Stangerine
Stangerine
> Can you share the command you used? torchrun --nproc_per_node 1 \ -m FlagEmbedding.llm_reranker.finetune_for_layerwise.run \ --output_dir /opt/data/private/zzq/models/bge-reranker-v2-minicpm-layerwise-finetuned \ --model_name_or_path /opt/data/private/zzq/models/bge-reranker-v2-minicpm-layerwise \ --train_data /opt/data/private/zzq/dataset/train_data/2.0/finetune_data_for_reranker_2.0.jsonl \ --learning_rate 2e-4 \ --num_train_epochs 1 \...
> @545999961, please take a look at this issue when you are convenient. Thank you！my friend
> Can you provide specific error information? I want to know where the error occurred. 
> can you provide your version of `transformers` and `flash-attn` Thank you, it has been solved. I changed the versions of flash-attn and torch.
> can you provide your version of `transformers` and `flash-attn` ` warnings.warn( /root/anaconda3/envs/zzq_kdd/lib/python3.9/site-packages/transformers/tokenization_utils_base.py:2692: UserWarning: `max_length` is ignored when `padding`=`True` and there is no truncation strategy. To pad to max length,...
accelerate 0.29.1 addict 2.4.0 aiohttp 3.9.3 aiolimiter 1.1.0 aiosignal 1.3.1 aliyun-python-sdk-core 2.15.0 aliyun-python-sdk-kms 2.16.2 annotated-types 0.6.0 antlr4-python3-runtime 4.9.3 anyio 4.3.0 argon2-cffi 23.1.0 argon2-cffi-bindings 21.2.0 asgiref 3.8.1 async-timeout 4.0.3 attrs 23.2.0...
> can you provide your version of `transformers` and `flash-attn` > can you provide your version of `transformers` and `flash-attn` During the process of fine-tuning bge-reranker-v2-minicpm-layerwise, the loss floats around...
> > > can you provide your version of `transformers` and `flash-attn` > > > > > > > can you provide your version of `transformers` and `flash-attn` > >...
> > 同样的问题，希望大神指导一下怎么解决 > > 用sam2_hiera_large.pt可以跑通 我跑sam2_hiera_large.pt的时候，遇到这个问题，请问大佬有遇到过吗，萌新求助谢谢 Traceback (most recent call last): File "/data/zzq/object_tracking/SAM-Adapter-PyTorch/train.py", line 257, in main(config, save_path) File "/data/zzq/object_tracking/SAM-Adapter-PyTorch/train.py", line 175, in main train_loss_G = train(train_loader, model) File...
Thanks, I already know that. Also, I want to know if the results reported in the paper are the average of three runs, or the best of the three.