{"cells":[{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"a_g6CqUuiWDT","outputId":"523c5332-ace7-4ab4-dece-926e819fd1a4","executionInfo":{"status":"ok","timestamp":1719068222057,"user_tz":-240,"elapsed":26507,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/drive')"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Z0Dl6DZOfpJu","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1717985966176,"user_tz":-240,"elapsed":5532,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}},"outputId":"bb1201c1-b6d5-4684-de9f-a1bf67e121e0"},"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.10/dist-packages (0.23.2)\n","Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (3.14.0)\n","Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (2023.6.0)\n","Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (24.0)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (6.0.1)\n","Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (2.31.0)\n","Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (4.66.4)\n","Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface_hub) (4.12.1)\n","Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (3.3.2)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (3.7)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (2.0.7)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface_hub) (2024.6.2)\n"]}],"source":["pip install huggingface_hub"]},{"cell_type":"code","execution_count":24,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":162,"referenced_widgets":["5fe4b2c3fe04458a827a1c7c76544629","de34133d4cac4e438d69aa259818bad1","30aace55d5b547669ac4dcc955ad96a1","aec90264b5ab41da9aa41278786efd03","dacb8b2334e04016aeb1e0fd9d61fe28","267717b34fc049e395f900337da35b0d","bf9320bf6f5d4512be5ad0805bf4f0dc","625a00fe1bd545899eab2746d22e9c9b","06e9d156aa2648ea84be54d51f3dfb5d","073e61cd9f8048da8b348ba9469e68f5","fd801b9167cd4eee9b12e27869fefef2","6b1ebd49c15141a78cc4246c87471f51","3a10a83aa25e47148f59f0a7b3118177","9d417aea0c54415b9b93d5b24ea06f4e","3bcc8ff2e284457190b26910afaef180","748f816e6c854b8c9bab5ab6e8c65624","5accc318a50948ef92c1c0d480f7678c","2918e3a7f65a41f8b4f52f1b9a77d405","ba76b3ca84fc49a69ebdf2f469bae526","6d7d13cf052d4f5f92d473be7a8d33d5","669a518d5d0f4f93864fe22987c6e9ba","7add1eefd911448190f81034306250c4","9e0e0a58a8ec475082283476d3ea59c2","69ff6bdc018249dc88d436072a0c6007","c155dd501120426fb7923ee311ea7cef","c85ef12573344b34a1838030db74f5b5","a987c038cf09437c8a4f06fa514ddd41","bd5df9b823114cb5abb1cc28c09b65c6","8a50adefbfcf48a5a2107b5968532bcc","752cda0ffe2f44deb19a5ec65c0211a7","3f26206d63444d7483de9d4a6cc298c8","b0e02d7e09ea4dcd90c101b88a2ba83c"]},"id":"s8yMdMBZfwp8","outputId":"909ea833-a8a9-4362-ec33-d54024208ba4","executionInfo":{"status":"ok","timestamp":1719072202506,"user_tz":-240,"elapsed":454,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}}},"outputs":[{"output_type":"display_data","data":{"text/plain":["VBox(children=(HTML(value='
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(0.70.16)\n","Requirement already satisfied: fsspec[http]<=2024.5.0,>=2023.1.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2023.6.0)\n","Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets) (3.9.5)\n","Requirement already satisfied: huggingface-hub>=0.21.2 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.23.4)\n","Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from datasets) (24.1)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (6.0.1)\n","Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.3.1)\n","Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (23.2.0)\n","Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.4.1)\n","Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (6.0.5)\n","Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.9.4)\n","Requirement already satisfied: async-timeout<5.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (4.0.3)\n","Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.21.2->datasets) (4.12.2)\n","Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets) (3.3.2)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets) (3.7)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets) (2.0.7)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets) (2024.6.2)\n","Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2.8.2)\n","Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2023.4)\n","Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2024.1)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas->datasets) (1.16.0)\n"]}],"source":["pip install datasets"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"5QkZgRtym6QX","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1717517072772,"user_tz":-240,"elapsed":6379,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}},"outputId":"d469302a-9e59-4841-8b03-0e4e4a945092"},"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting rouge_score\n"," Downloading rouge_score-0.1.2.tar.gz (17 kB)\n"," Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n","Requirement already satisfied: absl-py in /usr/local/lib/python3.10/dist-packages (from rouge_score) (1.4.0)\n","Requirement already satisfied: nltk in /usr/local/lib/python3.10/dist-packages (from rouge_score) (3.8.1)\n","Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from rouge_score) (1.25.2)\n","Requirement already satisfied: six>=1.14.0 in /usr/local/lib/python3.10/dist-packages (from rouge_score) (1.16.0)\n","Requirement already satisfied: click in /usr/local/lib/python3.10/dist-packages (from nltk->rouge_score) (8.1.7)\n","Requirement already satisfied: joblib in /usr/local/lib/python3.10/dist-packages (from nltk->rouge_score) (1.4.2)\n","Requirement already satisfied: regex>=2021.8.3 in /usr/local/lib/python3.10/dist-packages (from nltk->rouge_score) (2024.5.15)\n","Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from nltk->rouge_score) (4.66.4)\n","Building wheels for collected packages: rouge_score\n"," Building wheel for rouge_score (setup.py) ... \u001b[?25l\u001b[?25hdone\n"," Created wheel for rouge_score: filename=rouge_score-0.1.2-py3-none-any.whl size=24933 sha256=c88639beef646889d9826ebc03998b77688f195fbd6d6d22829bfc470f83a9af\n"," Stored in directory: /root/.cache/pip/wheels/5f/dd/89/461065a73be61a532ff8599a28e9beef17985c9e9c31e541b4\n","Successfully built rouge_score\n","Installing collected packages: rouge_score\n","Successfully installed rouge_score-0.1.2\n"]}],"source":["pip install rouge_score"]},{"cell_type":"code","execution_count":4,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9srcg82ts73r","outputId":"1988139b-e534-40c8-dbda-b5f9b90e674b","executionInfo":{"status":"ok","timestamp":1719068307687,"user_tz":-240,"elapsed":61488,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting accelerate\n"," Downloading accelerate-0.31.0-py3-none-any.whl (309 kB)\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m309.4/309.4 kB\u001b[0m \u001b[31m6.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from accelerate) (1.25.2)\n","Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from accelerate) (24.1)\n","Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from 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torch>=1.10.0->accelerate) (3.3)\n","Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (3.1.4)\n","Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (2023.6.0)\n","Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch>=1.10.0->accelerate)\n"," Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n","Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch>=1.10.0->accelerate)\n"," Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)\n","Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch>=1.10.0->accelerate)\n"," Using cached nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)\n","Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch>=1.10.0->accelerate)\n"," Using cached nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)\n","Collecting nvidia-cublas-cu12==12.1.3.1 (from torch>=1.10.0->accelerate)\n"," Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n","Collecting nvidia-cufft-cu12==11.0.2.54 (from torch>=1.10.0->accelerate)\n"," Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)\n","Collecting nvidia-curand-cu12==10.3.2.106 (from torch>=1.10.0->accelerate)\n"," Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n","Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch>=1.10.0->accelerate)\n"," Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n","Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch>=1.10.0->accelerate)\n"," Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n","Collecting nvidia-nccl-cu12==2.20.5 (from torch>=1.10.0->accelerate)\n"," Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl (176.2 MB)\n","Collecting nvidia-nvtx-cu12==12.1.105 (from torch>=1.10.0->accelerate)\n"," Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n","Requirement already satisfied: triton==2.3.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (2.3.0)\n","Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.10.0->accelerate)\n"," Downloading nvidia_nvjitlink_cu12-12.5.40-py3-none-manylinux2014_x86_64.whl (21.3 MB)\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.3/21.3 MB\u001b[0m \u001b[31m13.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->accelerate) (2.32.3)\n","Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->accelerate) (4.66.4)\n","Requirement already satisfied: MarkupSafe>=2.0 in 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nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, accelerate\n","Successfully installed accelerate-0.31.0 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.40 nvidia-nvtx-cu12-12.1.105\n"]}],"source":["pip install accelerate -U"]},{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"YIRJ_hpoIAoH","outputId":"5b393f81-3ba6-428b-ece1-e7bee0627ad4","executionInfo":{"status":"ok","timestamp":1719068332102,"user_tz":-240,"elapsed":4879,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["'0.31.0'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":1}],"source":["import accelerate\n","\n","accelerate.__version__"]},{"cell_type":"code","execution_count":3,"metadata":{"id":"NITeHKNnwsOG","executionInfo":{"status":"ok","timestamp":1719068375175,"user_tz":-240,"elapsed":468,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}}},"outputs":[],"source":["import torch\n","torch.cuda.empty_cache()"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"Vjnu4pNwSbRS","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1717499511356,"user_tz":-240,"elapsed":10420,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}},"outputId":"7af869de-9390-4124-b6c6-3b8dd61cf9bc"},"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting prettyprint\n"," Downloading prettyprint-0.1.5.tar.gz (2.1 kB)\n"," Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n","Building wheels for collected packages: prettyprint\n"," Building wheel for prettyprint (setup.py) ... \u001b[?25l\u001b[?25hdone\n"," Created wheel for prettyprint: filename=prettyprint-0.1.5-py3-none-any.whl size=3027 sha256=1a844ebdf0c53a3cc082d7fc0327d7d57c0b250bf96dbf448a78637d1f36628d\n"," Stored in directory: /root/.cache/pip/wheels/b2/d0/51/477413885481c635ab7c6400f96f47b8a0971bbc1241ff9c9f\n","Successfully built prettyprint\n","Installing collected packages: prettyprint\n","Successfully installed prettyprint-0.1.5\n"]}],"source":["!pip install prettyprint\n","import prettyprint as pprint"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"G1H5ew4oUEcD","outputId":"57f3faf0-c62b-4e6b-b365-d71b1f9dad11"},"outputs":[{"name":"stdout","output_type":"stream","text":["Mon May 27 04:30:22 2024 \n","+---------------------------------------------------------------------------------------+\n","| NVIDIA-SMI 535.104.05 Driver Version: 535.104.05 CUDA Version: 12.2 |\n","|-----------------------------------------+----------------------+----------------------+\n","| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |\n","| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |\n","| | | MIG M. |\n","|=========================================+======================+======================|\n","| 0 Tesla T4 Off | 00000000:00:04.0 Off | 0 |\n","| N/A 35C P8 8W / 70W | 0MiB / 15360MiB | 0% Default |\n","| | | N/A |\n","+-----------------------------------------+----------------------+----------------------+\n"," \n","+---------------------------------------------------------------------------------------+\n","| Processes: |\n","| GPU GI CI PID Type Process name GPU Memory |\n","| ID ID Usage |\n","|=======================================================================================|\n","| No running processes found |\n","+---------------------------------------------------------------------------------------+\n"]}],"source":["!nvidia-smi"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"NTval3Qx7ngS","executionInfo":{"status":"ok","timestamp":1717499522136,"user_tz":-240,"elapsed":10789,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}},"outputId":"3dcbbd8a-50ca-4bdd-869c-8851a66b45d4"},"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: matplotlib in /usr/local/lib/python3.10/dist-packages (3.7.1)\n","Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (1.2.1)\n","Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (0.12.1)\n","Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (4.52.4)\n","Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (1.4.5)\n","Requirement already satisfied: numpy>=1.20 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (1.25.2)\n","Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (24.0)\n","Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (9.4.0)\n","Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (3.1.2)\n","Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib) (2.8.2)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n"]}],"source":["pip install matplotlib"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"olP3Wvn-7ngT","executionInfo":{"status":"ok","timestamp":1717499531969,"user_tz":-240,"elapsed":9838,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}},"outputId":"4d707167-8111-42ea-fa77-764cf68aef2c"},"outputs":[{"output_type":"stream","name":"stdout","text":["Requirement already satisfied: scikit-learn in /usr/local/lib/python3.10/dist-packages (1.2.2)\n","Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.10/dist-packages (from scikit-learn) (1.25.2)\n","Requirement already satisfied: scipy>=1.3.2 in /usr/local/lib/python3.10/dist-packages (from scikit-learn) (1.11.4)\n","Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-learn) (1.4.2)\n","Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn) (3.5.0)\n"]}],"source":["pip install scikit-learn"]},{"cell_type":"code","execution_count":4,"metadata":{"id":"7xnIpegCiImk","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1719068878141,"user_tz":-240,"elapsed":497346,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}},"outputId":"e45edd11-2913-443a-9b7f-da0c9ef238d5"},"outputs":[{"output_type":"stream","name":"stdout","text":[" input_text \\\n","0 a large number of current language processing ... \n","1 current automatic summarizers usually rely on ... \n","2 even moderately long documents typically addre... \n","3 word sense disambiguation is often cast as a p... \n","4 we present a new parser for parsing down to pe... \n",".. ... \n","994 the ability to determine the named entities in... \n","995 many statistical or machine-learning approache... \n","996 the natural language processing community is i... \n","997 in this paper, we focus on the problem of dete... \n","998 when dealing with large amounts of text, findi... \n","\n"," target_text \n","0 tnt - a statistical part-of-speech tagger trig... \n","1 sentence reduction for automatic text summariz... \n","2 advances in domain independent linear text seg... \n","3 a simple approach to building ensembles of nai... \n","4 a maximum-entropy-inspired parser we present a... \n",".. ... \n","994 language independent named entity recognition ... \n","995 unsupervised models for named entity classific... \n","996 exploiting diversity in natural language proce... \n","997 detecting text similarity over short passages:... \n","998 cascaded grammatical relation assignment in th... \n","\n","[999 rows x 2 columns]\n"]}],"source":["import os\n","import glob\n","import pandas as pd\n","import matplotlib.pyplot as plt\n","from sklearn.model_selection import train_test_split\n","from transformers import LEDTokenizer, LEDForConditionalGeneration, Trainer, TrainingArguments\n","from datasets import Dataset, load_metric\n","\n","# Load data from txt files\n","def load_data(input_dir, target_dir):\n"," data = {'input_text': [], 'target_text': []}\n"," input_files = glob.glob(os.path.join(input_dir, '*.txt'))\n","\n"," for input_file in input_files:\n"," filename = os.path.basename(input_file)\n"," target_file = os.path.join(target_dir,filename)\n","\n"," with open(input_file, 'r',encoding=\"utf8\") as f:\n"," input_text = f.read()\n"," with open(target_file, 'r',encoding=\"utf8\") as f:\n"," target_text = f.read()\n","\n"," data['input_text'].append(input_text)\n"," data['target_text'].append(target_text)\n","\n"," return pd.DataFrame(data)\n","\n","# Define dataset paths\n","input_dir = '/content/drive/MyDrive/RA_Internship/PACSUM/DATASET_PACSUM/dataset/inputs'\n","target_dir = '/content/drive/MyDrive/RA_Internship/PACSUM/DATASET_PACSUM/dataset/targets'\n","\n","# Load data\n","data_df = load_data(input_dir, target_dir)\n","\n","print(data_df)\n","\n","# Split data\n","train_df, temp_df = train_test_split(data_df, test_size=0.2, random_state=42)\n","eval_df, test_df = train_test_split(temp_df, test_size=0.5, random_state=42)\n","\n","# Convert to Dataset\n","train_dataset = Dataset.from_pandas(train_df)\n","eval_dataset = Dataset.from_pandas(eval_df)\n","test_dataset = Dataset.from_pandas(test_df)\n","\n","\n","\n","\n","\n"]},{"cell_type":"code","execution_count":5,"metadata":{"id":"iVclerTAUi95","executionInfo":{"status":"ok","timestamp":1719069192131,"user_tz":-240,"elapsed":1742,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}}},"outputs":[],"source":["from transformers import AutoTokenizer"]},{"cell_type":"code","execution_count":6,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":336,"referenced_widgets":["ecdb8f63bddc4f2db1a77ddfa46d99fc","68f82b1de2b24584909cea6a043444ea","9124128dc68a4593a28027a3853c7a03","5c10793da3df431482537a411a1aadf1","94cfef26947546468c76108f90f11165","e842abba177d4f029649b39679910663","d57cb3274e3c47bb9fa51f730a189f4b","c7f2738f701042eab5a0b50dd9fd5f3a","36877a755fdd4cd298402c95270cfd07","0bc19276f0fe45ec8d1fc9a3d46ece1b","d4318388366240f6882fc9a5b5134a79","59b15b30cf914307b487b6f8ba3ec239","8cc6c703125c48b8926c7cd45c6775b2","7f4d8bc1ece4400f9dd49b7ce165fdfa","eed92d3d29d84d348c9ebcaf9131bab6","f5657944f8e64e219775ea8157c0525c","3fb1c1aa8b2d43feb77e1d367c735100","2374033316b340bab4ce5a045443cb5a","6ea556b3cced4a1c9d3f2fb0839ab193","106d1a162c844255aec2db57b0676aa5","8922c0c548e04c73a5a144e34f4fdd2c","406202362dbc4e5e984b669219174d68","75ffc30eb01c4bdc98cfd6b67ea8f1c9","9520ec3d15794c3d8396ea7ecfc8b123","9eb418e45edf4be29bfa18aa4377afcc","5385bc6967524c45b240f960ee2bcc64","d69eb864d1ec4afe9c70bfbd1278f42b","6217cfbd70e647e1b97f3f0772c21f34","b97c0e58bcef4a14bc99554a95c6fb0b","48c8db6b164c41e09b71e98d602e1c41","0d60b884ec4640b3bcad7ad1f47c477a","0b47d9a01602436e96e189ce1bd339df","59c4c0a791424ee69f75b3d6c66fc74c","c61efb32db994c0593a956a6b873852f","203745f0707e4b118c74011b890ef379","5e84dc76263445a1b70f0583643aa6c4","3f2df79362e74effaf06cc454fd9c747","58f5b11fbfe84a1b8d6466ec98e23191","2ae5a2b3f585435592aa4af073a4f320","56777c8bd2514789bd407511f52088ba","57bba496fc674d2eab38be3cf095b64c","6bbfe6a4850c4742af76a235edee7062","b3582e74daa74899a9d74d47bd10590f","89341fa46b644be9aa184576258eb81a","dd1775ee870f4bd69aca8d4b8438bfec","9c971eace91548f487ce14ea4c07b4b7","710dc52e7a8d472687c5a94ffd0df86c","1d6300e9add4414fbfd1f8661c6fed2b","0b7a4b82b2bd46038a716cf179a8708b","4cb302e7a1714d7798dbaeb16d618ba5","a92472a09abf404890feb49a35f270f4","d42f693ab374420fa337baa315346fb8","d8e12a55c1354eeaac68dd240728ec88","bf94395dcc4d43a29f4f10013b8be9f8","ddcd538137234cf780ed04f6b0c2cd0d"]},"id":"n3omQKJ4UvC5","outputId":"0d272fac-a278-4d30-d265-af574fad59aa","executionInfo":{"status":"ok","timestamp":1719069199018,"user_tz":-240,"elapsed":4417,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}}},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n","The secret `HF_TOKEN` does not exist in your Colab secrets.\n","To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n","You will be able to reuse this secret in all of your notebooks.\n","Please note that authentication is recommended but still optional to access public models or datasets.\n"," warnings.warn(\n"]},{"output_type":"display_data","data":{"text/plain":["tokenizer_config.json: 0%| | 0.00/27.0 [00:00 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mprettyprint\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpprint\u001b[39;00m\n","\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'prettyprint'"]}],"source":["import prettyprint as pprint"]},{"cell_type":"code","execution_count":12,"metadata":{"id":"7WlGFTdri6ie","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1719069240192,"user_tz":-240,"elapsed":466,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}},"outputId":"437e5003-b6b7-4638-80a1-f7842c7aa33f"},"outputs":[{"output_type":"stream","name":"stdout","text":["INPUT: in these results, the generative model performs significantly better than the others, and does about equally well at assigning pa.rt- of-speech tags. 1 in t roduct ion in recent years, the statistical parsing community has begun to reach out; for syntactic formalisms that recognize the individuality of words, l,ink grammars (sleator and pemperley, 1991) and lex- icalized tree-adjoining ranunars (schabes, 1992) have now received stochastic treatments. other researchers, not wishing to abandon context-flee grammar (ci\"g) but disillusioned with its lexica] blind spot, have tried to re-parameterize stochas- tic ci\"g in context-sensitive ways (black et al., 1992) or have augmented the formalism with lex- ical headwords (magerman, 1995; collins, 11996). in this paper, we 1)resent a [lexible l)robat)ilistic parser that simultaneously assigns both part-of- sl)eech tags and a bare-bones dependency struc- ture (illustrate.d in l!igure 1). the choice o t a simple syntactic structure is deliberate: we would like to ask some basic questions about where hx- ical relationships al)pear and how best, to exploit *this materia.l is based upon work supported un- der a national science i%undation graduate fellow- ship, and has benefited greatly from discussions with mike collins, dan m(:lame(l, mitch marcus and ad- wait ratnaparkhi. (a) tile man in the coiner taught his dachsht , ld io play gol f i;os dt nn in dt nn vbd pp.p$ nn to vh nn /? man n ~.. phty~ j j - y , .% (b) the ill __ ~ / .~dachshund it) gol f . ) f cofllel his file figure 1: (a) a bare-l>ones dependen(-y parse. ]]a<:h word points to a single t)arent, the word it modities; the head of the sentence points to the eos (end-of: sentence) ma.rk. crossing links and cycles arc not al- lowed. (b) constituent structure and sub(:ategoriza- tion may be highlighted by displaying the same de- pendencies as a lexical tree. it is uscflfl to look into thes0 basic ques- tions before trying to tine-tmm the performance of systems whose behavior is harder to understand. 1 the main contribution of the work is to i)ro- pose three distin(t, lexiealist hyl)otheses abou(. (,he probability space underlying sehl]ence structure. we il]ustrate how each hypothesis is (:xl)ressed in a depemteney framework, and how each can be used to guide our parser toward its favored so- lution.three new probabi l is t ic mode ls for dependency parsing: an exploration* j ason m. e i sner cis depar tment , un ivers i ty of pe lmsy lva i f ia .\n","TARGET: three new probabilistic models for dependency parsing: an exploration after presenting a novel o(n3) parsing algorithm for dependency grammar, we develop three contrasting ways to stochasticize it. we propose (a) a lexical affinity model where words struggle to modify each other, (b) a sense tagging model where words fluctuate randomly in their selectional preferences, and (e) a generative model where the speaker fleshes out each word's syntactic and conceptual structure without regard to the implications for the hearer. we also give preliminary empirical results from evaluating the three models' parsing performance on annotated wall street journal training text (derived from the penn treebank). in these results, the generative model performs significantly better than the others, and does about equally well at assigning part-of-speech tags. the proposed parsing algorithm is sufficient for searching over all projective trees in o (n3) time.\n","hello\n"]}],"source":["print(\"INPUT: \",train_dataset['input_text'][146])\n","print(\"TARGET: \",train_dataset['target_text'][146])\n","print(\"hello\")"]},{"cell_type":"code","execution_count":13,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":49,"referenced_widgets":["6139894fdbd044aab8c6be77ed5089e5","26aa8367f12d40c9a6702c8af9c2ee10","361199cab8df4b49ab8303c84fe3bcb7","dc7782ad3f084181b385046df993a0cb","a8a8c29792b84efd9e599e7e1c4f55a7","d345f3dcaece4025a0fdd02172a1fc11","a00e959199f7474596479496160248f4","24ff5cba99f54929a3b334934808e765","2c24c33bdc0e44fa8fe947f70b8e1df2","b8d8c9978be249c1a8edeffae8551aca","7ed5d0535116411ba8c060466297add5"]},"id":"OTR1wU63WBOr","outputId":"b30408ce-a3a2-46dc-d081-d8ef0fddd531","executionInfo":{"status":"ok","timestamp":1719069268750,"user_tz":-240,"elapsed":1199,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}}},"outputs":[{"output_type":"display_data","data":{"text/plain":["Map: 0%| | 0/100 [00:00=1.14.0 in /usr/local/lib/python3.10/dist-packages (from rouge_score) (1.16.0)\n","Requirement already satisfied: click in /usr/local/lib/python3.10/dist-packages (from nltk->rouge_score) (8.1.7)\n","Requirement already satisfied: joblib in /usr/local/lib/python3.10/dist-packages (from nltk->rouge_score) (1.4.2)\n","Requirement already satisfied: regex>=2021.8.3 in /usr/local/lib/python3.10/dist-packages (from nltk->rouge_score) (2024.5.15)\n","Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from nltk->rouge_score) (4.66.4)\n","Building wheels for collected packages: rouge_score\n"," Building wheel for rouge_score (setup.py) ... \u001b[?25l\u001b[?25hdone\n"," Created wheel for rouge_score: filename=rouge_score-0.1.2-py3-none-any.whl size=24933 sha256=33f623cb03c94c81d403f7425dedad596efad637e9caa9ffa3111bf225e96a26\n"," Stored in directory: /root/.cache/pip/wheels/5f/dd/89/461065a73be61a532ff8599a28e9beef17985c9e9c31e541b4\n","Successfully built rouge_score\n","Installing collected packages: rouge_score\n","Successfully installed rouge_score-0.1.2\n"]},{"output_type":"stream","name":"stderr","text":[":2: FutureWarning: load_metric is deprecated and will be removed in the next major version of datasets. Use 'evaluate.load' instead, from the new library 🤗 Evaluate: https://huggingface.co/docs/evaluate\n"," rouge = load_metric(\"rouge\")\n","/usr/local/lib/python3.10/dist-packages/datasets/load.py:759: FutureWarning: The repository for rouge contains custom code which must be executed to correctly load the metric. You can inspect the repository content at https://raw.githubusercontent.com/huggingface/datasets/2.19.2/metrics/rouge/rouge.py\n","You can avoid this message in future by passing the argument `trust_remote_code=True`.\n","Passing `trust_remote_code=True` will be mandatory to load this metric from the next major release of `datasets`.\n"," warnings.warn(\n"]},{"output_type":"display_data","data":{"text/plain":["Downloading builder script: 0%| | 0.00/2.17k [00:00=1.17 in /usr/local/lib/python3.10/dist-packages (from accelerate) (1.25.2)\n","Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from accelerate) (24.0)\n","Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from accelerate) (5.9.5)\n","Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from accelerate) (6.0.1)\n","Requirement already satisfied: torch>=1.10.0 in /usr/local/lib/python3.10/dist-packages (from accelerate) 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torch>=1.10.0->accelerate) (2.3.0)\n","Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.10.0->accelerate)\n"," Downloading nvidia_nvjitlink_cu12-12.5.40-py3-none-manylinux2014_x86_64.whl (21.3 MB)\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.3/21.3 MB\u001b[0m \u001b[31m35.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hRequirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->accelerate) (2.31.0)\n","Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->accelerate) (4.66.4)\n","Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.10.0->accelerate) (2.1.5)\n","Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (3.3.2)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (3.7)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (2.0.7)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate) (2024.2.2)\n","Requirement already satisfied: mpmath<1.4.0,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.10.0->accelerate) (1.3.0)\n","Installing collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, accelerate\n","Successfully installed accelerate-0.30.1 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.40 nvidia-nvtx-cu12-12.1.105\n"]}],"source":["!pip install accelerate -U"]},{"cell_type":"code","execution_count":19,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"h6UGccgsXO3S","outputId":"2536e50b-fbc4-4c2c-d83b-e3cb651f41d6","executionInfo":{"status":"ok","timestamp":1719069318289,"user_tz":-240,"elapsed":417,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}}},"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.10/dist-packages/transformers/training_args.py:1474: FutureWarning: `evaluation_strategy` is deprecated and will be removed in version 4.46 of 🤗 Transformers. Use `eval_strategy` instead\n"," warnings.warn(\n"]}],"source":["# enable fp16 apex training\n","training_args = Seq2SeqTrainingArguments(\n"," predict_with_generate=True,\n"," evaluation_strategy=\"steps\",\n"," per_device_train_batch_size=batch_size,\n"," per_device_eval_batch_size=batch_size,\n"," fp16=True,\n"," output_dir=\"./\",\n"," logging_steps=5,\n"," eval_steps=10,\n"," save_steps=10,\n"," save_total_limit=2,\n"," gradient_accumulation_steps=4,\n"," num_train_epochs=5,\n",")"]},{"cell_type":"code","execution_count":20,"metadata":{"id":"SM9e_n8xY6KE","executionInfo":{"status":"ok","timestamp":1719069322007,"user_tz":-240,"elapsed":622,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}}},"outputs":[],"source":["trainer = Seq2SeqTrainer(\n"," model=led,\n"," tokenizer=tokenizer,\n"," args=training_args,\n"," #compute_metrics=compute_metrics,\n"," train_dataset=train_dataset,\n"," eval_dataset=eval_dataset,\n",")"]},{"cell_type":"code","execution_count":21,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"kLjtjhv4ZNCP","outputId":"d514be5f-05f5-45db-9a54-4243a0a2731a","executionInfo":{"status":"ok","timestamp":1719071945641,"user_tz":-240,"elapsed":2619356,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}}},"outputs":[{"output_type":"display_data","data":{"text/plain":[""],"text/html":["\n","
\n"," \n"," \n"," [500/500 43:33, Epoch 5/5]\n","
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StepTraining LossValidation Loss
102.8648002.881588
202.9889002.786632
303.0516002.739434
402.6605002.713189
502.8093002.675948
602.9206002.660659
702.8094002.657620
802.5233002.632737
902.6508002.611667
1002.8456002.586114
1102.4622002.594203
1202.2871002.575082
1302.4482002.577598
1402.4079002.577733
1502.2842002.562148
1602.6267002.546337
1702.3895002.550294
1802.2786002.547001
1902.3628002.542010
2002.2809002.536673
2102.2726002.540544
2202.1934002.567594
2302.2447002.539946
2402.4508002.543459
2502.2969002.549047
2602.4206002.531697
2702.0131002.537778
2802.0025002.549222
2902.2179002.527988
3002.2082002.518951
3101.9491002.560796
3202.2910002.544772
3302.0431002.531899
3402.0671002.552888
3502.1939002.538817
3602.0606002.530621
3702.0088002.555676
3802.1919002.531735
3902.2516002.529018
4001.9401002.540375
4102.1101002.535391
4201.8906002.551980
4301.9808002.548765
4401.8195002.549592
4501.8512002.553532
4602.0464002.551943
4702.0176002.545003
4802.0686002.545952
4902.0267002.546269
5001.8617002.546145

"]},"metadata":{}},{"output_type":"stream","name":"stderr","text":["Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n","Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n"]},{"output_type":"execute_result","data":{"text/plain":["TrainOutput(global_step=500, training_loss=2.2905156116485594, metrics={'train_runtime': 2618.8179, 'train_samples_per_second': 1.525, 'train_steps_per_second': 0.191, 'total_flos': 2.157463663017984e+16, 'train_loss': 2.2905156116485594, 'epoch': 5.0})"]},"metadata":{},"execution_count":21}],"source":["trainer.train()"]},{"cell_type":"code","execution_count":22,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":734},"id":"7q8GUp1cQDiW","outputId":"608e9dcb-fea9-4882-a3b0-5d1adb18018d","executionInfo":{"status":"ok","timestamp":1719072078816,"user_tz":-240,"elapsed":1728,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}}},"outputs":[{"output_type":"display_data","data":{"text/plain":["

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\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["
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9evXa8xTKBQSRVP+cY+yOJo3Fz+5R8lYxUckbl8pxVTIGx4oFArY2tpqTFWrVgUADBkyBD4+PhrtlUolrKys8PvvvwMADhw4gPbt28PS0hLVq1fHu+++i9u3b5dMHv+zY8cONG7cGAqFAk5OTvjhhx80li9fvhz169eHkZERatSoAW9vb/Wy7du3o23btqhSpQqqV6+Obt26ISUlpUTjex33KIujWTPx8949ID4eqFZN0nAYY6UoNRUwNdXJW+kBsHx9xosXQJUqJbLtoUOHYtCgQeoL9gHg4MGDSE1NxYABAwAAKSkp+Oyzz+Dq6ooXL15g1qxZGDBgACIjI0vkcosLFy7g/fffx+zZs+Hj44OTJ09iwoQJqF69Ovz8/HD+/Hl88skn2LBhA9q2bYv4+HgcP34cABATE4OhQ4dizpw58PX1RUpKCo4fP16qd0/iQlkclpZA3brAnTtiQE/XrlJHxBhj2Lt3r7oIZvn666/x9ddfo0ePHqhSpQqCg4MxbNgwAMDmzZvh5eWlfoDxwIEDNdZdt24drK2tER0djSZNmhQ7vh9//BFdu3bFzJkzAQANGjRAdHQ0Fi9eDD8/Pzx48ABVqlTBu+++CzMzMzg6OqLZfx2TmJgYZGRk4N1334WTkxP09PTQtGnTYsekDR96LS4e0MNY5WBiInp2OphUSUlI+OcfqJKSxDwTk0KF+s477yAyMlJjGj9+PADAwMAA77//PjZt2gRA9B53796NoUOHqte/efMmBg8ejLp168Lc3BxOTk4AgAcPHpRIKq9evYp27dppzGvXrh1u3ryJzMxMeHp6wtHREXXr1sWwYcOwadMmpKamAgDc3NzQtWtXtG/fHu+//z5Wr16Nf//9t0Tiygv3KIvL3R3Yvp0H9DBW0clkJXb4M18qFZCZKd6vCIc6q1Spgnr16uW5fOjQoejUqROePHmCkJAQGBsba4yK7du3LxwdHbF69WrY29tDpVKhSZMmSE9PL9LuFJaZmRkuXryIsLAwHDp0CLNmzcLs2bNx7tw5WFpa4uDBgwgJCcHJkyexdOlSTJ8+HWfOnEGdOnVKJR7uURYXD+hhjJUzbdu2hYODA4KCgrBp0yYMGjQIcrkcAPD8+XNcv34dM2bMQNeuXeHi4lLiPTYXFxecOHFCY96JEyfQoEED6OvrAxA9327dumHRokX466+/cO/ePRw9ehSAuK1gmzZtMHv2bFy6dAmGhoYIDg4u0Rhfxz3K4soa0HPzJpCUBJibSxsPY6zSS0tLQ2xsrMY8AwMDWFlZqV8PGTIEK1euxI0bNxAaGqqeX7VqVVSvXh2rVq2CnZ0dHjx4gKlTpxYpjqdPn+a4KYGdnR0+//xztGzZEnPnzoWPjw9OnTqFZcuWYfny5QDEOdY7d+6gY8eOqFq1Kvbt2weVSoWGDRvizJkzOHz4MNq2bYs6derg3LlzePr0KVxcXIoUY4FQJZOYmEgAKDExMd+26enptGvXLkpPT9fe0MGBCCAKDy+hKMuHAuenEuLcaFce8vPy5UuKjo6mly9f6vy9MzMz6d9//6XMzMxCrztixAgCkGNq2LChRrvo6GgCQI6OjqRSqTSWhYSEkIuLCykUCnJ1daWwsDACQMHBwUREdPfuXQJAly5dyjOOTp065RrH3LlziYho+/bt1KhRI5LL5VS7dm1avHixet3jx49Tp06dqGrVqmRsbEyurq4UFBSkjrt79+5kZWVFCoWCGjRoQEuXLs0zDm3/jgWtB9yjLAnu7sDDh+Lwa8eOUkfDGKvEAgMDERgYmG87FxeXPC+p6NatG6KjozXmvd7Wyckp38sxwsLCtC4fOHBgjtG1Wdq3b5/n+i4uLti/fz+SkpJgbm6uk8eQ8TnKksCP3GKMsQqLC2VJ4AE9jDFWYXGhLAlZPcpr18TtphhjjFUYXChLgp0dYGsrrn366y+po2GMMVaCuFCWFD5PyViFlN+gFVa2lcS/HxfKksLnKRmrULIufNfV3WhY6ci69V3WDRWKgi8PKSl8z1fGKhQDAwOYmJjg6dOnkMvlOrkMIYtKpUJ6ejpevXql0/ctLwqSHyJCamoqnjx5AktLS/UXn6LgQllSsgrl338Dr14BRkbSxsMYKxaZTAY7OzvcvXsX9+/f1+l7ExFevnwJY2NjyGQynb53eVCY/FhaWsLW1rZY78eFsqQ4OADVqwPPnwNRUUCLFlJHxBgrJkNDQ9SvX1/nh1+VSiWOHTuGjh07FuuQYUVV0PzI5fJi9SSzSFooFyxYgJ07d+LatWswNjZG27Zt8d1336Fhw4Za11uyZAlWrFiBBw8ewMrKCt7e3liwYAGMpOzFyWSiVxkSIgb0cKFkrELQ09PT+d8WfX19ZGRkwMjIiAtlLnSdH0kPfoeHh8Pf3x+nT59GSEgIlEolunfvjhQt1yJu3rwZU6dORUBAAK5evYq1a9ciKCgIX3/9tQ4jzwMP6GGMsQpH0h7lgQMHNF4HBgbCxsYGFy5cQMc87pl68uRJtGvXDkOGDAEg7jk4ePBgnDlzptTjzRcP6GGMsQqnTJ2jTExMBABUq1YtzzZt27bFxo0bcfbsWbRq1Qp37tzBvn37MGzYsFzbp6WlIS0tTf06KSkJgDjGrVQqtcaTtTy/dmpNm0IOgP76CxmpqUAFP2RS6PxUIpwb7Tg/2nF+tCup/BR0fRmVkatpVSoVvLy8kJCQgIiICK1tf/75Z0yZMgVEhIyMDIwfPx4rVqzIte3s2bMxZ86cHPM3b94MExOTEoldjQi9hw6FPDUVof/7H5JK6WnbjDHGii81NRVDhgxBYmIizLU8S7jMFMqPPvoI+/fvR0REBGrVqpVnu7CwMPj6+uLbb79F69atcevWLUyaNAljxozBzJkzc7TPrUfp4OCAZ8+eaU0MIL5thISEwNPTs8AnjPU9PaEXHo6MVatAfn4FWqe8Kkp+KgvOjXacH+04P9qVVH6SkpJgZWWVb6EsE4deJ06ciL179+LYsWNaiyQAzJw5E8OGDcOHH34IAGjatClSUlIwduxYTJ8+PcfFpwqFAgqFIsd25HJ5gRNcmLZo0QIID4fB5csV/tBrlkLlp5Lh3GjH+dGO86NdcfNT0HUlLZREhI8//hjBwcEICwtDnQIcqkxNTc1RDLOukykTnWMe0MMYYxWKpIXS398fmzdvxu7du2FmZobY2FgAgIWFBYyNjQEAw4cPR82aNbFgwQIAQN++ffHjjz+iWbNm6kOvM2fORN++fUvkwtJiyyqUkZFAZiZQFmJijDFWZJIWyqwBOJ07d9aYv379evj9d37vwYMHGj3IGTNmQCaTYcaMGXj06BGsra3Rt29fzJs3T1dha1e/PmBuDiQlAcePA2/sG2OMsfJF8kOv+QkLC9N4bWBggICAAAQEBJRSVMWkrw/4+gKrVgGrV3OhZIyxco5vS18axowRP3fsAOLjpY2FMcZYsXChLA3NmwNvvw2kpQEbNkgdDWOMsWLgQlkaZDLgv8tXsHo1UBZG4zLGGCsSLpSlZehQwNhYPJ/y9Gmpo2GMMVZEXChLi6UlMGiQ+H31aklDYYwxVnRcKEtT1qCeoCBxuQhjjLFyhwtlaWrXDnBxAVJTgc2bpY6GMcZYEXChLE1vDuphjDFW7nChLG3DhwOGhuLer3z/V8YYK3e4UJY2KytgwADx+5o10sbCGGOs0LhQ6kLWoJ5Nm4CUFGljYYwxVihcKHXhnXeAunXFyNdt26SOhjHGWCFwodQFPT0e1MMYY+UUF0pd8fMTTxY5eVLcrYcxxli5wIVSV+zsgL59xe88qIcxxsoNLpS6lDWo5/ffgVevpI2FMcZYgXCh1KUePQAHB/GMyh9/lDoaxhhjBcCFUpf09YG5c8XvAQHA+fPSxsMYYyxfXCh1bfhw8VSRjAxgyBC+rpIxxso4LpS6JpMBK1cCtWoBN28Cn34qdUSMMca0KFKhfPjwIf755x/167Nnz2Ly5MlYtWpViQVWoVWrJgb0yGTiusrgYKkjYowxlociFcohQ4YgNDQUABAbGwtPT0+cPXsW06dPxzfffFOiAVZY77wDfPGF+H3MGODxY2njYYwxlqsiFcqoqCi0atUKAPDHH3+gSZMmOHnyJDZt2oTAwMCSjK9imzsXaNYMeP5c3JBApZI6IsYYY28oUqFUKpVQKBQAgMOHD8PLywsA4OzsjJiYmJKLrqIzNBQ3Sjc2BkJCgJ9/ljoixhhjbyhSoWzcuDFWrlyJ48ePIyQkBD179gQAPH78GNWrVy/RACs8F5fsayq/+gr46y9p42GMMaahSIXyu+++w6+//orOnTtj8ODBcHNzAwDs2bNHfUiWFcK4ceL2dunp4pKRly+ljogxxth/DIqyUufOnfHs2TMkJSWhatWq6vljx46FiYlJiQVXachk4v6vrq7ihukLFwJz5kgdFWOMMRSxR/ny5UukpaWpi+T9+/exZMkSXL9+HTY2NiUaYKVhY5N9jnLJEuDffyUNhzHGmFCkQtmvXz/8/vvvAICEhAS0bt0aP/zwA/r3748VK1YUeDsLFixAy5YtYWZmBhsbG/Tv3x/Xr1/Xuk7nzp0hk8lyTH369CnKrpQt3t5A06biAc9LlkgdDWOMMRSxUF68eBEdOnQAAGzfvh01atTA/fv38fvvv+PnQozcDA8Ph7+/P06fPo2QkBAolUp0794dKVpu67Zz507ExMSop6ioKOjr62PQoEFF2ZWyRU9P3AMW4F4lY4yVEUU6R5mamgozMzMAwKFDh/Dee+9BT08Pbdq0wf379wu8nQMHDmi8DgwMhI2NDS5cuICOHTvmuk61atU0Xm/duhUmJiYVo1ACwIABold55YoolnyukjHGJFWkQlmvXj3s2rULAwYMwMGDB/Hpf/crffLkCczNzYscTGJiIoCcxVCbtWvXwtfXF1WqVMl1eVpaGtLS0tSvk5KSAIhrQZVKpdZtZy3Pr11Jk02fDgNfX9CSJcjw9wdeGzBVlkiVn/KAc6Md50c7zo92JZWfgq4vIyIq7Ma3b9+OIUOGIDMzE126dEFISAgAcc7x2LFj2L9/f2E3CZVKBS8vLyQkJCAiIqJA65w9exatW7fGmTNn8rwsZfbs2ZiTS69s8+bNZXeErkqFzp9+Cov793HNxwfXBw+WOiLGGKtwUlNTMWTIECQmJmrt5BWpUALiHq8xMTFwc3ODnp441Xn27FmYm5vD2dm50Nv76KOPsH//fkRERKBWrVoFWmfcuHE4deoU/tJykX5uPUoHBwc8e/Ys396vUqlESEgIPD09IZfLC7YjJUS2c6foVZqbI+PmzTLZq5QyP2Ud50Y7zo92nB/tSio/SUlJsLKyyrdQFunQKwDY2trC1tZW/RSRWrVqFflmAxMnTsTevXtx7NixAhfJlJQUbN26Nd+bsCsUCvXt9l4nl8sLnODCtC0xgwYB8+ZBduUK5L/8UqbPVUqSn3KCc6Md50c7zo92xc1PQdct0qhXlUqFb775BhYWFnB0dISjoyMsLS0xd+5cqApxY28iwsSJExEcHIyjR4+iTp06BV5327ZtSEtLwwcffFCUXSj7eAQsY4yVCUUqlNOnT8eyZcuwcOFCXLp0CZcuXcL8+fOxdOlSzJw5s8Db8ff3x8aNG7F582aYmZkhNjYWsbGxePnaLdyGDx+OadOm5Vh37dq16N+/f8W+t2zWCFi+rpIxxiRTpEOvv/32G9asWaN+aggAuLq6ombNmpgwYQLmzZtXoO1k3Zygc+fOGvPXr18PPz8/AMCDBw/U50CzXL9+HRERETh06FBRwi8/snqV3t6iUE6eXCbPVTLGWEVWpEIZHx+f64AdZ2dnxMfHF3g7BRlHFBYWlmNew4YNC7RuhcDXVTLGmKSKdOjVzc0Ny5YtyzF/2bJlcHV1LXZQ7DV8rpIxxiRVpB7lokWL0KdPHxw+fBgeHh4AgFOnTuHhw4fYt29fiQbIoNmr/PJLYOVKQF9f6qgYY6xSKFKPslOnTrhx4wYGDBiAhIQEJCQk4L333sPff/+NDRs2lHSMTE8PyDrvu2YN4OUF/HcXI8YYY6WryNdR2tvb5xi0c/nyZaxduxarVq0qdmDsDX37Alu2ACNHAvv2AW3aAHv2APXrSx0ZY4xVaEXqUTKJ+PoCERFAzZrAtWtAq1bAf7cPZIwxVjq4UJY3zZsD58+LHmVCAtCrl3jgc2UZBcwYYzrGhbI8srUFQkOBESOAzExg0iRgzBjgtXvaMsYYKxmFOkf53nvvaV2ekJBQnFhYYRgZAevXA66uwBdfAGvXAtu3A40a5ZwcHACZTOqIGWOsXCpUobSwsMh3+fDhw4sVECsEmQz47DNRDD/4AHj+HDh1Skyvq1IF6N8fWLcOMDSUJFTGGCuvClUo169fX1pxsOLo2RN49Ai4cQOIjs6erl4V81JSgE2bAGtr4H//kzpaxhgrV4p8eQgrYxQKcVOCpk015yuVwM6dYsTskiVAp06id8kYY6xAeDBPRSeXAz4+wOefi9cjRwL37kkaEmOMlSdcKCuLBQuyLynx8QHS06WOiDHGygUulJWFXA5s3Soe03X2LDB1qtQRMcZYucCFsjJxdAQCA8Xv//sfsHu3pOEwxlh5wIWysvHyAj79VPzu5wfcvy9pOIwxVtZxoayMFi4U94nl85WMMZYvLpSVkaEhEBQEWFoCZ84AX38tdUSMMVZmcaGsrJycxC3wAOCHH4DNmyUNhzHGyioulJVZ//7AlCnidz8/caN1xhhjGrhQVnbffQcMGiTu4NO/P3DlitQRMcZYmcKFsrLT0wN+/x3o0AFIShLPt/znH6mjYoyxMoMLJROP7Nq1C3BxETdX79ULSEyUOirGGCsTuFAyoVo1YP9+wM4OiIoCBgzgB0Ezxhi4ULLXOToC+/YBpqZiYM/IkYBKJXVUjDEmKS6UTNPbbwM7dgAGBsCWLcC0aVJHxBhjkuJCyXLq3h1Ys0b8vmhR9v1hGWOsEuJCyXI3YgQwe7b43d8fuHZN0nAYY0wqkhbKBQsWoGXLljAzM4ONjQ369++P69ev57teQkIC/P39YWdnB4VCgQYNGmDfvn06iLiSmTkT6NoVSE0FfH2BV6+kjogxxnRO0kIZHh4Of39/nD59GiEhIVAqlejevTtSUlLyXCc9PR2enp64d+8etm/fjuvXr2P16tWoWbOmDiOvJPT0gA0bAGtr4PJl4KuvpI6IMcZ0zkDKNz9w4IDG68DAQNjY2ODChQvo2LFjruusW7cO8fHxOHnyJORyOQDAyckpz/dIS0tD2muXOSQlJQEAlEollEql1viylufXrkKzsoJszRoY9OsH/PwzMjp3Br37LgDOjzacG+04P9pxfrQrqfwUdH0ZEVGx3qkE3bp1C/Xr18eVK1fQpEmTXNv07t0b1apVg4mJCXbv3g1ra2sMGTIEX331FfT19XO0nz17NubMmZNj/ubNm2FiYlLi+1BRNV63DvX27EGamRnClizBq+rVpQ6JMcaKJTU1FUOGDEFiYiLMzc3zbFdmCqVKpYKXlxcSEhIQERGRZztnZ2fcu3cPQ4cOxYQJE3Dr1i1MmDABn3zyCQICAnK0z61H6eDggGfPnmlNDCC+bYSEhMDT01Pde6200tJg0LEjZJcuQdWpEzIPHIBSpco9P0olZEePgho3BmrVki5mCfFnRzvOj3acH+1KKj9JSUmwsrLKt1BKeuj1df7+/oiKitJaJAFRUG1sbLBq1Sro6+ujefPmePToERYvXpxroVQoFFAoFDnmy+XyAie4MG0rLLkc2LoVcHeHXng49L7/Xn3OUp2fZ8+AX38Fli8HHj8W5zbDw8Wt8Sop/uxox/nRjvOjXXHzU9B1y8TlIRMnTsTevXsRGhqKWvn0QOzs7NCgQQONw6wuLi6IjY1Fenp6aYdauTVoIIogAMyeDdnJk+L3K1eADz8EHByAGTNEkdTTA54+Bbp0AW7ckC5mxhgrJkkLJRFh4sSJCA4OxtGjR1GnTp1812nXrh1u3boF1Wu3Vrtx4wbs7OxgaGhYmuEyABg+HPjgAyAzE/rDhqHtzJmQN28OrF0rLh9p3lw8jeThQ6BpUyA2VhTLO3ekjpwxxopE0kLp7++PjRs3YvPmzTAzM0NsbCxiY2Px8uVLdZvhw4dj2mu3Ufvoo48QHx+PSZMm4caNG/i///s/zJ8/H/7+/lLsQuW0fDnw1luQPXwI6ytXQHp6gLc3EBEBnDsHDBsG2NsDhw9nP5GkSxfg/n2pI2eMsUKTtFCuWLECiYmJ6Ny5M+zs7NRTUFCQus2DBw8QExOjfu3g4ICDBw/i3LlzcHV1xSeffIJJkyZh6tSpUuxC5WRmBuzYAVWnTrg5YAAybtwAtm0D2rUDZLLsdjY2wJEjQP36okh26SKKJmOMlSOSDuYpyIDbsLCwHPM8PDxw+vTpUoiIFZibGzJDQhC9bx+catfOu52dHXD0KNCpkzj82qULEBYm5hcGkZgAcf6TMcZ0pMyMemUVWK1aolh27CgG9nTrJh4U/e+/onjevp398/ZtMXpWpcqeXi+SlpbAkiXiXrSMMaYDXCiZbjg6imdcduwIREeLEbRFkZAA+PkBV68C8+dz75IxVuq4UDLdqVtXFMvevYFbt8Th17feElPdutm/29qK52HKZKIQZk0yGfDTT8C33wLffSeeaLJxo3jQNGOMlRIulEy36tcXh19fvQKMjQu//ty5YiTtqFHA7t1A+/bAnj2AtvOk5U16OqCvLybGmOT4uBXTPZmsaEUyy5AhYkBQjRriqSatWgEVZXDXzZtAzZpi8BPfEJuxMoELJSuf2rQBzp4FXF2BuDigc2dgyxapoyqejAwxSOnZM+DECXEOljEmOS6UrPyqXVsUFC8vIC1N9DRnzcoeIVveLF4MnDoFZN1h6ttvgYsXpY1JCkolsHmzuKsTY2UAF0pWvpmaAjt3Al9+KV7PnQsMHgy8dnenciEyEsi6qf+qVcDAgaKH6ecnvgRUJjNmAEOHitshXrokdTSMcaFkFYC+vhgFu26dGC0bFCRubBAXJ3VkBfPqlbjtn1IJDBgg7qe7YoV4+sqVK6L4VxbJycDKleL3x4+BDh2AvXuljUkbpRLYtIlvz1jB8ahXVnGMHAk4OYne2OnTQOvW4o9sHg8BLzNmzQKiosQt/379VQx2srYWxdLbG1i4EOjXD2jZUupIS9+6dUBSkrjO1tERCAkR+75kCfDxx8Xb9rVrwIMHgKen5q0Wi2PKFODnn8WlThcvikubpJaRIb48FncfiUS+zp4VU9aj86ytxWf19cnWFqhSpWTiL4O4ULKK5Z13RJHs00dcq9m2LfDHH0DPnjnbEok258+LPyxNm4rLVwx0+N/i+HHg++/F76tXiz9CWQYOFIeRt2wRg3wuXgSMjHQXm65lZoqCCACffy6++EyYAKxZA3zyibhr0w8/FO2ymfPnxYCvlBTAx0cc3s7nwe352rVLFEkAiIkBfH3FgwB0+fl506+/Al98IYpkkybiM92kSfZkZaXZnkicpnjxQuTm5k1RFM+cET+fPCnY++rpiTtujRgB9O8PmJiU+K5JiiqZxMREAkCJiYn5tk1PT6ddu3ZRenq6DiIrf8p0fp49I+rYUdz8Tk+P6JdfiJ48IfrzT6KZM4l69CCqWjXr5njZk0JB1KwZ0fDhRIsXEx04INYrpALlJimJqE4d8b6jRuW9HzVqiDZffFHoOOjBA6Lly4l69yZydCQKCir8NvJy6BBR06ZELVuKOAsh1/xs3y72s3p1otRUMU+lIlq4MPvfx8uL6MWLwsV5+zaRjY3mv3P9+kSRkYXbzuvu3SOytBTbGjyYyMxM/D5lStG3+ZpC/99SqYhmzMj5eX5zqlGDqG5d8dPUlEgm097ewICoeXOijz4S/x+mTSMaPZqob1+i1q3F57dKFc11zM2JxowhiogQcZWCkvrbU9B6wD1KVjFVrw4cOgSMGwf89hvg7y+mNykUQLNm4r/4lStAaqoYQPLmIBJXV3HIztNTnDcriW/Mn38O3L0rDjH+739578eqVeLw4/ffi2/rbdvmvU2VCrhwAfjzTzFFRmou9/UVtwEcO7boccfEAJ99Bmzdmj2vXz/RmypOj/fHH8XPjz7Kvs5WJgO++krcuWnYMHFziY4dxb7Z2+e/zWfPxNGEJ0+At98W57I//FD0nNq0AZYuBUaPLtxhSqUyO4+tWgGBgSIeb2/xb9SmjTgaoCtKpficr18vXgcEiFiiosRnOipKTHfuaD9vb2IictqqlTht0aqVyFlB/k1v3xbPof3tN3G+dvVqMdWrJwZmVasmzj+/Ob14IQarZWSI/XjzJ5Hmnbn++90AQOeUFDHyvVmzksiidsUqx+UQ9yhLTrnIj0pFNH9+9jdnFxeiESNEL+v8eaK0tOy2mZlEt24RBQcTffMN0aBBRA0b5vyWbWhI9M47Yrvnzon13pBvbv78U2xLJiMKC8t/P4YPz+4JpaRk79vjx0T79olYBg0isrXVjFUmI2rblmjBAqIPP8yev3BhoVNJGRlEP/8segxZPfUxY4gsLMTrQYNyzUVucuTn9Ons3MbE5L7SyZNEVlainbU10a5d2t8kJYWoTRvR3tFR5IpI9H57987OxbBhheulfvmlWM/CgujOnez5U6aI+aamRFevFnx7uSjw/63kZKKePcX76usTrV6tve25c0QnThBdviw+6zExYn4B/93ylZlJFBpK5OeXs6dZCpPy1KlihVvQesCFUotyUQgkVK7yEx9PlJBQtHWfPCHaskUcHnVwyPkf1tpa/LHdvFl9CDLX3KSkiD9SS5ZkH0797LOCx29vL9bp2lUcOn7zcGLWZGpKNHAgUWCg5mFjlUocOstq9+WXBT80dvYskbt79rqtWhFdvCiWHT1KJJcXan9y5MfHR6zv56d9xdu3iVxds+MYOZIot//LGRlE/fqJNlWrEkVHay7PzBRfFvT1s79A/f13/oHv25f93jt2aC5TKok6dcreXnJy/tvLg/LPP+na+++TcufO3PePiCg2VhwWBYiMjcWXr7IkOZnot9/EF6j33xeHbCdPFqc+Fi0iWrGCaMMGom3bxJeevXvFqY4jR4jCw8X/lZMnxc/jx8W8sDCio0dJeeAAnZgzh9ILecj/TVwo88CFsuRUyvyoVETXrxMtW0bUv3/2uamsSU+PyMODMgICKOKbb0i5fLnoybm5Zf9RzpoaNSJ6+bLg7/36H+nX38/FRZwn++478Ufm1Svt21m0KHv9sWNFUclNZibRqVOi15jVI7e0FH/g3lxn48bsbf70U767ovHZuXcvOzeXL+efh1evRJHPisnJSfwRzaJSiXNqWeecIyLy3lZ4OJGdXXax+fhjops3c2/7zz/ZPdqJE3NvExOTvT0fn8Kfo7t7V5yHffM8Ybt2RAEBYl/S04lu3BDnGgER0+nThXufck7X5yi5UGpRKQtBIXB+SBy6DQ0Vf7ibNMn/cJGtrRgIMXdukQYJ0cqVogisXCn+OGYdhi2s1atFkQXEt/2sQ9AZGUTHjhF98glRrVqasX/wgejF5GX+/OzDvTt3an17jc/O55+L9bp1K9w+HDuWPRhKJhOHPl++1IzjzV5fbuLiiLp31zxc7eUl/l2zCp1SSdShg1jerJn2LzgREaK4AeLoQUGkpYm4jY2JAFIZGNCjNm1I9dZbOT9DZmbZh7vr1hVFs5LhQlnKuFCWHM5PLh48IFq1ijK9vCjF2poyu3YVhzt37iR6+LDURgEWybZt2YdMu3cnmjAh5zlOU1MiX9+CnUdVqUQPFSAyMhK90TyoPzvPnmWf89y3r/D7kJQkDullxZtVOAFxPrWgVCoxirdXL839f/ttcQh76tTsfBSkMP30U3ZvcM8e7V9ojhwhcnbOfs9OnSg9MjL7/9adO0SrVolDmNWqZbdr3lz7F5cKjAtlKeNCWXI4P3krN7k5eJDIxESzOFhYiHOuu3cX7tAwkeh5ZQ2UsbLK8zBmVn4yvv8++5xecQaU7N6tec62KJfSZImOJho/Xt2705i2bCnYNlQqcTj89XVr1hSDwMaOFZdaBAcTDR2avdzGRpyzU6ny/vxkZhJduCDaFfYymQqELw9hjOlO9+7iso4pU8RzPgcOBLp2zb4xe2Fl3UKwc2dxmUr37uISjN69c1yCIcvMhN6yZeLFp5+Kof9F5eUFeHiIuxxZWQFz5hR9Wy4u4q5I334rLnFYtgx49EhcguHrW7BtyGTisp7MTHF3oX//Fdt49Eg8vPzNthMmiPeztNS+XT09wN1dTExnuFAyVtl5eIinsJQUU1Nx60APD3Gd6LvvimvdZswQ14H+VxBtz5yB7N49Udg++KD475t127+SUr06MHWquN41Olrc5aYwTE3FlwYAeP5cXLt586Z4cHnWT2trYN48oEWLkoublTgulIyxkmdrK26BtmiRKF6XLoneaqNGwPTpwHvvod7u3aLt6zcYKIvkcsDNrXjbqF5dTG3alExMTKf46SGMsdJhbS2esXnvnuhNmpuLntnQoTBwdka169dBhobisCNjZRgXSsZY6bKyEo8Ku39f/KxWDbL/HktFgweXjSduMKYFF0rGmG5YWoqe5f37yFy4EP+0b4/M2bOljoqxfPE5SsaYbpmaQvXZZ7jg7IzeNWtKHQ1j+eIeJWOMMaYFF0rGGGNMCy6UjDHGmBZcKBljjDEtKt1gHiICACQlJeXbVqlUIjU1FUlJSZDL5aUdWrnD+ckb50Y7zo92nB/tSio/WXUgqy7kpdIVyuTkZACAg4ODxJEwxhgrC5KTk2FhYZHnchnlV0orGJVKhcePH8PMzAyyN27S/KakpCQ4ODjg4cOHMDc311GE5QfnJ2+cG+04P9pxfrQrqfwQEZKTk2Fvbw89LTflr3Q9Sj09PdSqVatQ65ibm/OHVQvOT944N9pxfrTj/GhXEvnR1pPMwoN5GGOMMS24UDLGGGNacKHUQqFQICAgAAqFQupQyiTOT944N9pxfrTj/Gin6/xUusE8jDHGWGFwj5IxxhjTggslY4wxpgUXSsYYY0wLLpSMMcaYFlwo8/DLL7/AyckJRkZGaN26Nc6ePSt1SDpx7Ngx9O3bF/b29pDJZNi1a5fGciLCrFmzYGdnB2NjY3Tr1g03b97UaBMfH4+hQ4fC3NwclpaWGD16NF68eKHDvSgdCxYsQMuWLWFmZgYbGxv0798f169f12jz6tUr+Pv7o3r16jA1NcXAgQMRFxen0ebBgwfo06cPTExMYGNjgy+++AIZGRm63JVSsWLFCri6uqovAvfw8MD+/fvVyytzbnKzcOFCyGQyTJ48WT2vMudo9uzZkMlkGpOzs7N6uaS5IZbD1q1bydDQkNatW0d///03jRkzhiwtLSkuLk7q0Erdvn37aPr06bRz504CQMHBwRrLFy5cSBYWFrRr1y66fPkyeXl5UZ06dejly5fqNj179iQ3Nzc6ffo0HT9+nOrVq0eDBw/W8Z6UvB49etD69espKiqKIiMjqXfv3lS7dm168eKFus348ePJwcGBjhw5QufPn6c2bdpQ27Zt1cszMjKoSZMm1K1bN7p06RLt27ePrKysaNq0aVLsUonas2cP/d///R/duHGDrl+/Tl9//TXJ5XKKiooiosqdmzedPXuWnJycyNXVlSZNmqSeX5lzFBAQQI0bN6aYmBj19PTpU/VyKXPDhTIXrVq1In9/f/XrzMxMsre3pwULFkgYle69WShVKhXZ2trS4sWL1fMSEhJIoVDQli1biIgoOjqaANC5c+fUbfbv308ymYwePXqks9h14cmTJwSAwsPDiUjkQi6X07Zt29Rtrl69SgDo1KlTRCS+iOjp6VFsbKy6zYoVK8jc3JzS0tJ0uwM6ULVqVVqzZg3n5jXJyclUv359CgkJoU6dOqkLZWXPUUBAALm5ueW6TOrc8KHXN6Snp+PChQvo1q2bep6enh66deuGU6dOSRiZ9O7evYvY2FiN3FhYWKB169bq3Jw6dQqWlpZo0aKFuk23bt2gp6eHM2fO6Dzm0pSYmAgAqFatGgDgwoULUCqVGvlxdnZG7dq1NfLTtGlT1KhRQ92mR48eSEpKwt9//63D6EtXZmYmtm7dipSUFHh4eHBuXuPv748+ffpo5ALgzw8A3Lx5E/b29qhbty6GDh2KBw8eAJA+N5Xupuj5efbsGTIzMzWSDQA1atTAtWvXJIqqbIiNjQWAXHOTtSw2NhY2NjYayw0MDFCtWjV1m4pApVJh8uTJaNeuHZo0aQJA7LuhoSEsLS012r6Zn9zyl7WsvLty5Qo8PDzw6tUrmJqaIjg4GI0aNUJkZGSlzw0AbN26FRcvXsS5c+dyLKvsn5/WrVsjMDAQDRs2RExMDObMmYMOHTogKipK8txwoWSsCPz9/REVFYWIiAipQylTGjZsiMjISCQmJmL79u0YMWIEwsPDpQ6rTHj48CEmTZqEkJAQGBkZSR1OmdOrVy/1766urmjdujUcHR3xxx9/wNjYWMLIeNRrDlZWVtDX188xmiouLg62trYSRVU2ZO2/ttzY2triyZMnGsszMjIQHx9fYfI3ceJE7N27F6GhoRqPbLO1tUV6ejoSEhI02r+Zn9zyl7WsvDM0NES9evXQvHlzLFiwAG5ubvjpp584NxCHD588eQJ3d3cYGBjAwMAA4eHh+Pnnn2FgYIAaNWpU+hy9ztLSEg0aNMCtW7ck//xwoXyDoaEhmjdvjiNHjqjnqVQqHDlyBB4eHhJGJr06derA1tZWIzdJSUk4c+aMOjceHh5ISEjAhQsX1G2OHj0KlUqF1q1b6zzmkkREmDhxIoKDg3H06FHUqVNHY3nz5s0hl8s18nP9+nU8ePBAIz9XrlzR+DIREhICc3NzNGrUSDc7okMqlQppaWmcGwBdu3bFlStXEBkZqZ5atGiBoUOHqn+v7Dl63YsXL3D79m3Y2dlJ//kp1lCgCmrr1q2kUCgoMDCQoqOjaezYsWRpaakxmqqiSk5OpkuXLtGlS5cIAP3444906dIlun//PhGJy0MsLS1p9+7d9Ndff1G/fv1yvTykWbNmdObMGYqIiKD69etXiMtDPvroI7KwsKCwsDCNIeypqanqNuPHj6fatWvT0aNH6fz58+Th4UEeHh7q5VlD2Lt3706RkZF04MABsra2rhDD+6dOnUrh4eF09+5d+uuvv2jq1Kkkk8no0KFDRFS5c5OX10e9ElXuHH3++ecUFhZGd+/epRMnTlC3bt3IysqKnjx5QkTS5oYLZR6WLl1KtWvXJkNDQ2rVqhWdPn1a6pB0IjQ0lADkmEaMGEFE4hKRmTNnUo0aNUihUFDXrl3p+vXrGtt4/vw5DR48mExNTcnc3JxGjhxJycnJEuxNycotLwBo/fr16jYvX76kCRMmUNWqVcnExIQGDBhAMTExGtu5d+8e9erVi4yNjcnKyoo+//xzUiqVOt6bkjdq1ChydHQkQ0NDsra2pq5du6qLJFHlzk1e3iyUlTlHPj4+ZGdnR4aGhlSzZk3y8fGhW7duqZdLmRt+zBZjjDGmBZ+jZIwxxrTgQskYY4xpwYWSMcYY04ILJWOMMaYFF0rGGGNMCy6UjDHGmBZcKBljjDEtuFAyxhhjWnChZIwxxrTgQslYOff06VN89NFHqF27NhQKBWxtbdGjRw+cOHECACCTybBr1y5pg2SsHOPnUTJWzg0cOBDp6en47bffULduXcTFxeHIkSN4/vy51KExViHwvV4ZK8cSEhJQtWpVhIWFoVOnTjmWOzk54f79++rXjo6OuHfvHgBg9+7dmDNnDqKjo2Fvb48RI0Zg+vTpMDAQ359lMhmWL1+OPXv2ICwsDHZ2dli0aBG8vb11sm+MlRV86JWxcszU1BSmpqbYtWsX0tLSciw/d+4cAGD9+vWIiYlRvz5+/DiGDx+OSZMmITo6Gr/++isCAwMxb948jfVnzpyJgQMH4vLlyxg6dCh8fX1x9erV0t8xxsoQ7lEyVs7t2LEDY8aMwcuXL+Hu7o5OnTrB19cXrq6uAETPMDg4GP3791ev061bN3Tt2hXTpk1Tz9u4cSO+/PJLPH78WL3e+PHjsWLFCnWbNm3awN3dHcuXL9fNzjFWBnCPkrFybuDAgXj8+DH27NmDnj17IiwsDO7u7ggMDMxzncuXL+Obb75R90hNTU0xZswYxMTEIDU1Vd0u6+nxr7/mHiWrbHgwD2MVgJGRETw9PeHp6YmZM2fiww8/REBAAPz8/HJt/+LFC8yZMwfvvfderttijGXjHiVjFVCjRo2QkpICAJDL5cjMzNRY7u7ujuvXr6NevXo5Jj297D8Lp0+f1ljv9OnTcHFxKf0dYKwM4R4lY+XY8+fPMWjQIIwaNQqurq4wMzPD+fPnsWjRIvTr1w+AGPl65MgRtGvXDgqFAlWrVsWsWbPw7rvvonbt2vD29oaenh4uX76MqKgofPvtt+rtb9u2DS1atED79u2xadMmnD17FmvXrpVqdxmTBjHGyq1Xr17R1KlTyd3dnSwsLMjExIQaNmxIM2bMoNTUVCIi2rNnD9WrV48MDAzI0dFRve6BAweobdu2ZGxsTObm5tSqVStatWqVejkA+uWXX8jT05MUCgU5OTlRUFCQrneRMcnxqFfGWK5yGy3LWGXE5ygZY4wxLbhQMsYYY1rwYB7GWK74rAxjAvcoGWOMMS24UDLGGGNacKFkjDHGtOBCyRhjjGnBhZIxxhjTggslY4wxpgUXSsYYY0wLLpSMMcaYFv8PDlHZDUry688AAAAASUVORK5CYII=\n"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["
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pandas as pd\n","df=pd.DataFrame(trainer.state.log_history)\n","import pandas as pd\n","import matplotlib.pyplot as plt\n","\n","# Assuming df is already defined, and train_loss and eval_loss are subsets of df\n","train_loss = df[['loss', 'step']]\n","eval_loss = df[['eval_loss', 'step']]\n","\n","# Remove NaN rows in both dataframes\n","train_loss_clean = train_loss.dropna()\n","eval_loss_clean = eval_loss.dropna()\n","\n","# Plotting the loss vs step for train_loss\n","plt.figure(figsize=(5, 2))\n","plt.plot(train_loss_clean['step'], train_loss_clean['loss'], label='Train Loss', color='blue')\n","plt.xlabel('Step')\n","plt.ylabel('Loss')\n","plt.title('Train Loss vs Step')\n","plt.legend()\n","plt.grid(True)\n","plt.show()\n","\n","# Plotting the loss vs step for eval_loss\n","plt.figure(figsize=(5, 2))\n","plt.plot(eval_loss_clean['step'], eval_loss_clean['eval_loss'], label='Eval Loss', color='red')\n","plt.xlabel('Step')\n","plt.ylabel('Loss')\n","plt.title('Eval Loss vs Step')\n","plt.legend()\n","plt.grid(True)\n","plt.show()\n","\n","# Plotting both losses together\n","plt.figure(figsize=(5, 2))\n","plt.plot(train_loss_clean['step'], train_loss_clean['loss'], label='Train Loss', color='blue')\n","plt.plot(eval_loss_clean['step'], eval_loss_clean['eval_loss'], label='Eval Loss', color='red')\n","plt.xlabel('Step')\n","plt.ylabel('Loss')\n","plt.title('Train and Eval Loss vs Step')\n","plt.legend()\n","plt.grid(True)\n","plt.show()\n"]},{"cell_type":"code","source":["df"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":443},"id":"wzsaK7v-kEJf","executionInfo":{"status":"ok","timestamp":1719072085407,"user_tz":-240,"elapsed":459,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}},"outputId":"87a0725a-3cb5-4bef-c787-09ff7d6302a0"},"execution_count":23,"outputs":[{"output_type":"execute_result","data":{"text/plain":[" loss grad_norm learning_rate epoch step eval_loss eval_runtime \\\n","0 3.4511 4.837308 4.950000e-05 0.05 5 NaN NaN \n","1 2.8648 3.968866 4.900000e-05 0.10 10 NaN NaN \n","2 NaN NaN NaN 0.10 10 2.881588 13.1553 \n","3 2.7824 3.681087 4.850000e-05 0.15 15 NaN NaN \n","4 2.9889 3.684774 4.800000e-05 0.20 20 NaN NaN \n",".. ... ... ... ... ... ... ... \n","146 NaN NaN NaN 4.90 490 2.546269 13.1952 \n","147 1.9039 3.169846 5.000000e-07 4.95 495 NaN NaN \n","148 1.8617 4.006496 0.000000e+00 5.00 500 NaN NaN \n","149 NaN NaN NaN 5.00 500 2.546145 13.1942 \n","150 NaN NaN NaN 5.00 500 NaN NaN \n","\n"," eval_samples_per_second eval_steps_per_second train_runtime \\\n","0 NaN NaN NaN \n","1 NaN NaN NaN \n","2 7.601 3.801 NaN \n","3 NaN NaN NaN \n","4 NaN NaN NaN \n",".. ... ... ... \n","146 7.578 3.789 NaN \n","147 NaN NaN NaN \n","148 NaN NaN NaN \n","149 7.579 3.790 NaN \n","150 NaN NaN 2618.8179 \n","\n"," train_samples_per_second train_steps_per_second total_flos \\\n","0 NaN NaN NaN \n","1 NaN NaN NaN \n","2 NaN NaN NaN \n","3 NaN NaN NaN \n","4 NaN NaN NaN \n",".. ... ... 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lossgrad_normlearning_rateepochstepeval_losseval_runtimeeval_samples_per_secondeval_steps_per_secondtrain_runtimetrain_samples_per_secondtrain_steps_per_secondtotal_flostrain_loss
03.45114.8373084.950000e-050.055NaNNaNNaNNaNNaNNaNNaNNaNNaN
12.86483.9688664.900000e-050.1010NaNNaNNaNNaNNaNNaNNaNNaNNaN
2NaNNaNNaN0.10102.88158813.15537.6013.801NaNNaNNaNNaNNaN
32.78243.6810874.850000e-050.1515NaNNaNNaNNaNNaNNaNNaNNaNNaN
42.98893.6847744.800000e-050.2020NaNNaNNaNNaNNaNNaNNaNNaNNaN
.............................................
146NaNNaNNaN4.904902.54626913.19527.5783.789NaNNaNNaNNaNNaN
1471.90393.1698465.000000e-074.95495NaNNaNNaNNaNNaNNaNNaNNaNNaN
1481.86174.0064960.000000e+005.00500NaNNaNNaNNaNNaNNaNNaNNaNNaN
149NaNNaNNaN5.005002.54614513.19427.5793.790NaNNaNNaNNaNNaN
150NaNNaNNaN5.00500NaNNaNNaNNaN2618.81791.5250.1912.157464e+162.290516
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\"\"\n }\n },\n {\n \"column\": \"eval_runtime\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.025352032805022493,\n \"min\": 13.1224,\n \"max\": 13.2284,\n \"num_unique_values\": 49,\n \"samples\": [\n 13.1801,\n 13.1597,\n 13.1952\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"eval_samples_per_second\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.0145731651626249,\n \"min\": 7.56,\n \"max\": 7.621,\n \"num_unique_values\": 31,\n \"samples\": [\n 7.568,\n 7.577,\n 7.586\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"eval_steps_per_second\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.007301216001601441,\n \"min\": 3.78,\n \"max\": 3.81,\n \"num_unique_values\": 24,\n \"samples\": [\n 3.788,\n 3.781,\n 3.801\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"train_runtime\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": null,\n \"min\": 2618.8179,\n \"max\": 2618.8179,\n \"num_unique_values\": 1,\n \"samples\": [\n 2618.8179\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"train_samples_per_second\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": null,\n \"min\": 1.525,\n \"max\": 1.525,\n \"num_unique_values\": 1,\n \"samples\": [\n 1.525\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"train_steps_per_second\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": null,\n \"min\": 0.191,\n \"max\": 0.191,\n \"num_unique_values\": 1,\n \"samples\": [\n 0.191\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"total_flos\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": null,\n \"min\": 2.157463663017984e+16,\n \"max\": 2.157463663017984e+16,\n \"num_unique_values\": 1,\n \"samples\": [\n 2.157463663017984e+16\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"train_loss\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": null,\n \"min\": 2.2905156116485594,\n \"max\": 2.2905156116485594,\n \"num_unique_values\": 1,\n \"samples\": [\n 2.2905156116485594\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}"}},"metadata":{},"execution_count":23}]},{"cell_type":"code","source":["# Assuming 'your_actual_output_directory' is the correct path where your model files are located\n","trainer.args.output_dir = '/content/drive/MyDrive/RA_Internship/PACSUM/DATASET_PACSUM'\n","\n","trainer.push_to_hub()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":237,"referenced_widgets":["eed064226daa42209faf3e2babbff2f5","701215520cf84d03afb988b169a30942","0762e779663e4c67a6779a938218f11b","31e3a0cffbf143ee922892b33a50d951","2d74cff91ac94df9a9fa2642161e15eb","6c6177779cf545948f439e8ac18bf86a","e0ae64ef5bbe4bf2a52bfc9766de5b93","96e8e511882a4a05abb3fbe3b6b3cab4","7c060dad24f24f37a9cdb3324326e6a1","f347597eb9fc43b9b143739bd2562264","3cd9acc15d6a45c5b521d69794bfd8cc","66c051fa36ec46bfbb09ceb3b62f684e","d73d8bf0b6d24cd88ad3357630122ce1","367cbb5ba74b461987fe4a8f8023ce8f","4642f6097cc842b8af2fa2d20d9f1d58","f8d0a657ad9f47a3986ba1e110b80f1b","e573ad694d5b41debce92dfb799f9d83","6a55f9956e874452bdfe2c3c09b271ac","42583383d55f4d6e8fcd004297361855","01d7d2b76a1846f18fb51aeaae1376cb","1798c8e65d214b01a16f65c3c254a6d8","842e0564de4b4ec4b58fca9c6e483077","1a903fc546ea488185c3ccebc6be18c0","2239406bfdf34d7da43e233294d6526e","cbdb5b0dea34496c8a1f9a58137aa557","b1422da2142745878aa9577f57c9e4f8","cfd3ea3c4adc412986022080aa5818d1","7cae8f8703124378a4c79d1e02514d73","52ed6a648c7a41f18184938cf38edce3","9687044615594e6980ea419fc3420a17","874386d2c2eb48b4b7380a7926d3ee69","83ca2408969e480d8a236ff1b39ea17b","22bc5b72b248443da26136ce6e0ee965"]},"id":"BsPnIUQ5i3Tj","executionInfo":{"status":"ok","timestamp":1719075352277,"user_tz":-240,"elapsed":58285,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}},"outputId":"6567ef8a-d3af-4aea-a4b4-2227f65c4834"},"execution_count":28,"outputs":[{"output_type":"stream","name":"stderr","text":["Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n","Non-default generation parameters: {'max_length': 512, 'min_length': 100, 'early_stopping': True, 'num_beams': 2, 'length_penalty': 2.0, 'no_repeat_ngram_size': 3}\n","Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n"]},{"output_type":"display_data","data":{"text/plain":["Upload 2 LFS files: 0%| | 0/2 [00:00=2.0.0 (from evaluate)\n"," Downloading datasets-2.19.2-py3-none-any.whl (542 kB)\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m542.1/542.1 kB\u001b[0m \u001b[31m5.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from evaluate) (1.25.2)\n","Collecting dill (from evaluate)\n"," Downloading dill-0.3.8-py3-none-any.whl (116 kB)\n","\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m13.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from evaluate) (2.0.3)\n","Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages 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This behaviour is the source of the following dependency conflicts.\n","google-colab 1.0.0 requires requests==2.31.0, but you have requests 2.32.3 which is incompatible.\u001b[0m\u001b[31m\n","\u001b[0mSuccessfully installed datasets-2.19.2 dill-0.3.8 evaluate-0.4.2 multiprocess-0.70.16 requests-2.32.3 xxhash-3.4.1\n"]},{"output_type":"display_data","data":{"application/vnd.colab-display-data+json":{"pip_warning":{"packages":["requests"]},"id":"1b11a3f4549d46ef834d30aa92a1c59a"}},"metadata":{}}]},{"source":["!pip install rouge_score"],"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"JhnsXhiG2CWs","executionInfo":{"status":"ok","timestamp":1717992473963,"user_tz":-240,"elapsed":8544,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}},"outputId":"5514a1d1-524d-4659-cfe9-d9d2e7dbd6cc"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting rouge_score\n"," Downloading rouge_score-0.1.2.tar.gz (17 kB)\n"," Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n","Requirement already satisfied: absl-py in /usr/local/lib/python3.10/dist-packages (from rouge_score) (1.4.0)\n","Requirement already satisfied: nltk in /usr/local/lib/python3.10/dist-packages (from rouge_score) (3.8.1)\n","Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from rouge_score) (1.25.2)\n","Requirement already satisfied: six>=1.14.0 in /usr/local/lib/python3.10/dist-packages (from rouge_score) (1.16.0)\n","Requirement already satisfied: click in /usr/local/lib/python3.10/dist-packages (from nltk->rouge_score) (8.1.7)\n","Requirement already satisfied: joblib in /usr/local/lib/python3.10/dist-packages (from nltk->rouge_score) (1.4.2)\n","Requirement already satisfied: regex>=2021.8.3 in /usr/local/lib/python3.10/dist-packages (from nltk->rouge_score) (2024.5.15)\n","Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from nltk->rouge_score) (4.66.4)\n","Building wheels for collected packages: rouge_score\n"," Building wheel for rouge_score (setup.py) ... \u001b[?25l\u001b[?25hdone\n"," Created wheel for rouge_score: filename=rouge_score-0.1.2-py3-none-any.whl size=24933 sha256=168b4badeb6312bb6379796e24a0fd6725b6d396e6e0d7eed0bbb302376ee608\n"," Stored in directory: /root/.cache/pip/wheels/5f/dd/89/461065a73be61a532ff8599a28e9beef17985c9e9c31e541b4\n","Successfully built rouge_score\n","Installing collected packages: rouge_score\n","Successfully installed rouge_score-0.1.2\n"]}]},{"cell_type":"code","source":["from evaluate import load\n","# Load the ROUGE metric\n","import evaluate\n","rouge = evaluate.load('rouge')"],"metadata":{"id":"RdsN4yTZ1dgn"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["candidates = [generated_summary]\n","\n","references = [[target_text]\n"," ]\n","results = rouge.compute(predictions=candidates, references=references)\n","print(results)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"AQl7VcgT2NSM","executionInfo":{"status":"ok","timestamp":1717992545609,"user_tz":-240,"elapsed":416,"user":{"displayName":"Aditi Paretkar","userId":"17466297872366651006"}},"outputId":"f0476ce9-a2bc-446a-fced-1742640177e7"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["{'rouge1': 0.45502645502645495, 'rouge2': 0.1702127659574468, 'rougeL': 0.2380952380952381, 'rougeLsum': 0.2380952380952381}\n"]}]}],"metadata":{"colab":{"provenance":[],"machine_shape":"hm","gpuType":"A100"},"kernelspec":{"display_name":"Python 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