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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: mongolian-roberta-base
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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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# mongolian-roberta-base
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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: 0.1308
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- Precision: 0.9243
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- Recall: 0.9322
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- F1: 0.9283
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- Accuracy: 0.9799
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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: 9
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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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| 0.1632 | 1.0 | 477 | 0.0908 | 0.8293 | 0.8817 | 0.8547 | 0.9682 |
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| 0.0607 | 2.0 | 954 | 0.0920 | 0.8506 | 0.8898 | 0.8698 | 0.9712 |
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| 0.0331 | 3.0 | 1431 | 0.0975 | 0.9192 | 0.9267 | 0.9229 | 0.9779 |
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| 0.0148 | 4.0 | 1908 | 0.1024 | 0.9179 | 0.9294 | 0.9236 | 0.9786 |
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| 0.0087 | 5.0 | 2385 | 0.1091 | 0.9196 | 0.9296 | 0.9246 | 0.9796 |
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| 0.0052 | 6.0 | 2862 | 0.1222 | 0.9240 | 0.9323 | 0.9281 | 0.9794 |
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| 0.0033 | 7.0 | 3339 | 0.1233 | 0.9214 | 0.9317 | 0.9265 | 0.9796 |
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| 0.0024 | 8.0 | 3816 | 0.1310 | 0.9250 | 0.9315 | 0.9282 | 0.9797 |
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| 0.0016 | 9.0 | 4293 | 0.1308 | 0.9243 | 0.9322 | 0.9283 | 0.9799 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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