llm-foundry
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Finetuning Models
I followed the tutorial at train/finetune_example/mpt-7b-arc-easy--gpu.yaml and added an additional evaluation using icl_tasks: 'eval/yamls/tasks_light.yaml' in order to evaluate accuracy on ARC Easy. As the model finetuned, training loss decreased, but so did accuracy, which appears to be a bug.
I repeated this using the full ARC Easy training set and the same thing occurred. Is there a reason that finetuning causes training loss to decrease but accuracy on evaluation to decrease?
When you used all of ARC easy, can you share what changes you made to the YAML?
Sure, I only changed:
data_dir: train/finetune_example/arc-easy/
In arc-easy I have a train.jsonl
I downloaded the data from: https://huggingface.co/datasets/ai2_arc