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bge-reranker-v2-m3-finetuned – AI Model by Nalyd1908 | AlphaNeural AI
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Nalyd1908
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bge-reranker-v2-m3-finetuned
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transformers
safetensors
xlm-roberta
text-classification
generated_from_trainer
BAAI/bge-reranker-v2-m3
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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bge-reranker-v2-m3-finetuned
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: 0.2950
Pointwise Accuracy: 0.919
Pointwise F1: 0.7990
Pointwise Auc: 0.9567
Group Top1 Accuracy: 0.885
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: 2e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 0.1
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Pointwise Accuracy
Pointwise F1
Pointwise Auc
Group Top1 Accuracy
1.8756
1.0
619
0.2950
0.919
0.7990
0.9567
0.885
Framework versions
Transformers 5.13.0
Pytorch 2.10.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2
