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update model card README.md
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README.md
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---
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language:
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- mn
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: roberta-base-ner-demo
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# roberta-base-ner-demo
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This model is a fine-tuned version of [bayartsogt/mongolian-roberta-base](https://huggingface.co/bayartsogt/mongolian-roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1349
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- Precision: 0.9210
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- Recall: 0.9330
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- F1: 0.9269
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- Accuracy: 0.9788
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.1615 | 1.0 | 477 | 0.0917 | 0.8327 | 0.8817 | 0.8565 | 0.9680 |
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| 0.0615 | 2.0 | 954 | 0.0917 | 0.8432 | 0.8918 | 0.8668 | 0.9701 |
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| 0.0404 | 3.0 | 1431 | 0.0961 | 0.8411 | 0.8970 | 0.8682 | 0.9710 |
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| 0.0227 | 4.0 | 1908 | 0.1056 | 0.9081 | 0.9262 | 0.9171 | 0.9770 |
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| 0.0133 | 5.0 | 2385 | 0.1117 | 0.8781 | 0.9108 | 0.8942 | 0.9744 |
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| 0.0083 | 6.0 | 2862 | 0.1231 | 0.9111 | 0.9288 | 0.9199 | 0.9775 |
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| 0.0061 | 7.0 | 3339 | 0.1263 | 0.9110 | 0.9293 | 0.9200 | 0.9776 |
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| 0.0071 | 8.0 | 3816 | 0.1316 | 0.9197 | 0.9302 | 0.9249 | 0.9783 |
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| 0.0031 | 9.0 | 4293 | 0.1335 | 0.9228 | 0.9327 | 0.9277 | 0.9790 |
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| 0.0021 | 10.0 | 4770 | 0.1349 | 0.9210 | 0.9330 | 0.9269 | 0.9788 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 2.0.0+cu118
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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