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ossbert-onc-unlab-bs64-5epochs
AlexeySorokin/ossbert-onc-unlab-bs64-5epochs
ossbert-onc-unlab-bs64-5epochs is a fill-mask model from AlexeySorokin. 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
- bert
- Access
- Public
- Created
- Feb 5, 2026
- Updated
- Feb 5, 2026
- SHA
- 450b4f73
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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. -->
ossbert-onc-unlab-bs64-5epochs
This model is a fine-tuned version of ania3000/untrained-ossbert-e on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.4311
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: 64
- eval_batch_size: 64
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.6292 | 0.4515 | 1000 | 4.9285 |
| 4.7574 | 0.9029 | 2000 | 4.4274 |
| 4.3777 | 1.3544 | 3000 | 4.1482 |
| 4.1427 | 1.8059 | 4000 | 3.9402 |
| 3.9638 | 2.2573 | 5000 | 3.7863 |
| 3.8346 | 2.7088 | 6000 | 3.6773 |
| 3.7363 | 3.1603 | 7000 | 3.6001 |
| 3.661 | 3.6117 | 8000 | 3.5307 |
| 3.6089 | 4.0632 | 9000 | 3.4765 |
| 3.555 | 4.5147 | 10000 | 3.4482 |
| 3.5316 | 4.9661 | 11000 | 3.4311 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.1+cu128
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Fill-Mask
- Library
- transformers
- Type
- bert
- Created
- Feb 5, 2026
- Updated
- Feb 5, 2026