--- datasets: - EleutherAI/the_pile_deduplicated language: - en --- # broken bc of updates to transformers library, let me reimplement and train GLORT2 (GLORT2 Low Rank Transformer Transformer) is a transformer model where every single linear layer is another smaller transformer model. I combined qkv into one operation which means one transformer instead of 3 to save on parameters, I played w using a transformer on the embeddings but it wasnt .. great, it's 768 dim 10 layers w/ 384 dim 1 layer as the replacements for linear layers (besides embed and lm head) also sorry I just realized theres some residual from where I copied the model code from in my own projects that includes some "expanded lm head size" stuff just ignore that if you're looking at the config and code this isn't a serious project so I don't care too much that it's there | model | 512-token strided perplexity on a pile test set | tokens | | --- | --- | --- | | cerebras 111m | 21.550655364990234 | 2.2b | | cerebras 256m | 15.203496932983398 | 5.1b | | cerebras 590m | 12.098200798034668 | 11.something b | | deduped pythia 70m (95.6M) | 22.393400192260742 | 300b | | deduped pythia 160m (213M) | 13.933751106262207 | 300b | | deduped pythia 410m (506M) | 9.61842155456543 | 300b | | llama w same settings as cerebras 111m (119m) | 13.882301330566406 | 2.2b | | llama plus w same settings as cerebras 111m and llama 70b embeddings (369m) | 13.565109252929688 | 2.2b | | **GLORT2 (205m)** | 13.051741600036621 | 2.2b | | Tasks |Version|Filter|n-shot| Metric |Value | |Stderr| |-------------|------:|------|-----:|--------|-----:|---|-----:| |arc_challenge| 1|none | 25|acc |0.1706|± |0.0110| | | |none | 25|acc_norm|0.2099|± |0.0119| |truthfulqa_mc2| 2|none | 0|acc |0.4599|± |0.0154| |winogrande| 1|none | 5|acc |0.5083|± |0.0141| |hellaswag| 1|none | 10|acc |0.2728|± |0.0044| | | |none | 10|acc_norm|0.2815|± |0.0045| |gsm8k| 2|get-answer| 5|exact_match| 0|± | 0| ### mmlu mean is 0.26394385964912276 i think | Tasks |Version|Filter|n-shot|Metric|Value | |Stderr| |-----------------------------------|------:|------|-----:|------|-----:|---|-----:| |world_religions | 0|none | 5|acc |0.1988|± |0.0306| |virology | 0|none | 5|acc |0.1928|± |0.0307| |us_foreign_policy | 0|none | 5|acc |0.2600|± |0.0441| |sociology | 0|none | 5|acc |0.2438|± |0.0304| |security_studies | 0|none | 5|acc |0.4000|± |0.0314| |public_relations | 0|none | 5|acc |0.2273|± |0.0401| |professional_psychology | 0|none | 5|acc |0.2484|± |0.0175| |professional_medicine | 0|none | 5|acc |0.4485|± |0.0302| |professional_law | 0|none | 5|acc |0.2445|± |0.0110| |professional_accounting | 0|none | 5|acc |0.2482|± |0.0258| |prehistory | 0|none | 5|acc |0.2562|± |0.0243| |philosophy | 0|none | 5|acc |0.2186|± |0.0235| |nutrition | 0|none | 5|acc |0.2941|± |0.0261| |moral_scenarios | 0|none | 5|acc |0.2503|± |0.0145| |moral_disputes | 0|none | 5|acc |0.1965|± |0.0214| |miscellaneous | 0|none | 5|acc |0.2554|± |0.0156| |medical_genetics | 0|none | 5|acc |0.3000|± |0.0461| |marketing | 0|none | 5|acc |0.1966|± |0.0260| |management | 0|none | 5|acc |0.1942|± |0.0392| |machine_learning | 0|none | 5|acc |0.2321|± |0.0401| |logical_fallacies | 0|none | 5|acc |0.2331|± |0.0332| |jurisprudence | 0|none | 5|acc |0.2407|± |0.0413| |international_law | 0|none | 5|acc |0.3719|± |0.0441| |human_sexuality | 0|none | 5|acc |0.2137|± |0.0360| |human_aging | 0|none | 5|acc |0.2646|± |0.0296| |high_school_world_history | 0|none | 5|acc |0.2489|± |0.0281| |high_school_us_history | 0|none | 5|acc |0.2304|± |0.0296| |high_school_statistics | 0|none | 5|acc |0.4722|± |0.0340| |high_school_psychology | 0|none | 5|acc |0.3083|± |0.0198| |high_school_physics | 0|none | 5|acc |0.3046|± |0.0376| |high_school_microeconomics | 0|none | 5|acc |0.3361|± |0.0307| |high_school_mathematics | 0|none | 5|acc |0.2630|± |0.0268| |high_school_macroeconomics | 0|none | 5|acc |0.3231|± |0.0237| |high_school_government_and_politics| 0|none | 5|acc |0.3523|± |0.0345| |high_school_geography | 0|none | 5|acc |0.3384|± |0.0337| |high_school_european_history | 0|none | 5|acc |0.2909|± |0.0355| |high_school_computer_science | 0|none | 5|acc |0.2600|± |0.0441| |high_school_chemistry | 0|none | 5|acc |0.2709|± |0.0313| |high_school_biology | 0|none | 5|acc |0.3161|± |0.0265| |global_facts | 0|none | 5|acc |0.1800|± |0.0386| |formal_logic | 0|none | 5|acc |0.1667|± |0.0333| |elementary_mathematics | 0|none | 5|acc |0.2540|± |0.0224| |electrical_engineering | 0|none | 5|acc |0.3103|± |0.0386| |econometrics | 0|none | 5|acc |0.2895|± |0.0427| |conceptual_physics | 0|none | 5|acc |0.2553|± |0.0285| |computer_security | 0|none | 5|acc |0.1900|± |0.0394| |college_physics | 0|none | 5|acc |0.3431|± |0.0472| |college_medicine | 0|none | 5|acc |0.2312|± |0.0321| |college_mathematics | 0|none | 5|acc |0.1800|± |0.0386| |college_computer_science | 0|none | 5|acc |0.3000|± |0.0461| |college_chemistry | 0|none | 5|acc |0.2900|± |0.0456| |college_biology | 0|none | 5|acc |0.2083|± |0.0340| |clinical_knowledge | 0|none | 5|acc |0.2038|± |0.0248| |business_ethics | 0|none | 5|acc |0.2100|± |0.0409| |astronomy | 0|none | 5|acc |0.1908|± |0.0320| |anatomy | 0|none | 5|acc |0.2963|± |0.0394| |abstract_algebra | 0|none | 5|acc |0.2000|± |0.0402|