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---
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language:
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- mn
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license: cc-by-nc-sa-4.0
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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: wikineural-multilingual-ner-ner
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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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# wikineural-multilingual-ner-ner
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This model is a fine-tuned version of [Babelscape/wikineural-multilingual-ner](https://huggingface.co/Babelscape/wikineural-multilingual-ner) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0333
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- Precision: 0.9718
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- Recall: 0.9761
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- F1: 0.9739
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- Accuracy: 0.9937
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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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| 0.1605 | 1.0 | 477 | 0.0787 | 0.8892 | 0.9112 | 0.9001 | 0.9758 |
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| 0.0816 | 2.0 | 954 | 0.0583 | 0.9188 | 0.9324 | 0.9256 | 0.9821 |
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| 0.0533 | 3.0 | 1431 | 0.0474 | 0.9374 | 0.9494 | 0.9434 | 0.9865 |
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| 0.0367 | 4.0 | 1908 | 0.0384 | 0.9555 | 0.9628 | 0.9591 | 0.9899 |
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| 0.0272 | 5.0 | 2385 | 0.0363 | 0.9633 | 0.9667 | 0.9650 | 0.9910 |
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| 0.0193 | 6.0 | 2862 | 0.0348 | 0.9664 | 0.9710 | 0.9687 | 0.9927 |
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| 0.0142 | 7.0 | 3339 | 0.0328 | 0.9710 | 0.9746 | 0.9728 | 0.9931 |
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| 0.0088 | 8.0 | 3816 | 0.0325 | 0.9731 | 0.9761 | 0.9746 | 0.9937 |
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| 0.0069 | 9.0 | 4293 | 0.0332 | 0.9728 | 0.9766 | 0.9747 | 0.9939 |
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| 0.0051 | 10.0 | 4770 | 0.0333 | 0.9718 | 0.9761 | 0.9739 | 0.9937 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.0.0+cu118
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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