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2rtl3/mn-roberta-base-demo-named-entity
mn-roberta-base-demo-named-entity is a token classification model from 2rtl3. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
This model is a fine-tuned version of bayartsogt/mongolian-roberta-base on the None dataset. It achieves the following results on the evaluation set:
More information needed
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More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1651 | 1.0 | 477 | 0.0835 | 0.8900 | 0.9145 | 0.9021 | 0.9745 |
| 0.0535 | 2.0 | 954 | 0.0780 | 0.9047 | 0.9243 | 0.9144 | 0.9775 |
| 0.0267 | 3.0 | 1431 | 0.0836 | 0.9184 | 0.9307 | 0.9245 | 0.9790 |
| 0.0159 | 4.0 | 1908 | 0.0936 | 0.9224 | 0.9329 | 0.9276 | 0.9803 |
| 0.0083 | 5.0 | 2385 | 0.1155 | 0.9224 | 0.9307 | 0.9265 | 0.9790 |
| 0.0055 | 6.0 | 2862 | 0.1211 | 0.9222 | 0.9316 | 0.9268 | 0.9793 |
| 0.0034 | 7.0 | 3339 | 0.1258 | 0.9199 | 0.9329 | 0.9263 | 0.9789 |
| 0.0025 | 8.0 | 3816 | 0.1300 | 0.9249 | 0.9339 | 0.9294 | 0.9799 |
| 0.002 | 9.0 | 4293 | 0.1352 | 0.9231 | 0.9313 | 0.9272 | 0.9795 |
| 0.0018 | 10.0 | 4770 | 0.1354 | 0.9239 | 0.9322 | 0.9280 | 0.9797 |