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README.md
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A modified GPT-2 model with only 25 million non-embedding params that outbenches GPT-2(124m), Pythia-70m/160m, and Cerebras-111m, it has ScaledSinusoidal position embeddings, embedding layernorm, no biases, and was trained on only 8 billion tokens of the SlimPajama dataset at home on 2xA6000. (On the graphic it's mis-labeled as cramp-41m)
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| model | avg | arc | hellaswag | mmlu | truthfulqa |
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| --- | --- | --- | --- | --- | --- |
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| cramp-25m | 30.57 | 21.76 | 27.35 | 25.53 | 47.66 |
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| pythia 70m deduped | 30.25 | 21.08 | 27.17 | 25.26 | 47.51 |
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| pythia 70m | 30.46 | 21.59 | 27.29 | 25.9 | 47.06 |
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| pythia 160m deduped | 31.16 | 24.06 | 30.34 | 24.95 | 44.34 |
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| pythia 160m | 30.58 | 22.78 | 30.34 | 24.95 | 44.26 |
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6079949388160e14e4e2e499/NzTdlxtBDp4drBRZgJiXt.png)
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A modified GPT-2 model with only 25 million non-embedding params that outbenches GPT-2(124m), Pythia-70m/160m, and Cerebras-111m, it has ScaledSinusoidal position embeddings, embedding layernorm, no biases, and was trained on only 8 billion tokens of the SlimPajama dataset at home on 2xA6000. (On the graphic it's mis-labeled as cramp-41m)
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**OLD BENCHMARK**
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| model | avg | arc | hellaswag | mmlu | truthfulqa |
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| --- | --- | --- | --- | --- | --- |
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| cramp-25m | 30.57 | 21.76 | 27.35 | 25.53 | 47.66 |
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| pythia 70m deduped | 30.25 | 21.08 | 27.17 | 25.26 | 47.51 |
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| pythia 70m | 30.46 | 21.59 | 27.29 | 25.9 | 47.06 |
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| pythia 160m deduped | 31.16 | 24.06 | 30.34 | 24.95 | 44.34 |
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| pythia 160m | 30.58 | 22.78 | 30.34 | 24.95 | 44.26 |
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***NEW BENCHMARK**
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| Tasks |Version|Filter|n-shot| Metric |Value | |Stderr|
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|-------------|------:|------|-----:|--------|-----:|---|-----:|
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|arc_challenge| 1|none | 25|acc |0.1724|± |0.0110|
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| | |none | 25|acc_norm|0.2031|± |0.0118|
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|truthfulqa_mc2| 2|none | 0|acc |0.4767|± |0.0156|
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|hellaswag| 1|none | 10|acc |0.2687|± |0.0044|
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| | |none | 10|acc_norm|0.2773|± |0.0045|
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|winogrande| 1|none | 5|acc |0.5028|± |0.0141|
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*MMLU*
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| Tasks |Version|Filter|n-shot|Metric|Value | |Stderr|
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|-----------------------------------|------:|------|-----:|------|-----:|---|-----:|
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|world_religions | 0|none | 5|acc |0.1813|± |0.0295|
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|virology | 0|none | 5|acc |0.1928|± |0.0307|
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|us_foreign_policy | 0|none | 5|acc |0.2900|± |0.0456|
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|sociology | 0|none | 5|acc |0.2438|± |0.0304|
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|security_studies | 0|none | 5|acc |0.2367|± |0.0272|
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|public_relations | 0|none | 5|acc |0.2455|± |0.0412|
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|professional_psychology | 0|none | 5|acc |0.2271|± |0.0169|
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|professional_medicine | 0|none | 5|acc |0.4375|± |0.0301|
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|professional_law | 0|none | 5|acc |0.2490|± |0.0110|
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|professional_accounting | 0|none | 5|acc |0.2589|± |0.0261|
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|prehistory | 0|none | 5|acc |0.2963|± |0.0254|
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|philosophy | 0|none | 5|acc |0.2315|± |0.0240|
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|nutrition | 0|none | 5|acc |0.2222|± |0.0238|
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|moral_scenarios | 0|none | 5|acc |0.2313|± |0.0141|
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|moral_disputes | 0|none | 5|acc |0.2168|± |0.0222|
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|miscellaneous | 0|none | 5|acc |0.2708|± |0.0159|
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|medical_genetics | 0|none | 5|acc |0.3000|± |0.0461|
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|marketing | 0|none | 5|acc |0.1923|± |0.0258|
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|management | 0|none | 5|acc |0.1942|± |0.0392|
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|machine_learning | 0|none | 5|acc |0.2054|± |0.0383|
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|logical_fallacies | 0|none | 5|acc |0.2393|± |0.0335|
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|jurisprudence | 0|none | 5|acc |0.2130|± |0.0396|
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|international_law | 0|none | 5|acc |0.2562|± |0.0398|
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|human_sexuality | 0|none | 5|acc |0.2366|± |0.0373|
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|human_aging | 0|none | 5|acc |0.2063|± |0.0272|
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|high_school_world_history | 0|none | 5|acc |0.2700|± |0.0289|
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|high_school_us_history | 0|none | 5|acc |0.2206|± |0.0291|
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|high_school_statistics | 0|none | 5|acc |0.4722|± |0.0340|
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|high_school_psychology | 0|none | 5|acc |0.2257|± |0.0179|
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|high_school_physics | 0|none | 5|acc |0.2384|± |0.0348|
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|high_school_microeconomics | 0|none | 5|acc |0.3403|± |0.0308|
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|high_school_mathematics | 0|none | 5|acc |0.2630|± |0.0268|
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|high_school_macroeconomics | 0|none | 5|acc |0.2051|± |0.0205|
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|high_school_government_and_politics| 0|none | 5|acc |0.2280|± |0.0303|
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|high_school_geography | 0|none | 5|acc |0.3535|± |0.0341|
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|high_school_european_history | 0|none | 5|acc |0.2909|± |0.0355|
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|high_school_computer_science | 0|none | 5|acc |0.2400|± |0.0429|
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|high_school_chemistry | 0|none | 5|acc |0.2759|± |0.0314|
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|high_school_biology | 0|none | 5|acc |0.3161|± |0.0265|
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|global_facts | 0|none | 5|acc |0.2000|± |0.0402|
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|formal_logic | 0|none | 5|acc |0.1825|± |0.0346|
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|elementary_mathematics | 0|none | 5|acc |0.2566|± |0.0225|
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|electrical_engineering | 0|none | 5|acc |0.2414|± |0.0357|
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|econometrics | 0|none | 5|acc |0.2544|± |0.0410|
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|conceptual_physics | 0|none | 5|acc |0.2809|± |0.0294|
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|computer_security | 0|none | 5|acc |0.2000|± |0.0402|
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|college_physics | 0|none | 5|acc |0.3431|± |0.0472|
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|college_medicine | 0|none | 5|acc |0.2197|± |0.0316|
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|college_mathematics | 0|none | 5|acc |0.3100|± |0.0465|
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|college_computer_science | 0|none | 5|acc |0.3100|± |0.0465|
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|college_chemistry | 0|none | 5|acc |0.3400|± |0.0476|
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|college_biology | 0|none | 5|acc |0.2083|± |0.0340|
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|clinical_knowledge | 0|none | 5|acc |0.2189|± |0.0254|
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|business_ethics | 0|none | 5|acc |0.2000|± |0.0402|
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|astronomy | 0|none | 5|acc |0.2237|± |0.0339|
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|anatomy | 0|none | 5|acc |0.3333|± |0.0407|
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|abstract_algebra | 0|none | 5|acc |0.2200|± |0.0416|
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6079949388160e14e4e2e499/NzTdlxtBDp4drBRZgJiXt.png)
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