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dsc25-nextlevelv2-bge-reranker-v2-m3-v1 – AI Model by htNghiaaa | AlphaNeural AI
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dsc25-nextlevelv2-bge-reranker-v2-m3-v1
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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-v1
This model is a fine-tuned version of
BAAI/bge-reranker-v2-m3
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.0750
F1 Macro: 0.7841
F1 Weighted: 0.7829
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
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_ratio: 0.1
num_epochs: 15
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
F1 Macro
F1 Weighted
0.7257
1.0
1620
0.7414
0.7792
0.7778
0.7244
2.0
3240
0.9083
0.8019
0.8010
0.6825
3.0
4860
0.9331
0.7967
0.7957
0.5836
4.0
6480
1.0750
0.7841
0.7829
Framework versions
Transformers 4.56.2
Pytorch 2.8.0+cu128
Datasets 4.1.1
Tokenizers 0.22.1
