Great explanation and a very advanced web service-well thought out and executed! From your previous video, I learned that fine-tuning is more like shaping intuition, since the model operates on statistical patterns and isn't really "learning" in the human sense. With that in mind, I have a question about the capabilities of fine-tuning: Can it be used to impart factual knowledge? For example, if I input data from a medical textbook, could the model be trained to make medical diagnoses in a way that approximates learning? (I used chatgpt to make this comment more clear ;) )
It's very hard to impart factual knowledge through fine-tuning. However, theoretically it's possible. You would need a larger corpus of text, and a better way to approach it might be "continued pre-training" - ideally before instruction-tuning is done to make the model conversational. To be honest, I haven't been able to experiment much in this area, so I can't say definitively. So take this answer with a grain of salt!
Can you make a video about tuning validation? How to reliably test that tuning gives us the results we're looking for?
Will do
Great explanation and a very advanced web service-well thought out and executed! From your previous video, I learned that fine-tuning is more like shaping intuition, since the model operates on statistical patterns and isn't really "learning" in the human sense. With that in mind, I have a question about the capabilities of fine-tuning: Can it be used to impart factual knowledge? For example, if I input data from a medical textbook, could the model be trained to make medical diagnoses in a way that approximates learning? (I used chatgpt to make this comment more clear ;) )
It's very hard to impart factual knowledge through fine-tuning. However, theoretically it's possible. You would need a larger corpus of text, and a better way to approach it might be "continued pre-training" - ideally before instruction-tuning is done to make the model conversational. To be honest, I haven't been able to experiment much in this area, so I can't say definitively. So take this answer with a grain of salt!
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