---
language:
- mn
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-multilingual-cased-mongolian-ner
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert-base-multilingual-cased-mongolian-ner

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1423
- Precision: 0.9057
- Recall: 0.9188
- F1: 0.9122
- Accuracy: 0.9753

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1726        | 1.0   | 477  | 0.1052          | 0.8531    | 0.8851 | 0.8688 | 0.9664   |
| 0.0827        | 2.0   | 954  | 0.0975          | 0.8722    | 0.8987 | 0.8852 | 0.9699   |
| 0.0571        | 3.0   | 1431 | 0.0926          | 0.8847    | 0.9054 | 0.8950 | 0.9719   |
| 0.0376        | 4.0   | 1908 | 0.1052          | 0.8980    | 0.9119 | 0.9049 | 0.9727   |
| 0.0271        | 5.0   | 2385 | 0.1137          | 0.9021    | 0.9158 | 0.9089 | 0.9746   |
| 0.0182        | 6.0   | 2862 | 0.1304          | 0.8839    | 0.9106 | 0.8970 | 0.9712   |
| 0.0145        | 7.0   | 3339 | 0.1274          | 0.9042    | 0.9187 | 0.9114 | 0.9748   |
| 0.0097        | 8.0   | 3816 | 0.1375          | 0.9009    | 0.9169 | 0.9088 | 0.9739   |
| 0.0063        | 9.0   | 4293 | 0.1421          | 0.9017    | 0.9171 | 0.9093 | 0.9748   |
| 0.0049        | 10.0  | 4770 | 0.1423          | 0.9057    | 0.9188 | 0.9122 | 0.9753   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3