QuangDuy's picture
Update exported model
2acd975 verified
{
"model_path": "outputs/bert-tiny-stage2-sbert",
"dataset": "another-symato/VMTEB-Zalo-legel-retrieval-wseg",
"eval_split": "train",
"results": [
{
"truncate_dim": 384,
"cosine_accuracy@1": 0.20344287949921752,
"cosine_accuracy@3": 0.34076682316118934,
"cosine_accuracy@5": 0.4182316118935837,
"cosine_accuracy@10": 0.5246478873239436,
"cosine_precision@1": 0.20344287949921752,
"cosine_precision@3": 0.11358894105373016,
"cosine_precision@5": 0.08364632237871533,
"cosine_precision@10": 0.05246478873239306,
"cosine_recall@1": 0.20344287949921752,
"cosine_recall@3": 0.34076682316118934,
"cosine_recall@5": 0.4182316118935837,
"cosine_recall@10": 0.5246478873239436,
"cosine_ndcg@3": 0.28296443965459644,
"cosine_ndcg@5": 0.31498936372857955,
"cosine_ndcg@10": 0.34952346401058043,
"cosine_mrr@3": 0.263041210224309,
"cosine_mrr@5": 0.2808815858111636,
"cosine_mrr@10": 0.2952013003949625,
"cosine_map@100": 0.30558138488387787
},
{
"truncate_dim": 256,
"cosine_accuracy@1": 0.1936619718309859,
"cosine_accuracy@3": 0.3392018779342723,
"cosine_accuracy@5": 0.40923317683881066,
"cosine_accuracy@10": 0.5117370892018779,
"cosine_precision@1": 0.1936619718309859,
"cosine_precision@3": 0.11306729264475783,
"cosine_precision@5": 0.08184663536776082,
"cosine_precision@10": 0.051173708920186564,
"cosine_recall@1": 0.1936619718309859,
"cosine_recall@3": 0.3392018779342723,
"cosine_recall@5": 0.40923317683881066,
"cosine_recall@10": 0.5117370892018779,
"cosine_ndcg@3": 0.27754763557316336,
"cosine_ndcg@5": 0.3064740024881631,
"cosine_ndcg@10": 0.3397688675668828,
"cosine_mrr@3": 0.25632498695878986,
"cosine_mrr@5": 0.2724243609806993,
"cosine_mrr@10": 0.2862491305859853,
"cosine_map@100": 0.2966242956740067
},
{
"truncate_dim": 128,
"cosine_accuracy@1": 0.17566510172143976,
"cosine_accuracy@3": 0.3212050078247261,
"cosine_accuracy@5": 0.39123630672926446,
"cosine_accuracy@10": 0.4823943661971831,
"cosine_precision@1": 0.17566510172143976,
"cosine_precision@3": 0.10706833594157612,
"cosine_precision@5": 0.07824726134585179,
"cosine_precision@10": 0.04823943661971724,
"cosine_recall@1": 0.17566510172143976,
"cosine_recall@3": 0.3212050078247261,
"cosine_recall@5": 0.39123630672926446,
"cosine_recall@10": 0.4823943661971831,
"cosine_ndcg@3": 0.25980688782975864,
"cosine_ndcg@5": 0.2885789457629316,
"cosine_ndcg@10": 0.3182168056871434,
"cosine_mrr@3": 0.2386541471048512,
"cosine_mrr@5": 0.2545774647887326,
"cosine_mrr@10": 0.2668972166331323,
"cosine_map@100": 0.2779128681223102
},
{
"truncate_dim": 64,
"cosine_accuracy@1": 0.14241001564945227,
"cosine_accuracy@3": 0.27230046948356806,
"cosine_accuracy@5": 0.3517214397496088,
"cosine_accuracy@10": 0.4428794992175274,
"cosine_precision@1": 0.14241001564945227,
"cosine_precision@3": 0.09076682316119022,
"cosine_precision@5": 0.0703442879499211,
"cosine_precision@10": 0.0442879499217519,
"cosine_recall@1": 0.14241001564945227,
"cosine_recall@3": 0.27230046948356806,
"cosine_recall@5": 0.3517214397496088,
"cosine_recall@10": 0.4428794992175274,
"cosine_ndcg@3": 0.21647319880114255,
"cosine_ndcg@5": 0.2491862954231763,
"cosine_ndcg@10": 0.27884940087516746,
"cosine_mrr@3": 0.19731351069379194,
"cosine_mrr@5": 0.21546687532602982,
"cosine_mrr@10": 0.22781736716595852,
"cosine_map@100": 0.23812275569660138
}
]
}