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answerdotai-ModernBERT-base_finetuned_augmented_augmented_nemotron-mini_4b
jackmedda/answerdotai-ModernBERT-base_finetuned_augmented_augmented_nemotron-mini_4b
answerdotai-ModernBERT-base_finetuned_augmented_augmented_nemotron-mini_4b is a text classification model from jackmedda. 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
- Feb 12, 2025
- Updated
- Feb 12, 2025
- SHA
- a4e9e35a
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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. -->
jackmedda/answerdotai-ModernBERT-base_finetuned_augmented_augmented_nemotron-mini_4b
This model is a fine-tuned version of answerdotai/ModernBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1590
- Accuracy: 0.9412
- F1: 0.9630
- Precision: 0.9286
- Recall: 1.0
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4854 | 1.0 | 43 | 1.2795 | 0.7 | 0.8235 | 0.7 | 1.0 |
| 1.0535 | 2.0 | 86 | 0.9959 | 0.7 | 0.8235 | 0.7 | 1.0 |
| 0.3683 | 3.0 | 129 | 0.5920 | 0.7 | 0.8235 | 0.7 | 1.0 |
| 0.6496 | 4.0 | 172 | 1.2441 | 0.7 | 0.8235 | 0.7 | 1.0 |
| 0.2656 | 5.0 | 215 | 0.8700 | 0.8 | 0.875 | 0.7778 | 1.0 |
| 0.2251 | 6.0 | 258 | 0.4596 | 0.9 | 0.9333 | 0.875 | 1.0 |
| 0.0032 | 7.0 | 301 | 1.7857 | 0.8 | 0.875 | 0.7778 | 1.0 |
| 0.0047 | 8.0 | 344 | 1.3231 | 0.9 | 0.9333 | 0.875 | 1.0 |
| 0.0 | 9.0 | 387 | 1.4540 | 0.9 | 0.9333 | 0.875 | 1.0 |
| 0.0 | 10.0 | 430 | 1.6984 | 0.9 | 0.9333 | 0.875 | 1.0 |
| 0.0 | 11.0 | 473 | 1.7000 | 0.9 | 0.9333 | 0.875 | 1.0 |
| 0.0 | 12.0 | 516 | 1.6878 | 0.9 | 0.9333 | 0.875 | 1.0 |
| 0.0 | 13.0 | 559 | 1.6862 | 0.9 | 0.9333 | 0.875 | 1.0 |
| 0.0 | 14.0 | 602 | 1.6822 | 0.9 | 0.9333 | 0.875 | 1.0 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- modernbert
- License
- apache-2.0
- Created
- Feb 12, 2025
- Updated
- Feb 12, 2025