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mdeberta-economy-classifier
mljn/mdeberta-economy-classifier
mdeberta-economy-classifier is a text classification model from mljn. 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
- deberta-v2
- Access
- Public
- Created
- May 18, 2026
- Updated
- May 18, 2026
- SHA
- 4579ee91
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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. -->
mdeberta-economy-classifier
This model is a fine-tuned version of microsoft/mdeberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5882
- Accuracy: 0.7296
- Accuracy Balanced: 0.5
- F1 Positive: 0.0
- P Positive: 0.0
- R Positive: 0.0
- F1 Macro: 0.4218
- F1 Weighted: 0.6155
- Mcc: 0.0
- Roc Auc: 0.5
- Pr Auc: 0.2704
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: 8
- 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
- lr_scheduler_warmup_steps: 50
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Accuracy Balanced | F1 Positive | P Positive | R Positive | F1 Macro | F1 Weighted | Mcc | Roc Auc | Pr Auc |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.7176 | 1.0 | 98 | 0.7254 | 0.7296 | 0.5 | 0.0 | 0.0 | 0.0 | 0.4218 | 0.6155 | 0.0 | 0.5 | 0.2704 |
| 0.9435 | 2.0 | 196 | 0.9822 | 0.7296 | 0.5 | 0.0 | 0.0 | 0.0 | 0.4218 | 0.6155 | 0.0 | 0.5129 | 0.2764 |
| 0.7660 | 3.0 | 294 | 0.5887 | 0.7296 | 0.5 | 0.0 | 0.0 | 0.0 | 0.4218 | 0.6155 | 0.0 | 0.5 | 0.2704 |
| 1.2351 | 4.0 | 392 | 0.8542 | 0.7296 | 0.5 | 0.0 | 0.0 | 0.0 | 0.4218 | 0.6155 | 0.0 | 0.4608 | 0.2616 |
| 0.6943 | 5.0 | 490 | 0.6057 | 0.7296 | 0.5 | 0.0 | 0.0 | 0.0 | 0.4218 | 0.6155 | 0.0 | 0.5 | 0.2704 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- May 18, 2026
- Updated
- May 18, 2026