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bge-reranker-v2-m3-finetune
Mithilss/bge-reranker-v2-m3-finetune
bge-reranker-v2-m3-finetune is a text classification model from Mithilss. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- xlm-roberta
- Access
- Public
- Created
- Oct 2, 2025
- Updated
- Oct 3, 2025
- SHA
- 57074ea6
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
bge-reranker-v2-m3-finetune
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: 0.3696
- Spearman: nan
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: 5e-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
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Spearman |
|---|---|---|---|---|
| No log | 0 | 0 | 1.0280 | 0.0247 |
| 0.4622 | 0.1639 | 1000 | 0.3804 | 0.1140 |
| 0.4779 | 0.3278 | 2000 | 0.3672 | 0.0431 |
| 0.3758 | 0.4916 | 3000 | 0.3703 | nan |
| 0.1635 | 0.6555 | 4000 | 0.3711 | nan |
| 0.3221 | 0.8194 | 5000 | 0.3684 | nan |
| 0.3741 | 0.9833 | 6000 | 0.3674 | -0.0151 |
| 0.502 | 1.1472 | 7000 | 0.3676 | nan |
| 0.6405 | 1.3110 | 8000 | 0.3675 | nan |
| 0.6499 | 1.4749 | 9000 | 0.3683 | nan |
| 0.3073 | 1.6388 | 10000 | 0.3717 | -0.0190 |
| 0.2343 | 1.8027 | 11000 | 0.3700 | -0.0153 |
| 0.6064 | 1.9666 | 12000 | 0.3729 | nan |
| 0.2455 | 2.1304 | 13000 | 0.3700 | -0.0119 |
| 0.2484 | 2.2943 | 14000 | 0.3690 | nan |
| 0.3715 | 2.4582 | 15000 | 0.3695 | -0.0078 |
| 0.2333 | 2.6221 | 16000 | 0.3696 | nan |
| 0.4614 | 2.7860 | 17000 | 0.3696 | nan |
| 0.2435 | 2.9499 | 18000 | 0.3696 | nan |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- apache-2.0
- Created
- Oct 2, 2025
- Updated
- Oct 3, 2025