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mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.12.hook_mlp_out.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 576, "1": 83, "2": 0, "3": 0}, "net_accuracy": 0.21416964575885603}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.13.hook_mlp_out.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 516, "1": 8, "2": 161, "3": 0}, "net_accuracy": 0.22261943451413715}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.13.hook_resid_post.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 0, "1": 691, "2": 0, "3": 37}, "net_accuracy": 0.2365940851478713}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.16.hook_mlp_out.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 530, "1": 2, "2": 46, "3": 163}, "net_accuracy": 0.24081897952551187}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.16.hook_resid_post.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 0, "1": 26, "2": 0, "3": 934}, "net_accuracy": 0.31199220019499513}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.17.hook_mlp_out.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 34, "1": 0, "2": 686, "3": 12}, "net_accuracy": 0.2378940526486838}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.19.hook_resid_post.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 0, "1": 251, "2": 28, "3": 619}, "net_accuracy": 0.2918427039324017}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.2.hook_mlp_out.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 0, "1": 14, "2": 707, "3": 7}, "net_accuracy": 0.2365940851478713}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.2.hook_resid_post.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 0, "1": 0, "2": 82, "3": 833}, "net_accuracy": 0.2973675658108547}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.21.hook_resid_post.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 0, "1": 99, "2": 522, "3": 152}, "net_accuracy": 0.2512187195320117}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.22.hook_mlp_out.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 668, "1": 0, "2": 0, "3": 0}, "net_accuracy": 0.2170945726356841}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.23.hook_mlp_out.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 660, "1": 0, "2": 0, "3": 13}, "net_accuracy": 0.21871953201169972}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.3.hook_mlp_out.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 326, "1": 0, "2": 0, "3": 445}, "net_accuracy": 0.25056873578160543}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.6.hook_mlp_out.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 4, "1": 718, "2": 0, "3": 0}, "net_accuracy": 0.2346441338966526}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.6.hook_resid_post.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 0, "1": 3, "2": 0, "3": 955}, "net_accuracy": 0.31134221644458887}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.7.hook_mlp_out.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 665, "1": 0, "2": 0, "3": 0}, "net_accuracy": 0.21611959701007474}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.7.hook_resid_post.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 0, "1": 250, "2": 0, "3": 696}, "net_accuracy": 0.30744231394215144}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_blocks.8.hook_resid_post.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 0, "1": 0, "2": 0, "3": 956}, "net_accuracy": 0.31069223269418267}

mmlu_social_sciences/few_shot_0/EleutherAI_gpt-neo-1.3B/last_token_relative_depth_100/accuracy_ln_final.hook_normalized.json

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+{"total_per_class": {"0": 668, "1": 721, "2": 732, "3": 956}, "correct_per_class": {"0": 187, "1": 119, "2": 131, "3": 392}, "net_accuracy": 0.2694182645433864}