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ossbert-lemm-v2-1
ania3000/ossbert-lemm-v2-1
ossbert-lemm-v2-1 is a token classification model from ania3000. Use it when you need labels on individual words, such as names. 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
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Oct 11, 2026
- Updated
- Oct 11, 2026
- SHA
- 32688cb0
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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. -->
trainer_output
This model is a fine-tuned version of AlexeySorokin/ossbert-onc-unlab-from_multilingual-bs64-5epochs on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1166
- Lemma accuracy: 98.6967
- Sentence accuracy (lemmas): 85.1376
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: 8
- 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
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Lemma accuracy | Sentence accuracy (lemmas) |
|---|---|---|---|---|---|
| 0.7292 | 1.0 | 546 | 0.2585 | 95.4135 | 59.4495 |
| 0.2212 | 2.0 | 1092 | 0.1648 | 97.3559 | 70.8257 |
| 0.1307 | 3.0 | 1638 | 0.1367 | 97.5815 | 75.0459 |
| 0.0951 | 4.0 | 2184 | 0.1183 | 98.2080 | 80.9174 |
| 0.0692 | 5.0 | 2730 | 0.1078 | 98.3208 | 81.4679 |
| 0.0488 | 6.0 | 3276 | 0.1061 | 98.2832 | 81.4679 |
| 0.041 | 7.0 | 3822 | 0.0979 | 98.5714 | 83.6697 |
| 0.0289 | 8.0 | 4368 | 0.1050 | 98.5965 | 83.4862 |
| 0.0223 | 9.0 | 4914 | 0.1098 | 98.5213 | 83.6697 |
| 0.0171 | 10.0 | 5460 | 0.1014 | 98.6967 | 85.1376 |
| 0.0084 | 11.0 | 6006 | 0.1028 | 98.6967 | 86.0550 |
| 0.0074 | 12.0 | 6552 | 0.1009 | 98.6466 | 84.5872 |
| 0.0057 | 13.0 | 7098 | 0.1009 | 98.7469 | 85.3211 |
| 0.0052 | 14.0 | 7644 | 0.1059 | 98.7093 | 85.5046 |
| 0.0035 | 15.0 | 8190 | 0.1070 | 98.6842 | 84.7706 |
| 0.0035 | 16.0 | 8736 | 0.1103 | 98.6591 | 84.5872 |
| 0.0022 | 17.0 | 9282 | 0.1166 | 98.6967 | 85.1376 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.11.0+cu130
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Oct 11, 2026
- Updated
- Oct 11, 2026