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AMANDA
DarksitoBest/AMANDA
AMANDA is a text classification model from DarksitoBest. 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
- bert
- Access
- Public
- Created
- Dec 26, 2025
- Updated
- Dec 27, 2025
- SHA
- 41e2a884
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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. -->
AMANDA
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4717
- Accuracy: 0.8243
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: 5e-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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2389 | 0.0769 | 5 | 0.8651 | 0.8243 |
| 0.6616 | 0.1538 | 10 | 0.6137 | 0.8243 |
| 0.3941 | 0.2308 | 15 | 0.6143 | 0.8243 |
| 0.6576 | 0.3077 | 20 | 0.5270 | 0.8243 |
| 0.4628 | 0.3846 | 25 | 0.4904 | 0.8243 |
| 0.4493 | 0.4615 | 30 | 0.5351 | 0.8243 |
| 0.5603 | 0.5385 | 35 | 0.5049 | 0.8243 |
| 0.5586 | 0.6154 | 40 | 0.4949 | 0.8243 |
| 0.528 | 0.6923 | 45 | 0.4784 | 0.8243 |
| 0.6357 | 0.7692 | 50 | 0.4717 | 0.8243 |
| 0.4228 | 0.8462 | 55 | 0.4674 | 0.8243 |
| 0.4739 | 0.9231 | 60 | 0.4616 | 0.8243 |
| 0.4855 | 1.0 | 65 | 0.4503 | 0.8243 |
| 0.6234 | 1.0769 | 70 | 0.4921 | 0.8243 |
| 0.5158 | 1.1538 | 75 | 0.4351 | 0.8243 |
| 0.3356 | 1.2308 | 80 | 0.4576 | 0.8243 |
| 0.4118 | 1.3077 | 85 | 0.4457 | 0.8243 |
| 0.39 | 1.3846 | 90 | 0.4153 | 0.8243 |
| 0.3848 | 1.4615 | 95 | 0.4377 | 0.8243 |
| 0.3499 | 1.5385 | 100 | 0.4427 | 0.8209 |
| 0.3776 | 1.6154 | 105 | 0.3825 | 0.8446 |
| 0.4228 | 1.6923 | 110 | 0.3755 | 0.8345 |
| 0.3157 | 1.7692 | 115 | 0.4031 | 0.8243 |
| 0.3163 | 1.8462 | 120 | 0.4938 | 0.8277 |
| 0.504 | 1.9231 | 125 | 0.4861 | 0.8277 |
| 0.4722 | 2.0 | 130 | 0.4717 | 0.8243 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Dec 26, 2025
- Updated
- Dec 27, 2025