You will get Finetuned BERT based Pre-Trained Model
Project details
Unlock the full potential of transformer-based NLP with a custom fine-tuned BERT text classification model tailored to your dataset and business objectives. Whether you need sentiment analysis, spam detection, intent recognition, topic classification, emotion detection, fake news detection, or any other custom NLP task.
My workflow includes dataset preprocessing, tokenization, label encoding, fine-tuning pretrained BERT models, hyperparameter optimization, model evaluation (Accuracy, Precision, Recall, F1-score, ROC-AUC), error analysis, and inference pipeline development. I also provide reproducible training scripts, well-documented code, and model checkpoints.
I can work with multilingual datasets, imbalanced classes, domain-specific corpora, and large-scale text collections. Whether you're building an AI-powered product, automating document classification, or improving customer support analytics, I ensure a scalable, production-ready solution with clear documentation and post-delivery support.
Technologies: Python, Hugging Face Transformers, BERT, RoBERTa, DistilBERT, PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, Weights & Biases, MLflow, Docker, FastAPI, and ONNX.
My workflow includes dataset preprocessing, tokenization, label encoding, fine-tuning pretrained BERT models, hyperparameter optimization, model evaluation (Accuracy, Precision, Recall, F1-score, ROC-AUC), error analysis, and inference pipeline development. I also provide reproducible training scripts, well-documented code, and model checkpoints.
I can work with multilingual datasets, imbalanced classes, domain-specific corpora, and large-scale text collections. Whether you're building an AI-powered product, automating document classification, or improving customer support analytics, I ensure a scalable, production-ready solution with clear documentation and post-delivery support.
Technologies: Python, Hugging Face Transformers, BERT, RoBERTa, DistilBERT, PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, Weights & Biases, MLflow, Docker, FastAPI, and ONNX.
Machine Learning Tools
NLTK, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, XGBoostWhat's included $100
These options are included with the project scope.
$100
- Delivery Time 3 days
- Number of Revisions Unlimited
- Number of Model Variations 3
- Number of Scenarios 4
- Number of Graphs/Charts 5
- Model Validation/Testing
- Model Documentation
- Source Code
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Chris D.
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Fast turnaround, followed the instructions, was diligent and made a big effort to meet my expectations. Thanks Juniard for your work!
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Dexter C.
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Dexter C.
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Bliss Tamar L.
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Junaid did really good job. He is scrupulous. Besides he is very responsive and good at cooperating. I will ask him help in my projects in the future as well.
About Junaid
NLP, Sentiment and Text Analyst
Larkana, Pakistan - 2:13 am local time
My core expertise includes:
Web scraping and data collection pipelines
Handling and wrangling text data
Feature extraction
Sentiment analysis
Topic modeling
Text classification
Named Entity Recognition (NER)
Social media and customer feedback analysis
Training and Fine tunning Machine Learning and Deep Learning
Transformer-based models (BERT, RoBERTa, DistilBERT)
Fine-tuning models on Hugging Face
Classification, prediction, and recommendation systems
I combine strong academic research expertise using NLP method which can aid value to industry. So, whether you need NLP pipelines, model fine-tuning, sentiment analysis and feature extraction, I can help turn your data into meaningful business value.
Tools & Technologies: Python, TensorFlow, PyTorch, Hugging Face, Scikit-learn, Pandas, NumPy, NLP Libraries, and Data Visualization.
Let's collaborate to build intelligent, transparent, and impactful AI solutions.
Steps for completing your project
After purchasing the project, send requirements so Junaid can start the project.
Delivery time starts when Junaid receives requirements from you.
Junaid works on your project following the steps below.
Revisions may occur after the delivery date.
Classifcation Probelm
The specific classification problem needed to be defined
Training Dataset
Whether client has their own data or needed to be obtained from other source