---
language:
- mn
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-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-base-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: 0.1333
- Precision: 0.9160
- Recall: 0.9229
- F1: 0.9194
- Accuracy: 0.9779

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1658        | 1.0   | 572  | 0.1113          | 0.8581    | 0.8792 | 0.8685 | 0.9658   |
| 0.0816        | 2.0   | 1144 | 0.0880          | 0.8950    | 0.9096 | 0.9022 | 0.9737   |
| 0.0554        | 3.0   | 1716 | 0.0935          | 0.8941    | 0.9096 | 0.9018 | 0.9741   |
| 0.0394        | 4.0   | 2288 | 0.1069          | 0.9070    | 0.9189 | 0.9129 | 0.9762   |
| 0.0284        | 5.0   | 2860 | 0.1029          | 0.9007    | 0.9184 | 0.9095 | 0.9752   |
| 0.0192        | 6.0   | 3432 | 0.1110          | 0.9102    | 0.9214 | 0.9157 | 0.9764   |
| 0.0139        | 7.0   | 4004 | 0.1156          | 0.9166    | 0.9272 | 0.9218 | 0.9786   |
| 0.0095        | 8.0   | 4576 | 0.1319          | 0.9091    | 0.9174 | 0.9132 | 0.9761   |
| 0.0066        | 9.0   | 5148 | 0.1313          | 0.9132    | 0.9226 | 0.9179 | 0.9781   |
| 0.0053        | 10.0  | 5720 | 0.1333          | 0.9160    | 0.9229 | 0.9194 | 0.9779   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3