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ModernBERT-base-AIME-1983-2023-instruct-qe-classifier-binary-10ep-lr5e-05
ymoslem/ModernBERT-base-AIME-1983-2023-instruct-qe-classifier-binary-10ep-lr5e-05
ModernBERT-base-AIME-1983-2023-instruct-qe-classifier-binary-10ep-lr5e-05 is a text classification model from ymoslem. 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
- modernbert
- Access
- Public
- Created
- Dec 7, 2025
- Updated
- Dec 7, 2025
- SHA
- 05ae268f
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Base models
Datasets
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. -->
Query Quality Estimation - Binary Classification
This model is a fine-tuned version of answerdotai/ModernBERT-base on the ymoslem/AIME-1983-2023-instruct dataset. It achieves the following results on the evaluation set:
- Loss: 0.8385
- Accuracy: 0.9
- F1 Macro: 0.8769
- F1 Weighted: 0.8982
- Precision: 0.8920
- Recall: 0.8651
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: 64
- eval_batch_size: 64
- 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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision | Recall |
|---|---|---|---|---|---|---|---|---|
| 0.6792 | 1.0 | 29 | 0.4925 | 0.6333 | 0.6329 | 0.6378 | 0.725 | 0.7381 |
| 0.6136 | 2.0 | 58 | 0.4563 | 0.8333 | 0.7948 | 0.8304 | 0.8068 | 0.7857 |
| 0.439 | 3.0 | 87 | 0.3382 | 0.8 | 0.7885 | 0.8082 | 0.7879 | 0.8413 |
| 0.3324 | 4.0 | 116 | 0.2936 | 0.7833 | 0.7727 | 0.7924 | 0.7770 | 0.8294 |
| 0.2416 | 5.0 | 145 | 0.3051 | 0.8 | 0.7885 | 0.8082 | 0.7879 | 0.8413 |
| 0.2002 | 6.0 | 174 | 0.3490 | 0.8667 | 0.8535 | 0.8711 | 0.8403 | 0.8889 |
| 0.0714 | 7.0 | 203 | 0.5923 | 0.9167 | 0.9050 | 0.9183 | 0.8919 | 0.9246 |
| 0.0231 | 8.0 | 232 | 0.5090 | 0.8833 | 0.8703 | 0.8868 | 0.8561 | 0.9008 |
| 0.0057 | 9.0 | 261 | 0.6692 | 0.9 | 0.8845 | 0.9014 | 0.875 | 0.8968 |
| 0.0017 | 10.0 | 290 | 0.8385 | 0.9 | 0.8769 | 0.8982 | 0.8920 | 0.8651 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- modernbert
- License
- apache-2.0
- Languages
- en
- Created
- Dec 7, 2025
- Updated
- Dec 7, 2025