Finetune Deepseek R1 LLM model using PEFT(Parameter Efficient Finetuning) Low-Rank Adaptation (LoRA) on your own dataset. Whether you're working on custom NLP tasks or looking to adapt Deepseek R1 for specific use cases, this tutorial will walk you through the entire process, from setting up your environment to training and evaluating the fine-tuned model.
Chapters :
00:00- Introduction
00:40 - How to use GPUs in Google Colab
01:50 - Installation of the dependencies
02:05 - Model Prediction without fine-tuning
06:45 - Finetune the Model using Lora
12:35 - Saving the fine-tuned Model
12:55 - Model Prediction with fine-tuning
15:40 - Finetuning with increased Epochs
🔍 What You'll Learn:
Preparing your custom dataset for fine-tuning
Setting up the environment and dependencies
Configuring LoRA for efficient fine-tuning
Training the Deepseek R1 model on your data
Evaluating and testing the fine-tuned model
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