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abacus-cheat-tell-v2
idirectships/abacus-cheat-tell-v2
abacus-cheat-tell-v2 is a text classification model from idirectships. 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
- May 12, 2026
- Updated
- May 12, 2026
- SHA
- bab75e12
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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. -->
abacus-cheat-tell-v2
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: 0.7369
- Accuracy: 0.5429
- F1: 0.6522
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
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 9 | 0.7369 | 0.5429 | 0.6522 |
| 0.7391 | 2.0 | 18 | 0.7043 | 0.4857 | 0.4375 |
| 0.6190 | 3.0 | 27 | 0.7502 | 0.5143 | 0.5854 |
| 0.5088 | 4.0 | 36 | 0.7590 | 0.4857 | 0.5 |
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
- modernbert
- License
- apache-2.0
- Created
- May 12, 2026
- Updated
- May 12, 2026