Do deep learning NLP models for one model
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What you get with this Offer
My focus includes diverse NLP applications like sentiment analysis, text classification, and machine translation.
During training, I fine-tune models with labeled data, often relying on transfer learning with pre-trained models.
Frameworks like TensorFlow and PyTorch, as well as libraries like Hugging Face Transformers, are my go-to tools for model development and training. I assess model performance using task-specific evaluation metrics.
Get more with Offer Add-ons
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I can deploy the model
Additional 2 working days
+$40 -
I can deliver all work in 1 working day
+$25
What the Freelancer needs to start the work
Project Objectives:
Clear understanding of the specific NLP task or tasks to be addressed (e.g., sentiment analysis, text classification, named entity recognition).
Data:
Access to relevant and labeled training data. The size and quality of the dataset are crucial for effective model training.
Data Preprocessing Details:
Information about any specific preprocessing steps required for the dataset, such as tokenization, cleaning, or handling special cases.
Model Preferences:
Any specific preferences or requirements regarding the choice of deep learning models, architectures, or pre-trained models.
Evaluation Metrics:
Agreement on the metrics to be used for evaluating the performance of the NLP model.
Timeline and Budget:
Clear communication of project timelines and budget constraints to manage expectations effectively.
It's important for both parties to establish clear communication and expectations to ensure a successful collaboration.