---
language:
- mn
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-multilingual-cased-ner-demo
  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-multilingual-cased-ner-demo

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: 0.1471
- Precision: 0.9148
- Recall: 0.9229
- F1: 0.9188
- Accuracy: 0.9759

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1743        | 1.0   | 477  | 0.0992          | 0.8649    | 0.8914 | 0.8780 | 0.9695   |
| 0.0848        | 2.0   | 954  | 0.0900          | 0.8822    | 0.9010 | 0.8915 | 0.9719   |
| 0.0557        | 3.0   | 1431 | 0.1110          | 0.8848    | 0.9001 | 0.8924 | 0.9699   |
| 0.0411        | 4.0   | 1908 | 0.1061          | 0.8993    | 0.9140 | 0.9066 | 0.9744   |
| 0.0298        | 5.0   | 2385 | 0.1130          | 0.8923    | 0.9147 | 0.9034 | 0.9732   |
| 0.0207        | 6.0   | 2862 | 0.1197          | 0.9078    | 0.9176 | 0.9127 | 0.9756   |
| 0.0144        | 7.0   | 3339 | 0.1372          | 0.9053    | 0.9180 | 0.9116 | 0.9742   |
| 0.0088        | 8.0   | 3816 | 0.1401          | 0.9080    | 0.9195 | 0.9137 | 0.9746   |
| 0.0066        | 9.0   | 4293 | 0.1442          | 0.9100    | 0.9216 | 0.9158 | 0.9753   |
| 0.0054        | 10.0  | 4770 | 0.1471          | 0.9148    | 0.9229 | 0.9188 | 0.9759   |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1