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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: Mongolian-distilbert-base-multilingual-cased-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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# Mongolian-distilbert-base-multilingual-cased-ner
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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: 0.1344
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- Precision: 0.8878
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- Recall: 0.9055
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- F1: 0.8966
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- Accuracy: 0.9739
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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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| 0.2155 | 1.0 | 477 | 0.1297 | 0.8050 | 0.8476 | 0.8257 | 0.9584 |
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| 0.1037 | 2.0 | 954 | 0.0951 | 0.8505 | 0.8882 | 0.8690 | 0.9699 |
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| 0.0687 | 3.0 | 1431 | 0.0978 | 0.8686 | 0.8924 | 0.8803 | 0.9711 |
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| 0.05 | 4.0 | 1908 | 0.1087 | 0.8764 | 0.8955 | 0.8858 | 0.9719 |
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| 0.0343 | 5.0 | 2385 | 0.1109 | 0.8781 | 0.8992 | 0.8885 | 0.9729 |
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| 0.0264 | 6.0 | 2862 | 0.1169 | 0.8798 | 0.9011 | 0.8903 | 0.9729 |
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| 0.0182 | 7.0 | 3339 | 0.1221 | 0.8871 | 0.9051 | 0.8960 | 0.9744 |
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| 0.0146 | 8.0 | 3816 | 0.1286 | 0.8846 | 0.9036 | 0.8940 | 0.9735 |
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| 0.0109 | 9.0 | 4293 | 0.1347 | 0.8880 | 0.9046 | 0.8962 | 0.9737 |
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| 0.0095 | 10.0 | 4770 | 0.1344 | 0.8878 | 0.9055 | 0.8966 | 0.9739 |
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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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