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NLI_UniversalClassifier_beta
N1CKNGUYEN/NLI_UniversalClassifier_beta
NLI_UniversalClassifier_beta is a text classification model from N1CKNGUYEN. 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 8, 2025
- Updated
- May 8, 2025
- SHA
- 61ecc7aa
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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. -->
nli_classifier
This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3715
- F1 Macro: 0.8526
- F1 Micro: 0.8656
- Accuracy Balanced: 0.8527
- Accuracy: 0.8656
- Precision Macro: 0.8526
- Recall Macro: 0.8527
- Precision Micro: 0.8656
- Recall Micro: 0.8656
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: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.06
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Micro | Accuracy Balanced | Accuracy | Precision Macro | Recall Macro | Precision Micro | Recall Micro |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.2235 | 1.0 | 9145 | 0.3456 | 0.8493 | 0.8627 | 0.8488 | 0.8627 | 0.8497 | 0.8488 | 0.8627 | 0.8627 |
| 0.1575 | 1.9998 | 18288 | 0.3715 | 0.8526 | 0.8656 | 0.8527 | 0.8656 | 0.8526 | 0.8527 | 0.8656 | 0.8656 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- May 8, 2025
- Updated
- May 8, 2025