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--- |
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datasets: |
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- Open-Orca/OpenOrca |
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library_name: transformers |
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tags: |
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- llama |
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--- |
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# Basilisk 4B |
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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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Built on `winglian/llama-2-4b`, a 4B parameter Llama-2 model, this model is finetuned with open orca CoT data. |
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``` |
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hf-causal-experimental (pretrained=winglian/basilisk-4b,use_accelerate=True,trust_remote_code=True), limit: None, provide_description: False, num_fewshot: 0, batch_size: None |
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| Task |Version| Metric |Value | |Stderr| |
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|------------------------------------------------|------:|---------------------|-----:|---|-----:| |
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|agieval_aqua_rat | 0|acc |0.2362|_ |0.0267| |
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| | |acc_norm |0.2283|_ |0.0264| |
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|agieval_logiqa_en | 0|acc |0.2688|_ |0.0174| |
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| | |acc_norm |0.2811|_ |0.0176| |
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|agieval_lsat_ar | 0|acc |0.2130|_ |0.0271| |
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| | |acc_norm |0.1913|_ |0.0260| |
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|agieval_lsat_lr | 0|acc |0.2255|_ |0.0185| |
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| | |acc_norm |0.2745|_ |0.0198| |
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|agieval_lsat_rc | 0|acc |0.2305|_ |0.0257| |
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| | |acc_norm |0.2491|_ |0.0264| |
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|agieval_sat_en | 0|acc |0.3641|_ |0.0336| |
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| | |acc_norm |0.3495|_ |0.0333| |
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|agieval_sat_en_without_passage | 0|acc |0.2427|_ |0.0299| |
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| | |acc_norm |0.2427|_ |0.0299| |
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|agieval_sat_math | 0|acc |0.2318|_ |0.0285| |
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| | |acc_norm |0.2091|_ |0.0275| |
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|bigbench_causal_judgement | 0|multiple_choice_grade|0.5000|_ |0.0364| |
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|bigbench_date_understanding | 0|multiple_choice_grade|0.3930|_ |0.0255| |
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|bigbench_disambiguation_qa | 0|multiple_choice_grade|0.2674|_ |0.0276| |
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|bigbench_geometric_shapes | 0|multiple_choice_grade|0.1838|_ |0.0205| |
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| | |exact_str_match |0.0279|_ |0.0087| |
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|bigbench_logical_deduction_five_objects | 0|multiple_choice_grade|0.2380|_ |0.0191| |
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|bigbench_logical_deduction_seven_objects | 0|multiple_choice_grade|0.1843|_ |0.0147| |
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|bigbench_logical_deduction_three_objects | 0|multiple_choice_grade|0.3800|_ |0.0281| |
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|bigbench_movie_recommendation | 0|multiple_choice_grade|0.3480|_ |0.0213| |
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|bigbench_navigate | 0|multiple_choice_grade|0.5000|_ |0.0158| |
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|bigbench_reasoning_about_colored_objects | 0|multiple_choice_grade|0.3680|_ |0.0108| |
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|bigbench_ruin_names | 0|multiple_choice_grade|0.2746|_ |0.0211| |
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|bigbench_salient_translation_error_detection | 0|multiple_choice_grade|0.2806|_ |0.0142| |
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|bigbench_snarks | 0|multiple_choice_grade|0.4972|_ |0.0373| |
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|bigbench_sports_understanding | 0|multiple_choice_grade|0.4939|_ |0.0159| |
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|bigbench_temporal_sequences | 0|multiple_choice_grade|0.2740|_ |0.0141| |
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|bigbench_tracking_shuffled_objects_five_objects | 0|multiple_choice_grade|0.1904|_ |0.0111| |
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|bigbench_tracking_shuffled_objects_seven_objects| 0|multiple_choice_grade|0.1394|_ |0.0083| |
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|bigbench_tracking_shuffled_objects_three_objects| 0|multiple_choice_grade|0.3800|_ |0.0281| |
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hf-causal-experimental (pretrained=winglian/basilisk-4b,use_accelerate=True,trust_remote_code=True), limit: None, provide_description: False, num_fewshot: 0, batch_size: 12 |
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| Task |Version| Metric |Value | |Stderr| |
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|-------------|------:|--------|-----:|---|-----:| |
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|arc_challenge| 0|acc |0.3285|_ |0.0137| |
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| | |acc_norm|0.3532|_ |0.0140| |
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|arc_easy | 0|acc |0.6364|_ |0.0099| |
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| | |acc_norm|0.6035|_ |0.0100| |
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|boolq | 1|acc |0.7196|_ |0.0079| |
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|hellaswag | 0|acc |0.4239|_ |0.0049| |
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| | |acc_norm|0.5473|_ |0.0050| |
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|openbookqa | 0|acc |0.2220|_ |0.0186| |
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| | |acc_norm|0.3320|_ |0.0211| |
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|piqa | 0|acc |0.6937|_ |0.0108| |
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| | |acc_norm|0.6921|_ |0.0108| |
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|winogrande | 0|acc |0.5399|_ |0.0140| |
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``` |
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