bge-reranker-v2-m3-finetune-lower-lr-gskf

This model is a fine-tuned version of BAAI/bge-reranker-v2-m3 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.3791
• Spearman: 0.5224

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 1e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Spearman
No log	0	0	0.5732	0.4669
0.3112	0.2455	1000	0.3868	0.4925
0.4568	0.4910	2000	0.3778	0.5076
0.5635	0.7366	3000	0.3827	0.5181
0.8171	0.9821	4000	0.3776	0.5221
0.2512	1.2276	5000	0.3791	0.5228
0.1408	1.4731	6000	0.3788	0.5226
0.6803	1.7186	7000	0.3790	0.5225
0.2595	1.9642	8000	0.3791	0.5224

Framework versions

• Transformers 4.56.2
• Pytorch 2.8.0+cu128
• Datasets 3.6.0
• Tokenizers 0.22.1