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router-mmBERT-base-v2-text-only
AmirMohseni/router-mmBERT-base-v2-text-only
router-mmBERT-base-v2-text-only is a text classification model from AmirMohseni. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- modernbert
- Access
- Public
- Created
- Oct 24, 2025
- Updated
- Oct 24, 2025
- SHA
- 985db478
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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. -->
router-mmBERT-base-v2-text-only
This model is a fine-tuned version of jhu-clsp/mmBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8326
- Accuracy: 0.6875
- Precision: 0.6827
- Recall: 0.6875
- F1: 0.6846
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- 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: cosine
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 2.6118 | 0.4545 | 20 | 0.6795 | 0.6193 | 0.7300 | 0.6193 | 0.6174 |
| 2.4002 | 0.9091 | 40 | 0.5451 | 0.7386 | 0.7327 | 0.7386 | 0.7270 |
| 2.1361 | 1.3636 | 60 | 0.8168 | 0.6705 | 0.6832 | 0.6705 | 0.6747 |
| 2.589 | 1.8182 | 80 | 0.5943 | 0.6364 | 0.6591 | 0.6364 | 0.6426 |
| 2.8187 | 2.2727 | 100 | 0.8248 | 0.5852 | 0.7404 | 0.5852 | 0.5725 |
| 2.08 | 2.7273 | 120 | 0.5875 | 0.7386 | 0.7409 | 0.7386 | 0.7166 |
| 1.1623 | 3.1818 | 140 | 0.6528 | 0.7159 | 0.7080 | 0.7159 | 0.7084 |
| 1.5022 | 3.6364 | 160 | 0.6610 | 0.6932 | 0.6828 | 0.6932 | 0.6834 |
| 0.898 | 4.0909 | 180 | 0.7076 | 0.6705 | 0.6683 | 0.6705 | 0.6693 |
| 0.7971 | 4.5455 | 200 | 0.8023 | 0.7045 | 0.6969 | 0.7045 | 0.6983 |
| 0.582 | 5.0 | 220 | 0.8326 | 0.6875 | 0.6827 | 0.6875 | 0.6846 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- modernbert
- License
- mit
- Created
- Oct 24, 2025
- Updated
- Oct 24, 2025