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Eval

The fine tuned model (DevQuasar/analytical_reasoning_r16a32_unsloth-Llama-3.2-3B-Instruct-bnb-4bit) has gained performace over the base model (unsloth/Llama-3.2-3B-Instruct-bnb-4bit) in the following tasks.

Test Base Model Fine-Tuned Model Performance Gain
leaderboard_bbh_logical_deduction_seven_objects 0.2520 0.4360 0.1840
leaderboard_bbh_logical_deduction_five_objects 0.3560 0.4560 0.1000
leaderboard_musr_team_allocation 0.2200 0.3200 0.1000
leaderboard_bbh_disambiguation_qa 0.3040 0.3760 0.0720
leaderboard_gpqa_diamond 0.2222 0.2727 0.0505
leaderboard_bbh_movie_recommendation 0.5960 0.6360 0.0400
leaderboard_bbh_formal_fallacies 0.5080 0.5400 0.0320
leaderboard_bbh_tracking_shuffled_objects_three_objects 0.3160 0.3440 0.0280
leaderboard_bbh_causal_judgement 0.5455 0.5668 0.0214
leaderboard_bbh_web_of_lies 0.4960 0.5160 0.0200
leaderboard_math_geometry_hard 0.0455 0.0606 0.0152
leaderboard_math_num_theory_hard 0.0519 0.0649 0.0130
leaderboard_musr_murder_mysteries 0.5280 0.5400 0.0120
leaderboard_gpqa_extended 0.2711 0.2802 0.0092
leaderboard_bbh_sports_understanding 0.5960 0.6040 0.0080
leaderboard_math_intermediate_algebra_hard 0.0107 0.0143 0.0036

Framework versions

  • unsloth 2024.11.5
  • trl 0.12.0

Training HW

  • V100

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Architecture
llama

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Evaluation results