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lease_sk_ner_emph_bsci_12_2
ttnksm/lease_sk_ner_emph_bsci_12_2
lease_sk_ner_emph_bsci_12_2 is a token classification model from ttnksm. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Feb 20, 2025
- Updated
- Feb 20, 2025
- SHA
- 5eb511c9
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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. -->
lease_sk_ner_emph_bsci_12_2
This model is a fine-tuned version of gerulata/slovakbert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0285
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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2206 | 1.0 | 309 | 0.0694 |
| 0.0449 | 2.0 | 618 | 0.0391 |
| 0.0316 | 3.0 | 927 | 0.0297 |
| 0.0208 | 4.0 | 1236 | 0.0290 |
| 0.0177 | 5.0 | 1545 | 0.0255 |
| 0.0133 | 6.0 | 1854 | 0.0268 |
| 0.0126 | 7.0 | 2163 | 0.0285 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0
- Task
- Token Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Feb 20, 2025
- Updated
- Feb 20, 2025