bge_reranker

This model is a fine-tuned version of BAAI/bge-reranker-v2-m3 on an unknown dataset.

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: 3e-05
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine_with_restarts
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 4.0
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.42.4
• Pytorch 2.1.0+cu118
• Datasets 2.20.0
• Tokenizers 0.19.1