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Browse files- README.md +146 -1
- scripts/TRAIN.md +4 -2
README.md
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![logo](./misc/logo.png)
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[loss, val_loss](https://api.wandb.ai/links/mtasic85/ecf4l9qp)
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[val_ppl](https://api.wandb.ai/links/mtasic85/qsn8mz13)
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[learning_rate](https://api.wandb.ai/links/mtasic85/7kyopu4t)
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## lm-evaluation-harness
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![logo](./misc/logo.png)
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A pretrained language model based on the Llama model with about **109M** parameters. This model has been trained on **9.7B** (`9,782,206,713`) tokens from more than **5.2M** (`5,285,575`) dataset rows.
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This model **isn't** designed for immediate use but rather for Continued Pretraining and Finetuning on a downstream task. While it can handle a context length of up to **32K** (`32,768`) tokens, it was pretrained with sequences of **2K** (`2048`) tokens.
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The objective is to streamline the cognitive or reasoning core, eliminating any redundant knowledge from the model.
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[loss, val_loss](https://api.wandb.ai/links/mtasic85/ecf4l9qp)
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[val_ppl](https://api.wandb.ai/links/mtasic85/qsn8mz13)
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[learning_rate](https://api.wandb.ai/links/mtasic85/7kyopu4t)
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## lm-evaluation-harness
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```bash
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litgpt evaluate --tasks 'leaderboard' --out_dir 'evaluate-0/' --batch_size 4 --dtype 'bfloat16' out/pretrain/final/
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```
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| Tasks |Version|Filter|n-shot| Metric | |Value | |Stderr|
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|-----------------------------------------------------------|-------|------|-----:|-----------------------|---|-----:|---|------|
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|leaderboard | N/A| | | | | | | |
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| - leaderboard_bbh | N/A| | | | | | | |
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| - leaderboard_bbh_boolean_expressions | 1|none | 3|acc_norm |↑ |0.5680|± |0.0314|
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| - leaderboard_bbh_causal_judgement | 1|none | 3|acc_norm |↑ |0.5294|± |0.0366|
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| - leaderboard_bbh_date_understanding | 1|none | 3|acc_norm |↑ |0.1880|± |0.0248|
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| - leaderboard_bbh_disambiguation_qa | 1|none | 3|acc_norm |↑ |0.3240|± |0.0297|
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| - leaderboard_bbh_formal_fallacies | 1|none | 3|acc_norm |↑ |0.4720|± |0.0316|
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| - leaderboard_bbh_geometric_shapes | 1|none | 3|acc_norm |↑ |0.0280|± |0.0105|
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| - leaderboard_bbh_hyperbaton | 1|none | 3|acc_norm |↑ |0.5160|± |0.0317|
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| - leaderboard_bbh_logical_deduction_five_objects | 1|none | 3|acc_norm |↑ |0.1760|± |0.0241|
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| - leaderboard_bbh_logical_deduction_seven_objects | 1|none | 3|acc_norm |↑ |0.1360|± |0.0217|
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| - leaderboard_bbh_logical_deduction_three_objects | 1|none | 3|acc_norm |↑ |0.3480|± |0.0302|
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| - leaderboard_bbh_movie_recommendation | 1|none | 3|acc_norm |↑ |0.2280|± |0.0266|
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| - leaderboard_bbh_navigate | 1|none | 3|acc_norm |↑ |0.4800|± |0.0317|
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| - leaderboard_bbh_object_counting | 1|none | 3|acc_norm |↑ |0.0640|± |0.0155|
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| - leaderboard_bbh_penguins_in_a_table | 1|none | 3|acc_norm |↑ |0.2329|± |0.0351|
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| - leaderboard_bbh_reasoning_about_colored_objects | 1|none | 3|acc_norm |↑ |0.1240|± |0.0209|
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| - leaderboard_bbh_ruin_names | 1|none | 3|acc_norm |↑ |0.2400|± |0.0271|
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| - leaderboard_bbh_salient_translation_error_detection | 1|none | 3|acc_norm |↑ |0.1560|± |0.0230|
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| - leaderboard_bbh_snarks | 1|none | 3|acc_norm |↑ |0.4607|± |0.0375|
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| - leaderboard_bbh_sports_understanding | 1|none | 3|acc_norm |↑ |0.4560|± |0.0316|
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| - leaderboard_bbh_temporal_sequences | 1|none | 3|acc_norm |↑ |0.2320|± |0.0268|
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| - leaderboard_bbh_tracking_shuffled_objects_five_objects | 1|none | 3|acc_norm |↑ |0.2000|± |0.0253|
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| - leaderboard_bbh_tracking_shuffled_objects_seven_objects| 1|none | 3|acc_norm |↑ |0.1520|± |0.0228|
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| - leaderboard_bbh_tracking_shuffled_objects_three_objects| 1|none | 3|acc_norm |↑ |0.3160|± |0.0295|
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| - leaderboard_bbh_web_of_lies | 1|none | 3|acc_norm |↑ |0.5040|± |0.0317|
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| - leaderboard_gpqa | N/A| | | | | | | |
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| - leaderboard_gpqa_diamond | 1|none | 0|acc_norm |↑ |0.1919|± |0.0281|
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| - leaderboard_gpqa_extended | 1|none | 0|acc_norm |↑ |0.2747|± |0.0191|
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| - leaderboard_gpqa_main | 1|none | 0|acc_norm |↑ |0.2589|± |0.0207|
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| - leaderboard_ifeval | 3|none | 0|inst_level_loose_acc |↑ |0.2002|± | N/A|
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| | |none | 0|inst_level_strict_acc |↑ |0.1871|± | N/A|
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| | |none | 0|prompt_level_loose_acc |↑ |0.1072|± |0.0133|
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| | |none | 0|prompt_level_strict_acc|↑ |0.0998|± |0.0129|
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| - leaderboard_math_hard | N/A| | | | | | | |
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| - leaderboard_math_algebra_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
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| - leaderboard_math_counting_and_prob_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
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| - leaderboard_math_geometry_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
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| - leaderboard_math_intermediate_algebra_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
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| - leaderboard_math_num_theory_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
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| - leaderboard_math_prealgebra_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
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| - leaderboard_math_precalculus_hard | 1|none | 4|exact_match |↑ |0.0000|± | 0|
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| - leaderboard_mmlu_pro | 0.1|none | 5|acc |↑ |0.1096|± |0.0028|
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| - leaderboard_musr | N/A| | | | | | | |
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| - leaderboard_musr_murder_mysteries | 1|none | 0|acc_norm |↑ |0.4800|± |0.0317|
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| - leaderboard_musr_object_placements | 1|none | 0|acc_norm |↑ |0.2930|± |0.0285|
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| - leaderboard_musr_team_allocation | 1|none | 0|acc_norm |↑ |0.3360|± |0.0299|
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```bash
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litgpt evaluate --tasks 'hellaswag,gsm8k,truthfulqa_mc2,mmlu,winogrande,arc_challenge' --out_dir 'evaluate-1/' --batch_size 4 --dtype 'bfloat16' out/pretrain/final/
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```
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Tasks |Version| Filter |n-shot| Metric | |Value | |Stderr|
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|arc_challenge | 1|none | 0|acc |↑ |0.2082|± |0.0119|
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| | |none | 0|acc_norm |↑ |0.2474|± |0.0126|
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|gsm8k | 3|flexible-extract| 5|exact_match|↑ |0.0106|± |0.0028|
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| | |strict-match | 5|exact_match|↑ |0.0008|± |0.0008|
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|hellaswag | 1|none | 0|acc |↑ |0.2766|± |0.0045|
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| | |none | 0|acc_norm |↑ |0.2926|± |0.0045|
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|mmlu | 2|none | |acc |↑ |0.2349|± |0.0036|
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| - humanities | 2|none | |acc |↑ |0.2461|± |0.0063|
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| - formal_logic | 1|none | 0|acc |↑ |0.2698|± |0.0397|
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| - high_school_european_history | 1|none | 0|acc |↑ |0.2000|± |0.0312|
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| - high_school_us_history | 1|none | 0|acc |↑ |0.2549|± |0.0306|
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| - high_school_world_history | 1|none | 0|acc |↑ |0.2616|± |0.0286|
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| - international_law | 1|none | 0|acc |↑ |0.2479|± |0.0394|
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| - jurisprudence | 1|none | 0|acc |↑ |0.2593|± |0.0424|
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| - logical_fallacies | 1|none | 0|acc |↑ |0.2638|± |0.0346|
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| - moral_disputes | 1|none | 0|acc |↑ |0.2457|± |0.0232|
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| - moral_scenarios | 1|none | 0|acc |↑ |0.2458|± |0.0144|
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| - philosophy | 1|none | 0|acc |↑ |0.1833|± |0.0220|
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| - prehistory | 1|none | 0|acc |↑ |0.2315|± |0.0235|
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| - professional_law | 1|none | 0|acc |↑ |0.2503|± |0.0111|
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| - world_religions | 1|none | 0|acc |↑ |0.3216|± |0.0358|
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| - other | 2|none | |acc |↑ |0.2391|± |0.0076|
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| - business_ethics | 1|none | 0|acc |↑ |0.2900|± |0.0456|
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| - clinical_knowledge | 1|none | 0|acc |↑ |0.2377|± |0.0262|
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| - college_medicine | 1|none | 0|acc |↑ |0.2197|± |0.0316|
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| - global_facts | 1|none | 0|acc |↑ |0.2100|± |0.0409|
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| - human_aging | 1|none | 0|acc |↑ |0.2960|± |0.0306|
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| - management | 1|none | 0|acc |↑ |0.1748|± |0.0376|
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| - marketing | 1|none | 0|acc |↑ |0.2949|± |0.0299|
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| - medical_genetics | 1|none | 0|acc |↑ |0.2700|± |0.0446|
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| - miscellaneous | 1|none | 0|acc |↑ |0.2222|± |0.0149|
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| - nutrition | 1|none | 0|acc |↑ |0.2092|± |0.0233|
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| - professional_accounting | 1|none | 0|acc |↑ |0.2518|± |0.0259|
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| - professional_medicine | 1|none | 0|acc |↑ |0.1949|± |0.0241|
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| - virology | 1|none | 0|acc |↑ |0.3012|± |0.0357|
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| - social sciences | 2|none | |acc |↑ |0.2246|± |0.0075|
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| - econometrics | 1|none | 0|acc |↑ |0.2807|± |0.0423|
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| - high_school_geography | 1|none | 0|acc |↑ |0.1818|± |0.0275|
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| - high_school_government_and_politics| 1|none | 0|acc |↑ |0.2176|± |0.0298|
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| - high_school_macroeconomics | 1|none | 0|acc |↑ |0.2179|± |0.0209|
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| - high_school_microeconomics | 1|none | 0|acc |↑ |0.2101|± |0.0265|
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| - high_school_psychology | 1|none | 0|acc |↑ |0.2000|± |0.0171|
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| - human_sexuality | 1|none | 0|acc |↑ |0.2519|± |0.0381|
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| - professional_psychology | 1|none | 0|acc |↑ |0.2516|± |0.0176|
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| - public_relations | 1|none | 0|acc |↑ |0.2182|± |0.0396|
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| - security_studies | 1|none | 0|acc |↑ |0.1959|± |0.0254|
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| - sociology | 1|none | 0|acc |↑ |0.2488|± |0.0306|
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| - us_foreign_policy | 1|none | 0|acc |↑ |0.2800|± |0.0451|
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| - stem | 2|none | |acc |↑ |0.2239|± |0.0074|
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| - abstract_algebra | 1|none | 0|acc |↑ |0.1800|± |0.0386|
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| - anatomy | 1|none | 0|acc |↑ |0.1778|± |0.0330|
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| - astronomy | 1|none | 0|acc |↑ |0.1974|± |0.0324|
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| - college_biology | 1|none | 0|acc |↑ |0.2569|± |0.0365|
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| - college_chemistry | 1|none | 0|acc |↑ |0.2400|± |0.0429|
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| - college_computer_science | 1|none | 0|acc |↑ |0.2400|± |0.0429|
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| - college_mathematics | 1|none | 0|acc |↑ |0.2400|± |0.0429|
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| - college_physics | 1|none | 0|acc |↑ |0.2255|± |0.0416|
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| - computer_security | 1|none | 0|acc |↑ |0.2700|± |0.0446|
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| - conceptual_physics | 1|none | 0|acc |↑ |0.2468|± |0.0282|
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| - electrical_engineering | 1|none | 0|acc |↑ |0.2552|± |0.0363|
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| - elementary_mathematics | 1|none | 0|acc |↑ |0.2407|± |0.0220|
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| - high_school_biology | 1|none | 0|acc |↑ |0.1710|± |0.0214|
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| - high_school_chemistry | 1|none | 0|acc |↑ |0.1724|± |0.0266|
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| - high_school_computer_science | 1|none | 0|acc |↑ |0.2600|± |0.0441|
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| - high_school_mathematics | 1|none | 0|acc |↑ |0.2519|± |0.0265|
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| - high_school_physics | 1|none | 0|acc |↑ |0.1457|± |0.0288|
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| - high_school_statistics | 1|none | 0|acc |↑ |0.2083|± |0.0277|
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| - machine_learning | 1|none | 0|acc |↑ |0.3571|± |0.0455|
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|truthfulqa_mc2 | 2|none | 0|acc |↑ |0.4506|± |0.0161|
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|winogrande | 1|none | 0|acc |↑ |0.5288|± |0.0140|
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| Groups |Version|Filter|n-shot|Metric| |Value | |Stderr|
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|------------------|------:|------|------|------|---|-----:|---|-----:|
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|mmlu | 2|none | |acc |↑ |0.2349|± |0.0036|
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| - humanities | 2|none | |acc |↑ |0.2461|± |0.0063|
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| - other | 2|none | |acc |↑ |0.2391|± |0.0076|
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| - social sciences| 2|none | |acc |↑ |0.2246|± |0.0075|
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| - stem | 2|none | |acc |↑ |0.2239|± |0.0074|
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scripts/TRAIN.md
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## Evaluate
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```bash
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litgpt evaluate --tasks 'hellaswag,gsm8k,truthfulqa_mc2,mmlu,
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```
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## Evaluate
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```bash
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litgpt evaluate --tasks 'leaderboard' --out_dir 'evaluate-0/' --batch_size 4 --dtype 'bfloat16' out/pretrain/final/
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litgpt evaluate --tasks 'hellaswag,gsm8k,truthfulqa_mc2,mmlu,winogrande,arc_challenge' --out_dir 'evaluate-1/' --batch_size 4 --dtype 'bfloat16' out/pretrain/final/
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litgpt evaluate --tasks 'mmlu_pro,ifeval,mgsm_direct,mathqa,gpqa' --out_dir 'evaluate-2/' --batch_size 4 --dtype 'bfloat16' out/pretrain/final/
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```
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