{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6826a9ff-3dbb-42f1-b5ea-b2cd0cbabf44",
   "metadata": {},
   "outputs": [],
   "source": [
    "from transformers import (\n",
    "    AutoConfig,\n",
    "    AutoModelForSequenceClassification,\n",
    "    AutoTokenizer,\n",
    "    DataCollatorWithPadding,\n",
    "    EvalPrediction,\n",
    "    HfArgumentParser,\n",
    "    Trainer,\n",
    "    TrainingArguments,\n",
    "    default_data_collator,\n",
    "    set_seed,\n",
    ")\n",
    "import json\n",
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "477afce3-a672-4154-b5f4-b5cee162a6f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = AutoModelForSequenceClassification.from_pretrained(\"sentiment-malay-deberta/checkpoint-88000\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d3d5a606-859e-4b26-a892-937296299ca8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[{'label': 'negative', 'score': 0.6645314693450928}, {'label': 'negative', 'score': 0.9972461462020874}, {'label': 'positive', 'score': 0.9917457699775696}, {'label': 'positive', 'score': 0.9973276853561401}, {'label': 'negative', 'score': 0.9989587068557739}, {'label': 'negative', 'score': 0.9864065051078796}]\n"
     ]
    }
   ],
   "source": [
    "from transformers import pipeline\n",
    "sentiment_analysis = pipeline(\"sentiment-analysis\",model=\"sentiment-malay-deberta/checkpoint-88000\")\n",
    "print(sentiment_analysis([\"teloq hang\",\"tak prihatin fikir kita ni apa\",\"bossku\",\"macam la dia tu hebat\",\"eh salah\",\"belagak pandai\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d8069cbf-8e5b-43a0-83b1-b00bf00e8526",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = []\n",
    "\n",
    "with open('combined-data-sentiment.jsonl') as f:\n",
    "    for x in f:\n",
    "        result = json.loads(x)\n",
    "        if result['split'] != 'train':\n",
    "            data.append(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "bcdce6cf-34ab-4bdc-a317-48f1d9c187cf",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████████████████████| 10857/10857 [15:37<00:00, 11.58it/s]\n"
     ]
    }
   ],
   "source": [
    "batch_size = 3\n",
    "predicted_labels = []\n",
    "for i in tqdm(range(0, len(data), batch_size)):\n",
    "    batch = data[i:i + batch_size]\n",
    "    batch_predictions = sentiment_analysis([x['text'] for x in batch])\n",
    "\n",
    "    for predictions in batch_predictions:\n",
    "        max_score_label = predictions['label']\n",
    "\n",
    "        predicted_labels.append(max_score_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "0ee8f722-4e53-4245-b27a-59224be2edf1",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/aisyah/.local/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1471: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "    negative    0.94533   0.97434   0.95962     20108\n",
      "     neutral    0.00000   0.00000   0.00000       699\n",
      "    positive    0.92857   0.93505   0.93180     11762\n",
      "\n",
      "    accuracy                        0.93924     32569\n",
      "   macro avg    0.62463   0.63646   0.63047     32569\n",
      "weighted avg    0.91899   0.93924   0.92897     32569\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/aisyah/.local/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1471: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/home/aisyah/.local/lib/python3.8/site-packages/sklearn/metrics/_classification.py:1471: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "\n",
    "print(classification_report([x['sentiment'] for x in data],predicted_labels, digits = 5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "59487536-1153-4ba7-80fc-e46a8080bfd8",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/aisyah/.local/lib/python3.8/site-packages/transformers/utils/hub.py:671: UserWarning: The `organization` argument is deprecated and will be removed in v5 of Transformers. Set your organization directly in the `repo_id` passed instead (`repo_id={organization}/{model_id}`).\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5d8b05ef5fd444df96cb959d9829509b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "model.safetensors:   0%|          | 0.00/283M [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "CommitInfo(commit_url='https://huggingface.co/malaysia-ai/deberta-v3-xsmall-malay-sentiment/commit/544700f30bbb273144933f93417cd87cad9b4c94', commit_message='Upload DebertaV2ForSequenceClassification', commit_description='', oid='544700f30bbb273144933f93417cd87cad9b4c94', pr_url=None, pr_revision=None, pr_num=None)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.push_to_hub('deberta-v3-xsmall-malay-sentiment', organization='malaysia-ai', safe_serialization=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "81de36e9-5e7e-4583-9c30-d835f7985858",
   "metadata": {},
   "outputs": [],
   "source": [
    "tokenizer = AutoTokenizer.from_pretrained(\"sentiment-malay-deberta/checkpoint-88000\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2ed2f170-8a46-47dd-9064-6cc0f2322230",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0ff3af039e6d43ce8e3b3d164bc0991d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "spm.model:   0%|          | 0.00/2.46M [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "CommitInfo(commit_url='https://huggingface.co/malaysia-ai/deberta-v3-xsmall-malay-sentiment/commit/3ecb0599c10fb975720251091ff9b3ef2eced5b7', commit_message='Upload tokenizer', commit_description='', oid='3ecb0599c10fb975720251091ff9b3ef2eced5b7', pr_url=None, pr_revision=None, pr_num=None)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokenizer.push_to_hub('deberta-v3-xsmall-malay-sentiment', organization='malaysia-ai', safe_serialization=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a5c3a962-d1d2-40cc-b5b8-7c8d016dcc7d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a9fec7de33ce48a2be756da4cfd46a97",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "combined-data-sentiment.jsonl:   0%|          | 0.00/652M [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "CommitInfo(commit_url='https://huggingface.co/datasets/aisyahhrazak/combined-malay-sentiment/commit/9ab06163578a4743a657f66d3b39a38e014d8c4d', commit_message='Upload README.md with huggingface_hub', commit_description='', oid='9ab06163578a4743a657f66d3b39a38e014d8c4d', pr_url=None, pr_revision=None, pr_num=None)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from huggingface_hub import HfApi\n",
    "api = HfApi()\n",
    "api.upload_file(\n",
    "    path_or_fileobj=\"combined-data-sentiment.jsonl\",\n",
    "    path_in_repo=\"README.md\",\n",
    "    repo_id=\"aisyahhrazak/combined-malay-sentiment\",\n",
    "    repo_type=\"dataset\",\n",
    ")"
   ]
  }
 ],
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