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ModernBERT-base-TeleQnA-router-qe-classifier-binary-10ep-lr2e-05-qwen4b-5runs-5evals
ymoslem/ModernBERT-base-TeleQnA-router-qe-classifier-binary-10ep-lr2e-05-qwen4b-5runs-5evals
ModernBERT-base-TeleQnA-router-qe-classifier-binary-10ep-lr2e-05-qwen4b-5runs-5evals 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
- Jun 6, 2026
- Updated
- Jun 6, 2026
- SHA
- 97afa813
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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/TeleQnA-router dataset. It achieves the following results on the evaluation set:
- Loss: 3.1982
- Accuracy: 0.665
- F1 Macro: 0.5873
- F1 Weighted: 0.6479
- Precision: 0.6048
- Recall: 0.5852
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: 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 |
|---|---|---|---|---|---|---|---|---|
| 0.3857 | 1.0 | 704 | 1.0551 | 0.6658 | 0.5596 | 0.6328 | 0.5971 | 0.5643 |
| 0.1486 | 2.0 | 1408 | 1.3319 | 0.6342 | 0.5883 | 0.6348 | 0.5880 | 0.5887 |
| 0.0954 | 3.0 | 2112 | 1.8186 | 0.6512 | 0.5644 | 0.6302 | 0.5829 | 0.5648 |
| 0.0279 | 4.0 | 2816 | 1.8675 | 0.6262 | 0.6014 | 0.6350 | 0.6017 | 0.6119 |
| 0.0155 | 5.0 | 3520 | 2.6794 | 0.6638 | 0.5781 | 0.6425 | 0.6004 | 0.5774 |
| 0.0123 | 6.0 | 4224 | 2.7620 | 0.6458 | 0.5795 | 0.6360 | 0.5867 | 0.5776 |
| 0.0083 | 7.0 | 4928 | 2.7599 | 0.6524 | 0.5930 | 0.6456 | 0.5982 | 0.5908 |
| 0.002 | 8.0 | 5632 | 3.1982 | 0.665 | 0.5873 | 0.6479 | 0.6048 | 0.5852 |
Framework versions
- Transformers 4.57.3
- 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
- Jun 6, 2026
- Updated
- Jun 6, 2026