ag_glm_s_n200_v1 · adjudicated
ag_news_200 | — | — | max_tokens 200, temperature 0.0 | none | correct 0.935 |
cnn_glm_s_n200_v1 · judged/judge-summ-pick-v1
cnn_dailymail_200 | — | — | max_tokens 1200, temperature 0.0 | none | judge_won 0.001 |
cnn_glm_s_n200_v1 · judged/judge-summ-v1
cnn_dailymail_200 | — | — | max_tokens 1200, temperature 0.0 | none | judge_score 4.530 |
cnn_glm_s_n200_v1 · judged/judge-summ-v2
cnn_dailymail_200 | — | — | max_tokens 1200, temperature 0.0 | none | judge_score 4.420 |
sf_glm_s_bm25first_n200_v1 · pair
scifact_200 | — | Evidence retrieval for scientific claims (SciFact) | max_tokens 700, temperature 0.0 | none | ndcg_10 0.742 |
sf_glm_s_e5first_n200_v1 · pair
scifact_200 | — | Evidence retrieval for scientific claims (SciFact) | max_tokens 700, temperature 0.0 | none | ndcg_10 0.789 |
cnn_glm_s_n200_v1 · silver
cnn_dailymail_200 | — | — | max_tokens 1200, temperature 0.0 | none | coverage 0.303 |
ag_glm_s_n200_v1
ag_news_200 | — | News topic classification (AG News) | max_tokens 200, temperature 0.0 | none | correct 0.850 |
cnn_glm_s_n200_v1
cnn_dailymail_200 | — | Short news summaries (CNN) | max_tokens 1200, temperature 0.0 | none | coverage 0.314 |
db_glm_s_n200_v1
dbpedia_280 | — | Encyclopedia topic classification (DBpedia) | max_tokens 200, temperature 0.0 | none | correct 0.939 |
fn_glm_s_n200_v1
few_nerd_280 | — | Named-entity extraction (Few-NERD) | max_tokens 600, temperature 0.0 | none | f1 0.553 |
sf_glm_s_n200_v1
scifact_200 | — | Evidence retrieval for scientific claims (SciFact) | max_tokens 700, temperature 0.0 | none | ndcg_10 0.744 |
se_glm_s_n100_v1
summeval_100 | — | A scorer that agrees with experts on summaries (SummEval) | max_tokens 1500, temperature 0.0 | none | tau 0.446 |
