update reranker FT

Author: 545999961

FlagEmbedding/abc/finetune/reranker/AbsModeling.py

@@ -61,7 +61,7 @@ def forward(self, pair: Union[Dict[str, Tensor], List[Dict[str, Tensor]]] = None
             if teacher_scores is not None:
                 teacher_targets = teacher_targets.to(grouped_logits.device)
                 # print(teacher_targets, torch.mean(torch.sum(torch.log_softmax(grouped_logits, dim=-1) * teacher_targets, dim=-1)))
-                loss += torch.mean(torch.sum(torch.log_softmax(grouped_logits, dim=-1) * teacher_targets, dim=-1))
+                loss += - torch.mean(torch.sum(torch.log_softmax(grouped_logits, dim=-1) * teacher_targets, dim=-1))
         else:
             loss = None
 

examples/finetune/reranker/README.md

@@ -248,7 +248,7 @@ torchrun --nproc_per_node 2 \
     --query_instruction_format '{}{}' \
     --passage_instruction_for_rerank 'B: ' \
     --passage_instruction_format '{}{}' \
-	--output_dir ./test_decoder_only_base_bge-reranker-v2-gemma \
+	--output_dir ./test_decoder_only_base_bge-reranker-v2-minicpm-layerwise \
     --overwrite_output_dir \
     --learning_rate 2e-4 \
     --fp16 \