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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: testing_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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# testing_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: 0.1244
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- Precision: 0.9311
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- Recall: 0.9399
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- F1: 0.9355
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- Accuracy: 0.9821
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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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| 0.1683 | 1.0 | 477 | 0.0805 | 0.8377 | 0.8921 | 0.8640 | 0.9730 |
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| 0.0545 | 2.0 | 954 | 0.0739 | 0.9205 | 0.9334 | 0.9269 | 0.9806 |
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| 0.0292 | 3.0 | 1431 | 0.0778 | 0.9270 | 0.9354 | 0.9312 | 0.9817 |
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| 0.0164 | 4.0 | 1908 | 0.0884 | 0.9290 | 0.9360 | 0.9325 | 0.9820 |
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| 0.008 | 5.0 | 2385 | 0.1025 | 0.9247 | 0.9365 | 0.9306 | 0.9811 |
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| 0.0057 | 6.0 | 2862 | 0.1093 | 0.9294 | 0.9369 | 0.9331 | 0.9815 |
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| 0.0037 | 7.0 | 3339 | 0.1173 | 0.9336 | 0.9412 | 0.9374 | 0.9822 |
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| 0.0026 | 8.0 | 3816 | 0.1217 | 0.9281 | 0.9374 | 0.9327 | 0.9817 |
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| 0.0016 | 9.0 | 4293 | 0.1225 | 0.9334 | 0.9399 | 0.9366 | 0.9821 |
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| 0.0012 | 10.0 | 4770 | 0.1244 | 0.9311 | 0.9399 | 0.9355 | 0.9821 |
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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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