330880.0000000.3009710.3009710
14Qwen/Qwen2-7B-Instruct1.260.3435170.0785880.3302140.0000000.2665490.2665490
15Qwen/Qwen2-7B-Instruct1.280.3405340.0720380.3260960.0000000.1844660.1844660
16Qwen/Qwen2-7B-Instruct1.300.3344690.0621480.3218690.0052960.3256840.3309801
17internlm/internlm2_5-7b-chat-1m1.000.3715350.1059770.3631330.0000005.5401595.5401591
18internlm/internlm2_5-7b-chat-1m1.020.3529010.0869790.3399990.0000000.3071490.3071490
19shenzhi-wang/Llama3.1-70B-Chinese-Chat1.000.3816860.1151830.3705720.0000000.4068840.4068840
20shenzhi-wang/Llama3.1-70B-Chinese-Chat1.020.3810850.1143410.3698760.0000000.4333630.4333630
21shenzhi-wang/Llama3.1-70B-Chinese-Chat1.040.3801910.1135320.3693890.0000000.4236540.4236540
22shenzhi-wang/Llama3.1-70B-Chinese-Chat1.060.3786220.1122050.3689340.0000000.4236540.4236540
\n","
"],"text/plain":[" model rpp meteor bleu_1 \\\n","0 Qwen/Qwen2-72B-Instruct 1.00 0.394969 0.122949 \n","1 Qwen/Qwen2-7B-Instruct 1.00 0.375794 0.112577 \n","2 Qwen/Qwen2-7B-Instruct 1.02 0.376816 0.115539 \n","3 Qwen/Qwen2-7B-Instruct 1.04 0.371515 0.113116 \n","4 Qwen/Qwen2-7B-Instruct 1.06 0.372161 0.109860 \n","5 Qwen/Qwen2-7B-Instruct 1.08 0.371297 0.108095 \n","6 Qwen/Qwen2-7B-Instruct 1.10 0.371353 0.108097 \n","7 Qwen/Qwen2-7B-Instruct 1.12 0.368204 0.105056 \n","8 Qwen/Qwen2-7B-Instruct 1.14 0.363077 0.100516 \n","9 Qwen/Qwen2-7B-Instruct 1.16 0.360604 0.095724 \n","10 Qwen/Qwen2-7B-Instruct 1.18 0.360785 0.095713 \n","11 Qwen/Qwen2-7B-Instruct 1.20 0.356755 0.091249 \n","12 Qwen/Qwen2-7B-Instruct 1.22 0.351004 0.083507 \n","13 Qwen/Qwen2-7B-Instruct 1.24 0.346560 0.079543 \n","14 Qwen/Qwen2-7B-Instruct 1.26 0.343517 0.078588 \n","15 Qwen/Qwen2-7B-Instruct 1.28 0.340534 0.072038 \n","16 Qwen/Qwen2-7B-Instruct 1.30 0.334469 0.062148 \n","17 internlm/internlm2_5-7b-chat-1m 1.00 0.371535 0.105977 \n","18 internlm/internlm2_5-7b-chat-1m 1.02 0.352901 0.086979 \n","19 shenzhi-wang/Llama3.1-70B-Chinese-Chat 1.00 0.381686 0.115183 \n","20 shenzhi-wang/Llama3.1-70B-Chinese-Chat 1.02 0.381085 0.114341 \n","21 shenzhi-wang/Llama3.1-70B-Chinese-Chat 1.04 0.380191 0.113532 \n","22 shenzhi-wang/Llama3.1-70B-Chinese-Chat 1.06 0.378622 0.112205 \n","\n"," rouge_l ews_score repetition_score total_repetitions \\\n","0 0.383564 0.000000 0.360989 0.360989 \n","1 0.364250 0.000000 0.265666 0.265666 \n","2 0.369539 0.000000 0.255958 0.255958 \n","3 0.363711 0.000000 0.268314 0.268314 \n","4 0.360878 0.000000 0.281553 0.281553 \n","5 0.359401 0.000000 0.211827 0.211827 \n","6 0.359469 0.000000 0.253310 0.253310 \n","7 0.358380 0.000000 0.440424 0.440424 \n","8 0.349606 0.000000 0.280671 0.280671 \n","9 0.350540 0.000000 0.265666 0.265666 \n","10 0.344178 0.000000 0.285966 0.285966 \n","11 0.344236 0.000000 0.291262 0.291262 \n","12 0.336692 0.000000 0.269197 0.269197 \n","13 0.333088 0.000000 0.300971 0.300971 \n","14 0.330214 0.000000 0.266549 0.266549 \n","15 0.326096 0.000000 0.184466 0.184466 \n","16 0.321869 0.005296 0.325684 0.330980 \n","17 0.363133 0.000000 5.540159 5.540159 \n","18 0.339999 0.000000 0.307149 0.307149 \n","19 0.370572 0.000000 0.406884 0.406884 \n","20 0.369876 0.000000 0.433363 0.433363 \n","21 0.369389 0.000000 0.423654 0.423654 \n","22 0.368934 0.000000 0.423654 0.423654 \n","\n"," num_entries_with_max_output_tokens \n","0 0 \n","1 0 \n","2 0 \n","3 0 \n","4 0 \n","5 0 \n","6 0 \n","7 0 \n","8 0 \n","9 0 \n","10 0 \n","11 0 \n","12 0 \n","13 0 \n","14 0 \n","15 0 \n","16 1 \n","17 1 \n","18 0 \n","19 0 \n","20 0 \n","21 0 \n","22 0 "]},"execution_count":33,"metadata":{},"output_type":"execute_result"}],"source":["metrics_df = get_metrics(df)\n","metrics_df"]},{"cell_type":"code","execution_count":34,"metadata":{},"outputs":[],"source":["metrics_df[\"rap\"] = metrics_df.apply(\n"," lambda x: x[\"meteor\"] / math.log10(10 + x[\"total_repetitions\"]), axis=1\n",")"]},{"cell_type":"code","execution_count":35,"metadata":{},"outputs":[{"data":{"text/html":["
\n","\n","\n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n","
modelrppmeteorbleu_1rouge_lews_scorerepetition_scoretotal_repetitionsnum_entries_with_max_output_tokensrap
0Qwen/Qwen2-72B-Instruct1.000.3949690.1229490.3835640.0000000.3609890.36098900.388978
1Qwen/Qwen2-7B-Instruct1.000.3757940.1125770.3642500.0000000.2656660.26566600.371563
2Qwen/Qwen2-7B-Instruct1.020.3768160.1155390.3695390.0000000.2559580.25595800.372725
3Qwen/Qwen2-7B-Instruct1.040.3715150.1131160.3637110.0000000.2683140.26831400.367291
4Qwen/Qwen2-7B-Instruct1.060.3721610.1098600.3608780.0000000.2815530.28155300.367727
5Qwen/Qwen2-7B-Instruct1.080.3712970.1080950.3594010.0000000.2118270.21182700.367947
6Qwen/Qwen2-7B-Instruct1.100.3713530.1080970.3594690.0000000.2533100.25331000.367362
7Qwen/Qwen2-7B-Instruct1.120.3682040.1050560.3583800.0000000.4404240.44042400.361439
8Qwen/Qwen2-7B-Instruct1.140.3630770.1005160.3496060.0000000.2806710.28067100.358765
9Qwen/Qwen2-7B-Instruct1.160.3606040.0957240.3505400.0000000.2656660.26566600.356544
10Qwen/Qwen2-7B-Instruct1.180.3607850.0957130.3441780.0000000.2859660.28596600.356421
11Qwen/Qwen2-7B-Instruct1.200.3567550.0912490.3442360.0000000.2912620.29126200.352361
12Qwen/Qwen2-7B-Instruct1.220.3510040.0835070.3366920.0000000.2691970.26919700.347001
13Qwen/Qwen2-7B-Instruct1.240.3465600.0795430.3330880.0000000.3009710.30097100.342154
14Qwen/Qwen2-7B-Instruct1.260.3435170.0785880.3302140.0000000.2665490.26654900.339636
15Qwen/Qwen2-7B-Instruct1.280.3405340.0720380.3260960.0000000.1844660.18446600.337852
16Qwen/Qwen2-7B-Instruct1.300.3344690.0621480.3218690.0052960.3256840.33098010.329805
17internlm/internlm2_5-7b-chat-1m1.000.3715350.1059770.3631330.0000005.5401595.54015910.311833
18internlm/internlm2_5-7b-chat-1m1.020.3529010.0869790.3399990.0000000.3071490.30714900.348325
19shenzhi-wang/Llama3.1-70B-Chinese-Chat1.000.3816860.1151830.3705720.0000000.4068840.40688400.375187
20shenzhi-wang/Llama3.1-70B-Chinese-Chat1.020.3810850.1143410.3698760.0000000.4333630.43336300.374190
21shenzhi-wang/Llama3.1-70B-Chinese-Chat1.040.3801910.1135320.3693890.0000000.4236540.42365400.373461
22shenzhi-wang/Llama3.1-70B-Chinese-Chat1.060.3786220.1122050.3689340.0000000.4236540.42365400.371920
\n","
"],"text/plain":[" model rpp meteor bleu_1 \\\n","0 Qwen/Qwen2-72B-Instruct 1.00 0.394969 0.122949 \n","1 Qwen/Qwen2-7B-Instruct 1.00 0.375794 0.112577 \n","2 Qwen/Qwen2-7B-Instruct 1.02 0.376816 0.115539 \n","3 Qwen/Qwen2-7B-Instruct 1.04 0.371515 0.113116 \n","4 Qwen/Qwen2-7B-Instruct 1.06 0.372161 0.109860 \n","5 Qwen/Qwen2-7B-Instruct 1.08 0.371297 0.108095 \n","6 Qwen/Qwen2-7B-Instruct 1.10 0.371353 0.108097 \n","7 Qwen/Qwen2-7B-Instruct 1.12 0.368204 0.105056 \n","8 Qwen/Qwen2-7B-Instruct 1.14 0.363077 0.100516 \n","9 Qwen/Qwen2-7B-Instruct 1.16 0.360604 0.095724 \n","10 Qwen/Qwen2-7B-Instruct 1.18 0.360785 0.095713 \n","11 Qwen/Qwen2-7B-Instruct 1.20 0.356755 0.091249 \n","12 Qwen/Qwen2-7B-Instruct 1.22 0.351004 0.083507 \n","13 Qwen/Qwen2-7B-Instruct 1.24 0.346560 0.079543 \n","14 Qwen/Qwen2-7B-Instruct 1.26 0.343517 0.078588 \n","15 Qwen/Qwen2-7B-Instruct 1.28 0.340534 0.072038 \n","16 Qwen/Qwen2-7B-Instruct 1.30 0.334469 0.062148 \n","17 internlm/internlm2_5-7b-chat-1m 1.00 0.371535 0.105977 \n","18 internlm/internlm2_5-7b-chat-1m 1.02 0.352901 0.086979 \n","19 shenzhi-wang/Llama3.1-70B-Chinese-Chat 1.00 0.381686 0.115183 \n","20 shenzhi-wang/Llama3.1-70B-Chinese-Chat 1.02 0.381085 0.114341 \n","21 shenzhi-wang/Llama3.1-70B-Chinese-Chat 1.04 0.380191 0.113532 \n","22 shenzhi-wang/Llama3.1-70B-Chinese-Chat 1.06 0.378622 0.112205 \n","\n"," rouge_l ews_score repetition_score total_repetitions \\\n","0 0.383564 0.000000 0.360989 0.360989 \n","1 0.364250 0.000000 0.265666 0.265666 \n","2 0.369539 0.000000 0.255958 0.255958 \n","3 0.363711 0.000000 0.268314 0.268314 \n","4 0.360878 0.000000 0.281553 0.281553 \n","5 0.359401 0.000000 0.211827 0.211827 \n","6 0.359469 0.000000 0.253310 0.253310 \n","7 0.358380 0.000000 0.440424 0.440424 \n","8 0.349606 0.000000 0.280671 0.280671 \n","9 0.350540 0.000000 0.265666 0.265666 \n","10 0.344178 0.000000 0.285966 0.285966 \n","11 0.344236 0.000000 0.291262 0.291262 \n","12 0.336692 0.000000 0.269197 0.269197 \n","13 0.333088 0.000000 0.300971 0.300971 \n","14 0.330214 0.000000 0.266549 0.266549 \n","15 0.326096 0.000000 0.184466 0.184466 \n","16 0.321869 0.005296 0.325684 0.330980 \n","17 0.363133 0.000000 5.540159 5.540159 \n","18 0.339999 0.000000 0.307149 0.307149 \n","19 0.370572 0.000000 0.406884 0.406884 \n","20 0.369876 0.000000 0.433363 0.433363 \n","21 0.369389 0.000000 0.423654 0.423654 \n","22 0.368934 0.000000 0.423654 0.423654 \n","\n"," num_entries_with_max_output_tokens rap \n","0 0 0.388978 \n","1 0 0.371563 \n","2 0 0.372725 \n","3 0 0.367291 \n","4 0 0.367727 \n","5 0 0.367947 \n","6 0 0.367362 \n","7 0 0.361439 \n","8 0 0.358765 \n","9 0 0.356544 \n","10 0 0.356421 \n","11 0 0.352361 \n","12 0 0.347001 \n","13 0 0.342154 \n","14 0 0.339636 \n","15 0 0.337852 \n","16 1 0.329805 \n","17 1 0.311833 \n","18 0 0.348325 \n","19 0 0.375187 \n","20 0 0.374190 \n","21 0 0.373461 \n","22 0 0.371920 "]},"execution_count":35,"metadata":{},"output_type":"execute_result"}],"source":["metrics_df"]},{"cell_type":"code","execution_count":36,"metadata":{},"outputs":[],"source":["models = metrics_df[\"model\"].unique()"]},{"cell_type":"code","execution_count":37,"metadata":{},"outputs":[{"data":{"text/plain":["array(['Qwen/Qwen2-72B-Instruct', 'Qwen/Qwen2-7B-Instruct',\n"," 'internlm/internlm2_5-7b-chat-1m',\n"," 'shenzhi-wang/Llama3.1-70B-Chinese-Chat'], dtype=object)"]},"execution_count":37,"metadata":{},"output_type":"execute_result"}],"source":["models"]},{"cell_type":"code","execution_count":38,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["
"]},"metadata":{},"output_type":"display_data"}],"source":["# plot meteor vs rpp\n","\n","import matplotlib.pyplot as plt\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","# ax.grid(which=\"minor\", linestyle=\":\", linewidth=\"0.5\", color=\"black\")\n","\n","for model in models:\n"," model_df = metrics_df[metrics_df[\"model\"] == model]\n"," ax.plot(model_df[\"rpp\"], model_df[\"meteor\"], label=model + \" (METEOR)\")\n"," ax.plot(\n"," model_df[\"rpp\"], model_df[\"rap\"], label=model + \" (RAP-METEOR)\", linestyle=\"--\"\n"," )\n","\n","ax.set_xlabel(\"Repetition Penalty Parameter\")\n","ax.set_ylabel(\"METEOR & RAP-METEOR\")\n","ax.legend(loc=\"lower center\", bbox_to_anchor=(0.5, -0.5))\n","plt.show()"]},{"cell_type":"code","execution_count":49,"metadata":{},"outputs":[{"data":{"image/png":"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","text/plain":["
"]},"metadata":{},"output_type":"display_data"}],"source":["# plot mtr vs rpp\n","import matplotlib.pyplot as plt\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","# ax.grid(which=\"minor\", linestyle=\":\", linewidth=\"0.5\", color=\"black\")\n","\n","for model in models:\n"," model_df = metrics_df[metrics_df[\"model\"] == model]\n"," ax.plot(model_df[\"rpp\"], model_df[\"total_repetitions\"], label=model)\n","\n","\n","ax.set_xlabel(\"Repetition Penalty Parameter\")\n","ax.set_ylabel(\"Mean Total Repetitions (MTR)\")\n","ax.legend(loc=\"lower center\", bbox_to_anchor=(0.5, -0.3))\n","plt.show()"]},{"cell_type":"code","execution_count":40,"metadata":{},"outputs":[],"source":["tokenizers = {model: load_tokenizer(model) for model in models}"]},{"cell_type":"code","execution_count":42,"metadata":{},"outputs":[],"source":["col = \"internlm/internlm2_5-7b-chat-1m/rpp-1.00\"\n","df[[\"ews_score\", \"repetition_score\", \"total_repetitions\"]] = df[col].apply(\n"," detect_scores\n",")\n","df[\"output_tokens\"] = df[col].apply(\n"," lambda x: len(tokenizers[col.split(\"/rpp\")[0]](x)[\"input_ids\"])\n",")"]},{"cell_type":"code","execution_count":43,"metadata":{},"outputs":[{"data":{"text/html":["
\n","\n","\n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n"," \n","
chineseenglishQwen/Qwen2-72B-Instruct/rpp-1.00Qwen/Qwen2-7B-Instruct/rpp-1.00Qwen/Qwen2-7B-Instruct/rpp-1.02Qwen/Qwen2-7B-Instruct/rpp-1.04Qwen/Qwen2-7B-Instruct/rpp-1.06Qwen/Qwen2-7B-Instruct/rpp-1.08Qwen/Qwen2-7B-Instruct/rpp-1.10Qwen/Qwen2-7B-Instruct/rpp-1.12...internlm/internlm2_5-7b-chat-1m/rpp-1.00internlm/internlm2_5-7b-chat-1m/rpp-1.02shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.00shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.02shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.04shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.06ews_scorerepetition_scoretotal_repetitionsoutput_tokens
503青天哟——蓝天哟——花花绿绿的天哟——棒槌哟亲哥哟你死了——可就塌了妹妹的天哟——A blue sky yo – a sapphire sky yo – a painted ...Blue sky oh—clear sky oh—colorful sky oh—my de...Blue sky oh - blue heaven oh - colorful sky oh...Blue heaven—oh, blue sky—oh, colorful sky—stic...Blue heaven—oh, blue sky—oh, colorful sky—stup...Blue sky oh - blue heaven oh - colorful sky oh...Blue sky—oh, blue heaven—colorful sky—stupid f...Blue sky - oh blue heaven - colorful sky - you...Blue sky - oh blue sky - colorful sky - you've......Oh, the blue sky, the blue sky, the sky with i...Oh blue sky - oh green sky - oh colorful sky -...Blue sky, oh — Green sky, oh — Colorful sky, o...Blue sky, oh — Green sky, oh — Colorful sky, o...Blue sky, oh — Green sky, oh — Colorful sky, o...Blue sky, oh — Green sky, oh — Colorful sky, o...0611261122049
\n","

1 rows × 29 columns

\n","
"],"text/plain":[" chinese \\\n","503 青天哟——蓝天哟——花花绿绿的天哟——棒槌哟亲哥哟你死了——可就塌了妹妹的天哟—— \n","\n"," english \\\n","503 A blue sky yo – a sapphire sky yo – a painted ... \n","\n"," Qwen/Qwen2-72B-Instruct/rpp-1.00 \\\n","503 Blue sky oh—clear sky oh—colorful sky oh—my de... \n","\n"," Qwen/Qwen2-7B-Instruct/rpp-1.00 \\\n","503 Blue sky oh - blue heaven oh - colorful sky oh... \n","\n"," Qwen/Qwen2-7B-Instruct/rpp-1.02 \\\n","503 Blue heaven—oh, blue sky—oh, colorful sky—stic... \n","\n"," Qwen/Qwen2-7B-Instruct/rpp-1.04 \\\n","503 Blue heaven—oh, blue sky—oh, colorful sky—stup... \n","\n"," Qwen/Qwen2-7B-Instruct/rpp-1.06 \\\n","503 Blue sky oh - blue heaven oh - colorful sky oh... \n","\n"," Qwen/Qwen2-7B-Instruct/rpp-1.08 \\\n","503 Blue sky—oh, blue heaven—colorful sky—stupid f... \n","\n"," Qwen/Qwen2-7B-Instruct/rpp-1.10 \\\n","503 Blue sky - oh blue heaven - colorful sky - you... \n","\n"," Qwen/Qwen2-7B-Instruct/rpp-1.12 ... \\\n","503 Blue sky - oh blue sky - colorful sky - you've... ... \n","\n"," internlm/internlm2_5-7b-chat-1m/rpp-1.00 \\\n","503 Oh, the blue sky, the blue sky, the sky with i... \n","\n"," internlm/internlm2_5-7b-chat-1m/rpp-1.02 \\\n","503 Oh blue sky - oh green sky - oh colorful sky -... \n","\n"," shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.00 \\\n","503 Blue sky, oh — Green sky, oh — Colorful sky, o... \n","\n"," shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.02 \\\n","503 Blue sky, oh — Green sky, oh — Colorful sky, o... \n","\n"," shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.04 \\\n","503 Blue sky, oh — Green sky, oh — Colorful sky, o... \n","\n"," shenzhi-wang/Llama3.1-70B-Chinese-Chat/rpp-1.06 ews_score \\\n","503 Blue sky, oh — Green sky, oh — Colorful sky, o... 0 \n","\n"," repetition_score total_repetitions output_tokens \n","503 6112 6112 2049 \n","\n","[1 rows x 29 columns]"]},"execution_count":43,"metadata":{},"output_type":"execute_result"}],"source":["rows = df.query(\"total_repetitions > 1000\")\n","rows"]},{"cell_type":"code","execution_count":44,"metadata":{},"outputs":[],"source":["row = rows.iloc[0]"]},{"cell_type":"code","execution_count":45,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["青天哟——蓝天哟——花花绿绿的天哟——棒槌哟亲哥哟你死了——可就塌了妹妹的天哟——\n"]}],"source":["print(row[\"chinese\"])"]},{"cell_type":"code","execution_count":46,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["A blue sky yo – a sapphire sky yo – a painted sky yo – a mighty cudgel yo – dear elder brother yo – death has claimed you – you have brought down little sister's sky yo –.\n"]}],"source":["print(row[\"english\"])"]},{"cell_type":"code","execution_count":47,"metadata":{},"outputs":[{"name":"stdout","output_type":"stream","text":["Oh, the blue sky, the blue sky, the sky with its colorful hues, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky, the sky\n","----detect excessive whitespaces----\n","----detect text repetitions----\n","\n","Group 1 found at 2-16: `, the blue sky`\n","Group 2 found at 16-30: `, the blue sky`\n","Group 3 found at 16-30: `, the blue sky`\n","