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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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license: apache-2.0
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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: test-distilbert-base-multilingual-cased
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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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# test-distilbert-base-multilingual-cased
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This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1533
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- Precision: 0.8783
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- Recall: 0.9010
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- F1: 0.8895
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- Accuracy: 0.9721
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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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| 0.2124 | 1.0 | 477 | 0.1286 | 0.8065 | 0.8469 | 0.8262 | 0.9586 |
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| 0.103 | 2.0 | 954 | 0.1113 | 0.8374 | 0.8772 | 0.8568 | 0.9663 |
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| 0.0673 | 3.0 | 1431 | 0.1124 | 0.8480 | 0.8810 | 0.8641 | 0.9668 |
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| 0.0474 | 4.0 | 1908 | 0.1165 | 0.8658 | 0.8922 | 0.8788 | 0.9710 |
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| 0.0338 | 5.0 | 2385 | 0.1254 | 0.8664 | 0.8909 | 0.8785 | 0.9692 |
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| 0.0236 | 6.0 | 2862 | 0.1349 | 0.8686 | 0.8954 | 0.8818 | 0.9707 |
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| 0.018 | 7.0 | 3339 | 0.1428 | 0.8772 | 0.8991 | 0.8880 | 0.9715 |
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| 0.0133 | 8.0 | 3816 | 0.1505 | 0.8739 | 0.8961 | 0.8849 | 0.9712 |
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| 0.0106 | 9.0 | 4293 | 0.1529 | 0.8812 | 0.9012 | 0.8911 | 0.9720 |
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| 0.0082 | 10.0 | 4770 | 0.1533 | 0.8783 | 0.9010 | 0.8895 | 0.9721 |
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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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