run-llama/finetune-embedding
1
0
Fork 0
mirror of https://github.com/run-llama/finetune-embedding.git synced 2026-07-01 20:54:01 -04:00
Code Issues 5 Packages Projects Releases Wiki Activity

wip

Browse Source
This commit is contained in:
Simon Suo
2023-08-22 00:41:22 -07:00
parent 4cc612e3c1
commit f0e1a476b3
1 changed files with 2 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files
results/Information-Retrieval_evaluation_finetuned_results.csv
+2
View File
@@ -0,0 +1,2 @@
epoch,steps,cos_sim-Accuracy@1,cos_sim-Accuracy@3,cos_sim-Accuracy@5,cos_sim-Accuracy@10,cos_sim-Precision@1,cos_sim-Recall@1,cos_sim-Precision@3,cos_sim-Recall@3,cos_sim-Precision@5,cos_sim-Recall@5,cos_sim-Precision@10,cos_sim-Recall@10,cos_sim-MRR@10,cos_sim-NDCG@10,cos_sim-MAP@100,dot_score-Accuracy@1,dot_score-Accuracy@3,dot_score-Accuracy@5,dot_score-Accuracy@10,dot_score-Precision@1,dot_score-Recall@1,dot_score-Precision@3,dot_score-Recall@3,dot_score-Precision@5,dot_score-Recall@5,dot_score-Precision@10,dot_score-Recall@10,dot_score-MRR@10,dot_score-NDCG@10,dot_score-MAP@100
-1,-1,0.6075949367088608,0.7860759493670886,0.8481012658227848,0.8949367088607595,0.6075949367088608,0.6075949367088608,0.2620253164556962,0.7860759493670886,0.16962025316455695,0.8481012658227848,0.08949367088607593,0.8949367088607595,0.7084348000803694,0.754002916549901,0.7127630344044761,0.6012658227848101,0.7873417721518987,0.8468354430379746,0.8936708860759494,0.6012658227848101,0.6012658227848101,0.26244725738396624,0.7873417721518987,0.16936708860759495,0.8468354430379746,0.08936708860759493,0.8936708860759494,0.7047292545710266,0.7509244135912676,0.7091348642450167
1 epoch steps cos_sim-Accuracy@1 cos_sim-Accuracy@3 cos_sim-Accuracy@5 cos_sim-Accuracy@10 cos_sim-Precision@1 cos_sim-Recall@1 cos_sim-Precision@3 cos_sim-Recall@3 cos_sim-Precision@5 cos_sim-Recall@5 cos_sim-Precision@10 cos_sim-Recall@10 cos_sim-MRR@10 cos_sim-NDCG@10 cos_sim-MAP@100 dot_score-Accuracy@1 dot_score-Accuracy@3 dot_score-Accuracy@5 dot_score-Accuracy@10 dot_score-Precision@1 dot_score-Recall@1 dot_score-Precision@3 dot_score-Recall@3 dot_score-Precision@5 dot_score-Recall@5 dot_score-Precision@10 dot_score-Recall@10 dot_score-MRR@10 dot_score-NDCG@10 dot_score-MAP@100
2 -1 -1 0.6075949367088608 0.7860759493670886 0.8481012658227848 0.8949367088607595 0.6075949367088608 0.6075949367088608 0.2620253164556962 0.7860759493670886 0.16962025316455695 0.8481012658227848 0.08949367088607593 0.8949367088607595 0.7084348000803694 0.754002916549901 0.7127630344044761 0.6012658227848101 0.7873417721518987 0.8468354430379746 0.8936708860759494 0.6012658227848101 0.6012658227848101 0.26244725738396624 0.7873417721518987 0.16936708860759495 0.8468354430379746 0.08936708860759493 0.8936708860759494 0.7047292545710266 0.7509244135912676 0.7091348642450167