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{
"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]"
]
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},
{
"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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"language": "python",
"name": "venv"
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
}
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