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  LORA adapters of `meta-llama/Meta-Llama-3.1-8B-Instruct`, trained on 100 context samples from the HotpotQA dataset using the RAFT method, enable the model to better reason through the context and return more accurate outcomes.
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  ### Evaluation
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- Evaluated on 1k samples of validation set of HotpotQA.
 
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  | type | exatch_match| f1 | precision | recall |
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  |--------------|-------------|------------|---------------|---------|
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- | pretrained | 0.33 | 0.4195 | 0.4391 | 0.4931 |
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- | finetuned | 0.359 | **0.4821** | 0.4897 | 0.5281 |
 
 
 
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  LORA adapters of `meta-llama/Meta-Llama-3.1-8B-Instruct`, trained on 100 context samples from the HotpotQA dataset using the RAFT method, enable the model to better reason through the context and return more accurate outcomes.
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  ### Evaluation
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+
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+ Evaluated on FULL validation set of HotpotQA.
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  | type | exatch_match| f1 | precision | recall |
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  |--------------|-------------|------------|---------------|---------|
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+ | pretrained | 0.2980 | 0.3979 | 0.4116 | 0.5263 |
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+ | finetuned | 0.3606 | **0.4857** | 0.4989 | 0.5318 |
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+
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+ Finetuned version increases **22% on F1 and 15% on average**