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Le","userId":"02258782812217274557"}}},"outputs":[],"source":["import re\n","import string\n","import numpy as np\n","import random\n","import pandas as pd\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","%matplotlib inline\n","from plotly import graph_objs as go\n","import plotly.express as px\n","import plotly.figure_factory as ff\n","from collections import Counter\n","\n","from PIL import Image\n","from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator\n","\n","\n","import nltk\n","from nltk.corpus import stopwords\n","from nltk.tokenize import word_tokenize\n","\n","from tqdm import tqdm\n","import os\n","import nltk\n","import spacy\n","import random\n","from spacy.util import compounding\n","from spacy.util import minibatch\n","\n","from collections import defaultdict\n","from collections import Counter\n","\n","import keras\n","from keras.models import Sequential\n","from keras.initializers import Constant\n","from keras.layers import (LSTM,\n"," Embedding,\n"," BatchNormalization,\n"," Dense,\n"," TimeDistributed,\n"," Dropout,\n"," Bidirectional,\n"," Flatten,\n"," GlobalMaxPool1D)\n","from keras.preprocessing.text import Tokenizer\n","from keras.preprocessing.sequence import pad_sequences\n","# from keras.layers.embeddings import Embedding\n","from keras.callbacks import ModelCheckpoint, ReduceLROnPlateau\n","from keras.optimizers import Adam\n","\n","from sklearn.metrics import (\n"," precision_score,\n"," recall_score,\n"," f1_score,\n"," classification_report,\n"," accuracy_score\n",")\n","import torch, os\n","import pandas as pd\n","from transformers import pipeline, BertForSequenceClassification, BertTokenizerFast\n","from torch.utils.data import Dataset"]},{"cell_type":"code","source":["!pip install accelerate -U"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"te4T8LBfQU2v","executionInfo":{"status":"ok","timestamp":1721280039419,"user_tz":-420,"elapsed":71504,"user":{"displayName":"Le Le","userId":"02258782812217274557"}},"outputId":"d5f487ec-917c-4a78-9b99-066995f812d7"},"execution_count":8,"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting accelerate\n"," Downloading accelerate-0.32.1-py3-none-any.whl (314 kB)\n","\u001b[?25l \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/314.1 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K \u001b[91m━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[90m╺\u001b[0m\u001b[90m━━━━━━━━━━━━━\u001b[0m \u001b[32m204.8/314.1 kB\u001b[0m \u001b[31m6.3 MB/s\u001b[0m eta \u001b[36m0:00:01\u001b[0m\r\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m314.1/314.1 kB\u001b[0m \u001b[31m6.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hRequirement already satisfied: numpy<2.0.0,>=1.17 in /usr/local/lib/python3.10/dist-packages (from accelerate) (1.25.2)\n","Requirement already satisfied: packaging>=20.0 in 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/usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (1.13.0)\n","Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from 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==2.3.1 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate) (2.3.1)\n","Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.10.0->accelerate)\n"," Downloading nvidia_nvjitlink_cu12-12.5.82-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[31m20.9 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) (2024.7.4)\n","Requirement already satisfied: mpmath<1.4,>=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-0.32.1 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-cu12-12.5.82 nvidia-nvtx-cu12-12.1.105\n"]}]},{"cell_type":"code","source":["dataset = pd.read_csv(\"/content/drive/MyDrive/ThaiLand/Data/finetuned/afterProcessing.csv\")"],"metadata":{"id":"-ILANLavQXm_","executionInfo":{"status":"ok","timestamp":1721280115790,"user_tz":-420,"elapsed":673,"user":{"displayName":"Le Le","userId":"02258782812217274557"}}},"execution_count":2,"outputs":[]},{"cell_type":"code","source":["from torch import cuda\n","device = 'cuda' if cuda.is_available() else 'cpu'\n","device"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":36},"id":"iAf1Ub1rQoaV","executionInfo":{"status":"ok","timestamp":1721280115791,"user_tz":-420,"elapsed":18,"user":{"displayName":"Le Le","userId":"02258782812217274557"}},"outputId":"d5425a20-66c9-46a9-824e-ed8463b3c5f5"},"execution_count":3,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'cuda'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":3}]},{"cell_type":"code","source":["dataset = dataset.sample(frac=1.0, random_state=42)"],"metadata":{"id":"3l45jG65Q7QL","executionInfo":{"status":"ok","timestamp":1721280115791,"user_tz":-420,"elapsed":16,"user":{"displayName":"Le Le","userId":"02258782812217274557"}}},"execution_count":4,"outputs":[]},{"cell_type":"code","source":["labels = dataset['sentiment'].unique().tolist()\n","labels = [s.strip() for s in labels ]\n","labels"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"cDmG_mWWQ9Zh","executionInfo":{"status":"ok","timestamp":1721280115791,"user_tz":-420,"elapsed":16,"user":{"displayName":"Le Le","userId":"02258782812217274557"}},"outputId":"b4132e30-5414-457c-9185-a5f629a0bd6d"},"execution_count":5,"outputs":[{"output_type":"execute_result","data":{"text/plain":["['Positive', 'Neutral', 'Negative']"]},"metadata":{},"execution_count":5}]},{"cell_type":"code","source":["for key, value in enumerate(labels):\n"," print(value)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"-gPsU9_iRAnS","executionInfo":{"status":"ok","timestamp":1721280115791,"user_tz":-420,"elapsed":15,"user":{"displayName":"Le Le","userId":"02258782812217274557"}},"outputId":"f732f5b8-52f2-47d5-9998-a7e11a3b7658"},"execution_count":6,"outputs":[{"output_type":"stream","name":"stdout","text":["Positive\n","Neutral\n","Negative\n"]}]},{"cell_type":"code","source":["NUM_LABELS= len(labels)\n","\n","id2label={id:label for id,label in enumerate(labels)}\n","\n","label2id={label:id for id,label in enumerate(labels)}"],"metadata":{"id":"ZD4qISrFRBoI","executionInfo":{"status":"ok","timestamp":1721280115791,"user_tz":-420,"elapsed":14,"user":{"displayName":"Le Le","userId":"02258782812217274557"}}},"execution_count":7,"outputs":[]},{"cell_type":"code","source":["dataset[\"labels\"]=dataset.sentiment.map(lambda x: label2id[x.strip()])"],"metadata":{"id":"3ZXKRXtrREns","executionInfo":{"status":"ok","timestamp":1721280115792,"user_tz":-420,"elapsed":15,"user":{"displayName":"Le Le","userId":"02258782812217274557"}}},"execution_count":8,"outputs":[]},{"cell_type":"code","source":["tokenizer = BertTokenizerFast.from_pretrained(\"ProsusAI/finbert\", max_length=512)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":249,"referenced_widgets":["4c1db77f7131490c9b7913a0e657c061","77ee6ab4b31f47789cb9f1df7dcc1dc9","343f349617cb40bdbce950f5e0c39e7c","12dea7a6f5c5453f90df11a068a0eb21","d745b639f7a2417e9162b8755daf46c4","4e9e03501e1f4852acd6cf6c25a63a38","c64b5aa4b012456aa8ee272097f59770","d194cd9ab7134e43b19b1c4dfb013b54","50262a51f70245bf85dae103f13f8b0c","10805c2321a743b393a589b849d24ab4","d502d3b63e954ef2a1db0f6c80eeaf22","2dc61c5fe0fe47a28851b1a89a3fd81b","9c43569ede994d23bbfed687b2ba0a9e","5d9f334c833a4eb290954f1fe138fef9","f6883b2a67b849aaba998ac86543447a","d957b82a5cf34bf09cf3246cfdb977c0","2d6cdb4acfcf44da85040b15f26f8663","350aab0911694f0bb0d25a189b5597da","e7f11a9bb67c47db8dfcd075abfa680d","758ae67c24204729853e96ae7d6d198f","3c7d7ede820b4f36a5a82380dc0418cb","94a1ab82e3ef4ce1b23b7c19eba4522e","c52bd193e16b4a46bd9448919848b1ba","dbb0b4dc9b06410eb470c3a0f816a1d6","f8041547dbd44b1296ea2a9dfd116b27","31f416302aa64a0fb809fa2750c7a68b","2bf239b1c803422dbaf1146074a909d6","308e4b8a771c4149b54f9920c3054c65","8cfd0ff385f44fe68c7e7905d90fde77","0fbbc4bc74054caf864aca2141ccb81e","d157dffa311f42dc8050cf49a65d5af3","42f5e9c8f503468f970b66bbdff7ba59","50200764bb584526a72cdb3c83a91a1d","e7b3556f30ed499283cb50e1e6e99077","7b0f65c69b7746da8fc05b83f2c82a5d","92b4291ad78d4a2e872b2066cb33bb27","ce04528401cc4b64ab55f3292839e824","a3a8b14b44be4ee0a896209d2cac3ed6","9039bf753f65475c82190c17943f80eb","cc539086ade141838b077de8c7a74d3e","1b962e27eac04d35a8a517fd719e4845","f31d0c35190b41f8b1e8658bf652fd90","94b2178d06914cc29a309b21807006ef","639833706e064d50a735a161894f5f6f"]},"id":"5a23ZfEGRG8D","executionInfo":{"status":"ok","timestamp":1721280118966,"user_tz":-420,"elapsed":3188,"user":{"displayName":"Le Le","userId":"02258782812217274557"}},"outputId":"ff0540ad-975d-4229-b432-b13212b3781b"},"execution_count":9,"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%| | 0.00/252 [00:00"],"text/html":["\n"," \n"," \n","
\n"," [1830/1830 1:03:13, Epoch 3/3]\n","
\n"," \n"," \n"," | Step | \n"," Training Loss | \n"," Validation Loss | \n"," Accuracy | \n"," F1 | \n"," Precision | \n"," Recall | \n","
\n"," \n"," \n"," \n"," | 50 | \n"," 1.215200 | \n"," 0.614000 | \n"," 0.700410 | \n"," 0.654520 | \n"," 0.733853 | \n"," 0.702028 | \n","
\n"," \n"," | 100 | \n"," 0.535700 | \n"," 0.473581 | \n"," 0.826462 | \n"," 0.821550 | \n"," 0.826996 | \n"," 0.826804 | \n","
\n"," \n"," | 150 | \n"," 0.442100 | \n"," 0.418947 | \n"," 0.850051 | \n"," 0.846622 | \n"," 0.849416 | \n"," 0.850491 | \n","
\n"," \n"," | 200 | \n"," 0.459100 | \n"," 0.417725 | \n"," 0.838974 | \n"," 0.833642 | \n"," 0.841746 | \n"," 0.839463 | \n","
\n"," \n"," | 250 | \n"," 0.438200 | \n"," 0.387644 | \n"," 0.854872 | \n"," 0.853693 | \n"," 0.853832 | \n"," 0.855017 | \n","
\n"," \n"," | 300 | \n"," 0.400200 | \n"," 0.406291 | \n"," 0.843385 | \n"," 0.845370 | \n"," 0.850290 | \n"," 0.843340 | \n","
\n"," \n"," | 350 | \n"," 0.408500 | \n"," 0.381836 | \n"," 0.857641 | \n"," 0.857365 | \n"," 0.857235 | \n"," 0.857941 | \n","
\n"," \n"," | 400 | \n"," 0.369200 | \n"," 0.370010 | \n"," 0.860821 | \n"," 0.859204 | \n"," 0.859768 | \n"," 0.861085 | \n","
\n"," \n"," | 450 | \n"," 0.368600 | \n"," 0.372971 | \n"," 0.861026 | \n"," 0.860391 | \n"," 0.860033 | \n"," 0.861260 | \n","
\n"," \n"," | 500 | \n"," 0.396600 | \n"," 0.376049 | \n"," 0.856615 | \n"," 0.857340 | \n"," 0.858361 | \n"," 0.856850 | \n","
\n"," \n"," | 550 | \n"," 0.372900 | \n"," 0.353303 | \n"," 0.867282 | \n"," 0.866727 | \n"," 0.866365 | \n"," 0.867522 | \n","
\n"," \n"," | 600 | \n"," 0.360500 | \n"," 0.358157 | \n"," 0.863179 | \n"," 0.863681 | \n"," 0.864476 | \n"," 0.863239 | \n","
\n"," \n"," | 650 | \n"," 0.347100 | \n"," 0.367144 | \n"," 0.864410 | \n"," 0.864313 | \n"," 0.864586 | \n"," 0.864471 | \n","
\n"," \n"," | 700 | \n"," 0.339700 | \n"," 0.363200 | \n"," 0.865846 | \n"," 0.865801 | \n"," 0.865614 | \n"," 0.866027 | \n","
\n"," \n"," | 750 | \n"," 0.297700 | \n"," 0.373714 | \n"," 0.863077 | \n"," 0.861932 | \n"," 0.861959 | \n"," 0.863432 | \n","
\n"," \n"," | 800 | \n"," 0.304700 | \n"," 0.360875 | \n"," 0.865641 | \n"," 0.866366 | \n"," 0.867339 | \n"," 0.865733 | \n","
\n"," \n"," | 850 | \n"," 0.281700 | \n"," 0.381632 | \n"," 0.868205 | \n"," 0.866136 | \n"," 0.867533 | \n"," 0.868517 | \n","
\n"," \n"," | 900 | \n"," 0.266700 | \n"," 0.373397 | \n"," 0.869026 | \n"," 0.868028 | \n"," 0.868553 | \n"," 0.869162 | \n","
\n"," \n"," | 950 | \n"," 0.280900 | \n"," 0.352265 | \n"," 0.870154 | \n"," 0.870576 | \n"," 0.870962 | \n"," 0.870274 | \n","
\n"," \n"," | 1000 | \n"," 0.296400 | \n"," 0.362135 | \n"," 0.870872 | \n"," 0.869292 | \n"," 0.870477 | \n"," 0.871104 | \n","
\n"," \n"," | 1050 | \n"," 0.299300 | \n"," 0.350195 | \n"," 0.873128 | \n"," 0.872778 | \n"," 0.872898 | \n"," 0.873227 | \n","
\n"," \n"," | 1100 | \n"," 0.315300 | \n"," 0.353175 | \n"," 0.872308 | \n"," 0.870296 | \n"," 0.871765 | \n"," 0.872607 | \n","
\n"," \n"," | 1150 | \n"," 0.308900 | \n"," 0.358130 | \n"," 0.872103 | \n"," 0.870992 | \n"," 0.871133 | \n"," 0.872372 | \n","
\n"," \n"," | 1200 | \n"," 0.302700 | \n"," 0.351292 | \n"," 0.872513 | \n"," 0.871211 | \n"," 0.871867 | \n"," 0.872669 | \n","
\n"," \n"," | 1250 | \n"," 0.229400 | \n"," 0.367332 | \n"," 0.871385 | \n"," 0.871496 | \n"," 0.871498 | \n"," 0.871527 | \n","
\n"," \n"," | 1300 | \n"," 0.232100 | \n"," 0.363012 | \n"," 0.871590 | \n"," 0.871842 | \n"," 0.872701 | \n"," 0.871609 | \n","
\n"," \n"," | 1350 | \n"," 0.200300 | \n"," 0.395148 | \n"," 0.872000 | \n"," 0.871407 | \n"," 0.871124 | \n"," 0.872225 | \n","
\n"," \n"," | 1400 | \n"," 0.194800 | \n"," 0.391207 | \n"," 0.872410 | \n"," 0.872140 | \n"," 0.871925 | \n"," 0.872579 | \n","
\n"," \n"," | 1450 | \n"," 0.193900 | \n"," 0.387140 | \n"," 0.873333 | \n"," 0.873423 | \n"," 0.873431 | \n"," 0.873477 | \n","
\n"," \n"," | 1500 | \n"," 0.189700 | \n"," 0.393748 | \n"," 0.873846 | \n"," 0.873173 | \n"," 0.872961 | \n"," 0.874070 | \n","
\n"," \n"," | 1550 | \n"," 0.195100 | \n"," 0.391498 | \n"," 0.871077 | \n"," 0.870204 | \n"," 0.870351 | \n"," 0.871258 | \n","
\n"," \n"," | 1600 | \n"," 0.193000 | \n"," 0.390159 | \n"," 0.873231 | \n"," 0.872859 | \n"," 0.872687 | \n"," 0.873397 | \n","
\n"," \n"," | 1650 | \n"," 0.198200 | \n"," 0.390281 | \n"," 0.873436 | \n"," 0.873419 | \n"," 0.873326 | \n"," 0.873591 | \n","
\n"," \n"," | 1700 | \n"," 0.183600 | \n"," 0.392936 | \n"," 0.873436 | \n"," 0.873193 | \n"," 0.873116 | \n"," 0.873577 | \n","
\n"," \n"," | 1750 | \n"," 0.211200 | \n"," 0.392684 | \n"," 0.874154 | \n"," 0.873830 | \n"," 0.873753 | \n"," 0.874303 | \n","
\n"," \n"," | 1800 | \n"," 0.193700 | \n"," 0.389910 | \n"," 0.873846 | \n"," 0.873913 | \n"," 0.874053 | \n"," 0.873958 | \n","
\n"," \n","
"]},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":["TrainOutput(global_step=1830, training_loss=0.3258447571530368, metrics={'train_runtime': 3796.5285, 'train_samples_per_second': 15.409, 'train_steps_per_second': 0.482, 'total_flos': 1.5392134937088e+16, 'train_loss': 0.3258447571530368, 'epoch': 3.0})"]},"metadata":{},"execution_count":19}]},{"cell_type":"code","source":["q=[trainer.evaluate(eval_dataset=df) for df in [train_dataloader, val_dataloader, test_dataset]]\n","\n","pd.DataFrame(q, index=[\"train\",\"val\",\"test\"]).iloc[:,:5]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":163},"id":"TM8323vQRtPS","executionInfo":{"status":"ok","timestamp":1721284215256,"user_tz":-420,"elapsed":271699,"user":{"displayName":"Le Le","userId":"02258782812217274557"}},"outputId":"5b1efaf5-9b28-4abe-f712-2b1082441e4a"},"execution_count":20,"outputs":[{"output_type":"display_data","data":{"text/plain":[""],"text/html":["\n"," \n"," \n","
\n"," [610/610 04:31]\n","
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\n"," \n"," \n"," | \n"," eval_loss | \n"," eval_Accuracy | \n"," eval_F1 | \n"," eval_Precision | \n"," eval_Recall | \n","
\n"," \n"," \n"," \n"," | train | \n"," 0.234579 | \n"," 0.920615 | \n"," 0.919718 | \n"," 0.920132 | \n"," 0.920377 | \n","
\n"," \n"," | val | \n"," 0.362135 | \n"," 0.870872 | \n"," 0.869292 | \n"," 0.870477 | \n"," 0.871104 | \n","
\n"," \n"," | test | \n"," 0.362268 | \n"," 0.868000 | \n"," 0.866591 | \n"," 0.867133 | \n"," 0.868500 | \n","
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\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtrainer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpush_to_hub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"railwayBK-sentiment-analysis\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/transformers/trainer.py\u001b[0m in \u001b[0;36mpush_to_hub\u001b[0;34m(self, commit_message, blocking, token, **kwargs)\u001b[0m\n\u001b[1;32m 4274\u001b[0m \u001b[0;31m# In case the user calls this method with args.push_to_hub = False\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4275\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhub_model_id\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4276\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minit_hf_repo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtoken\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtoken\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4277\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4278\u001b[0m \u001b[0;31m# Needs to be executed on all processes for TPU training, but will only save on the processed determined by\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/transformers/trainer.py\u001b[0m in \u001b[0;36minit_hf_repo\u001b[0;34m(self, token)\u001b[0m\n\u001b[1;32m 4098\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4099\u001b[0m \u001b[0mtoken\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtoken\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtoken\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhub_token\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4100\u001b[0;31m \u001b[0mrepo_url\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcreate_repo\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrepo_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtoken\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtoken\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprivate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhub_private_repo\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexist_ok\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 4101\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhub_model_id\u001b[0m \u001b[0;34m=\u001b[0m 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request information\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mHfHubHTTPError\u001b[0m: (Request ID: Root=1-6698bb96-16e8663d3d51591c5b511547;e22595ec-d9ac-4add-9ee5-622f11708499)\n\n403 Forbidden: You don't have the rights to create a model under the namespace \"vinh120203\".\nCannot access content at: https://huggingface.co./api/repos/create.\nIf you are trying to create or update content,make sure you have a token with the `write` role."]}]}]} |