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Feat/intragen experiments (#414)
* added curriculum * readapted readme * corrected small errors * Delete eval/eval/r1/algorithmic/word_sorting.json * removed redundant argument * added spell * removed duplicated fit * changed config * added composite changes * added composite changes * updated yaml * added spell backward * updated read me * added qwen2.5 * added * Add files via upload * updated missing trainer func * updated curr * updated spell back * updated correctness score func * updated configs * added local evals * added updates * updated datasets * added fsdp to hf utility * added algorithmic qwen 3b yaml * updated read me * updated configs * added preappend token * updated with thinking token * updated test score board * resolved comments * added evaluation scripts * removed results from pr * added config * added partial reward scoring * added evaluation composites * added training configs * added games eval * added rubriks cube * resolved merge cinflicts * added games config * added latest eval configs * updated strucutre * Delete training/evaluations/eval_graphs_composite.yaml --------- Co-authored-by: joesharratt1229 <joesharrat1229@gmail.com>
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@ -55,9 +55,9 @@ def test_rubikscube_items():
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assert dataset.score_answer(answer=None, entry=item) == 0.0
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if item["metadata"]["example_correct_answer"] != "R":
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assert dataset.score_answer(answer="R", entry=item) == 0.05
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assert dataset.score_answer(answer="R", entry=item) == 0.01
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assert dataset.score_answer(answer="R2 R3 R4 R5 R'2 R'3", entry=item) == 0.05
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assert dataset.score_answer(answer="R2 R3 R4 R5 R'2 R'3", entry=item) == 0.01
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if len(item["metadata"]["example_correct_answer"]) > 0:
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assert dataset.score_answer(answer="", entry=item) == 0.01
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