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{ "model_name": "22h__cabrita_7b_pt_850000", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.451 }, "oab_mcq": { "acc": 0.23 }, "enem_mcq": { "acc": 0.194 }, "bluex_mcq": { "acc": 0.183 }, "hatebr": { "acc": 0.5 }, "assin_rte_ptbr": { "acc": 0.226 }, "faquad_rte_parq": { "acc": 0.488 } }
{ "model_name": "22h__open-cabrita3b", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.45 }, "oab_mcq": { "acc": 0.229 }, "enem_mcq": { "acc": 0.194 }, "bluex_mcq": { "acc": 0.181 }, "hatebr": { "acc": 0.5 }, "assin_rte_ptbr": { "acc": 0.232 }, "faquad_rte_parq": { "acc": 0.488 } }
{ "model_name": "PORTULAN__gervasio-7b-portuguese-ptbr-decoder", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.456 }, "oab_mcq": { "acc": 0.233 }, "enem_mcq": { "acc": 0.188 }, "bluex_mcq": { "acc": 0.198 }, "hatebr": { "acc": 0.507 }, "assin_rte_ptbr": { "acc": 0.232 }, "faquad_rte_parq": { "acc": 0.488 } }
{ "model_name": "PORTULAN__gervasio-7b-portuguese-ptpt-decoder", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.454 }, "oab_mcq": { "acc": 0.232 }, "enem_mcq": { "acc": 0.198 }, "bluex_mcq": { "acc": 0.187 }, "hatebr": { "acc": 0.524 }, "assin_rte_ptbr": { "acc": 0.232 }, "faquad_rte_parq": { "acc": 0.488 } }
{ "model_name": "PORTULAN__gervasio-8b-portuguese-ptpt-decoder", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.729 }, "oab_mcq": { "acc": 0.482 }, "enem_mcq": { "acc": 0.7 }, "bluex_mcq": { "acc": 0.576 }, "hatebr": { "acc": 0.801 }, "assin_rte_ptbr": { "acc": 0.24 }, "faquad_rte_parq": { "acc": 0.524 } }
{ "model_name": "TucanoBR__Tucano-160m", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.464 }, "oab_mcq": { "acc": 0.229 }, "enem_mcq": { "acc": 0.193 }, "bluex_mcq": { "acc": 0.185 }, "hatebr": { "acc": 0.503 }, "assin_rte_ptbr": { "acc": 0.455 }, "faquad_rte_parq": { "acc": 0.488 } }
{ "model_name": "TucanoBR__Tucano-1b1-Instruct", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.45 }, "oab_mcq": { "acc": 0.269 }, "enem_mcq": { "acc": 0.199 }, "bluex_mcq": { "acc": 0.227 }, "hatebr": { "acc": 0.5 }, "assin_rte_ptbr": { "acc": 0.52 }, "faquad_rte_parq": { "acc": 0.479 } }
{ "model_name": "TucanoBR__Tucano-1b1", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.45 }, "oab_mcq": { "acc": 0.215 }, "enem_mcq": { "acc": 0.194 }, "bluex_mcq": { "acc": 0.228 }, "hatebr": { "acc": 0.501 }, "assin_rte_ptbr": { "acc": 0.232 }, "faquad_rte_parq": { "acc": 0.488 } }
{ "model_name": "TucanoBR__Tucano-2b4-Instruct", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.45 }, "oab_mcq": { "acc": 0.255 }, "enem_mcq": { "acc": 0.184 }, "bluex_mcq": { "acc": 0.231 }, "hatebr": { "acc": 0.5 }, "assin_rte_ptbr": { "acc": 0.232 }, "faquad_rte_parq": { "acc": 0.488 } }
{ "model_name": "TucanoBR__Tucano-2b4", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.436 }, "oab_mcq": { "acc": 0.229 }, "enem_mcq": { "acc": 0.179 }, "bluex_mcq": { "acc": 0.19 }, "hatebr": { "acc": 0.521 }, "assin_rte_ptbr": { "acc": 0.232 }, "faquad_rte_parq": { "acc": 0.488 } }
{ "model_name": "maritaca-ai__sabia-7b", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.455 }, "oab_mcq": { "acc": 0.396 }, "enem_mcq": { "acc": 0.635 }, "bluex_mcq": { "acc": 0.522 }, "hatebr": { "acc": 0.621 }, "assin_rte_ptbr": { "acc": 0.232 }, "faquad_rte_parq": { "acc": 0.506 } }
{ "model_name": "prosodia__ProsodiaT1.7B", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.747 }, "oab_mcq": { "acc": 0.566 }, "enem_mcq": { "acc": 0.714 }, "bluex_mcq": { "acc": 0.593 }, "hatebr": { "acc": 0.785 }, "assin_rte_ptbr": { "acc": 0.833 }, "faquad_rte_parq": { "acc": 0.665 } }
{ "model_name": "recogna-nlp__Bode-3.1-8B-Instruct-full", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.72 }, "oab_mcq": { "acc": 0.478 }, "enem_mcq": { "acc": 0.698 }, "bluex_mcq": { "acc": 0.565 }, "hatebr": { "acc": 0.79 }, "assin_rte_ptbr": { "acc": 0.236 }, "faquad_rte_parq": { "acc": 0.538 } }
{ "model_name": "recogna-nlp__Phi-Bode", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.491 }, "oab_mcq": { "acc": 0.235 }, "enem_mcq": { "acc": 0.202 }, "bluex_mcq": { "acc": 0.182 }, "hatebr": { "acc": 0.527 }, "assin_rte_ptbr": { "acc": 0.232 }, "faquad_rte_parq": { "acc": 0.447 } }
{ "model_name": "recogna-nlp__phi-bode-2-ultraalpaca", "model_dtype": "float16", "model_sha": "main" }
{ "tweetsent": { "acc": 0.482 }, "oab_mcq": { "acc": 0.232 }, "enem_mcq": { "acc": 0.199 }, "bluex_mcq": { "acc": 0.183 }, "hatebr": { "acc": 0.506 }, "assin_rte_ptbr": { "acc": 0.232 }, "faquad_rte_parq": { "acc": 0.291 } }

Those results back the first publication of "Atlas", our portuguese-only language models benchmark, whose purpose is to fullfill as a guidance for understand the SLM/LLM scenario in all portuguese-speaking countries. The results found here are not supposed to either accomplish every model or every benchmarking-tasks possible, although the objective of such thing is, indeed, to provide a complete panorama for our lusophone models.

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