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CBert
wenda2025/CBert
CBert is a fill-mask model from wenda2025. Use it when you need the model to fill a missing word. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Fill-Mask
- Library
- transformers
- Model type
- cbert
- Access
- Public
- Created
- Apr 24, 2026
- Updated
- May 6, 2026
- SHA
- bda3b8f4
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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. -->
CBert
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3567
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 8
- 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: 10000
- num_epochs: 1006
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.3331 | 40.1606 | 20000 | 0.6457 |
| 0.4121 | 80.3213 | 40000 | 0.4129 |
| 0.2460 | 120.4819 | 60000 | 0.3705 |
| 0.1813 | 160.6426 | 80000 | 0.3514 |
| 0.1459 | 200.8032 | 100000 | 0.3478 |
| 0.1240 | 240.9639 | 120000 | 0.3188 |
| 0.1081 | 281.1245 | 140000 | 0.3414 |
| 0.0960 | 321.2851 | 160000 | 0.3398 |
| 0.0861 | 361.4458 | 180000 | 0.3567 |
Framework versions
- Transformers 5.6.2
- Pytorch 2.11.0+cu130
- Datasets 4.8.4
- Tokenizers 0.22.2
- Task
- Fill-Mask
- Library
- transformers
- Type
- cbert
- Created
- Apr 24, 2026
- Updated
- May 6, 2026