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modernbert-base-optuna-final
valer125/modernbert-base-optuna-final
modernbert-base-optuna-final is a text classification model from valer125. 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
- Oct 25, 2025
- Updated
- Oct 25, 2025
- SHA
- b22dc824
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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. -->
modernbert-base-optuna-final
This model is a fine-tuned version of answerdotai/ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6436
- Accuracy: 0.92
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: 16
- eval_batch_size: 16
- 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2663 | 1.0 | 1147 | 0.7402 | 0.9735 |
| 0.5182 | 2.0 | 2294 | 0.4189 | 0.9903 |
| 0.3466 | 3.0 | 3441 | 0.3385 | 0.9939 |
| 0.2841 | 4.0 | 4588 | 0.3102 | 0.9948 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- modernbert
- License
- apache-2.0
- Created
- Oct 25, 2025
- Updated
- Oct 25, 2025