---
language:
- mn
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mongolian-bert-base-multilingual-cased-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. -->

# mongolian-bert-base-multilingual-cased-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: 0.1399
- Precision: 0.9072
- Recall: 0.9189
- F1: 0.9131
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1794        | 1.0   | 477  | 0.1089          | 0.8606    | 0.8871 | 0.8737 | 0.9685   |
| 0.0859        | 2.0   | 954  | 0.0978          | 0.8734    | 0.8973 | 0.8852 | 0.9703   |
| 0.0597        | 3.0   | 1431 | 0.0959          | 0.8970    | 0.9080 | 0.9025 | 0.9749   |
| 0.042         | 4.0   | 1908 | 0.1032          | 0.9008    | 0.9167 | 0.9087 | 0.9751   |
| 0.028         | 5.0   | 2385 | 0.1177          | 0.9011    | 0.9157 | 0.9083 | 0.9755   |
| 0.02          | 6.0   | 2862 | 0.1239          | 0.9048    | 0.9150 | 0.9099 | 0.9749   |
| 0.0143        | 7.0   | 3339 | 0.1289          | 0.9045    | 0.9168 | 0.9106 | 0.9749   |
| 0.009         | 8.0   | 3816 | 0.1376          | 0.9037    | 0.9171 | 0.9103 | 0.9755   |
| 0.0068        | 9.0   | 4293 | 0.1372          | 0.9067    | 0.9188 | 0.9127 | 0.9763   |
| 0.0053        | 10.0  | 4770 | 0.1399          | 0.9072    | 0.9189 | 0.9131 | 0.9759   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3