---
language:
- mn
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-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. -->

# distilbert-base-multilingual-cased-ner-demo

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1687
- Precision: 0.8684
- Recall: 0.8891
- F1: 0.8786
- Accuracy: 0.9693

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2009        | 1.0   | 572  | 0.1271          | 0.8074    | 0.8440 | 0.8253 | 0.9590   |
| 0.0951        | 2.0   | 1144 | 0.1069          | 0.8469    | 0.8768 | 0.8616 | 0.9671   |
| 0.063         | 3.0   | 1716 | 0.1136          | 0.8486    | 0.8783 | 0.8632 | 0.9680   |
| 0.0444        | 4.0   | 2288 | 0.1221          | 0.8506    | 0.8808 | 0.8654 | 0.9675   |
| 0.0303        | 5.0   | 2860 | 0.1389          | 0.8576    | 0.8823 | 0.8698 | 0.9677   |
| 0.0217        | 6.0   | 3432 | 0.1457          | 0.8683    | 0.8878 | 0.8779 | 0.9685   |
| 0.0157        | 7.0   | 4004 | 0.1542          | 0.8661    | 0.8873 | 0.8766 | 0.9692   |
| 0.0121        | 8.0   | 4576 | 0.1615          | 0.8730    | 0.8878 | 0.8803 | 0.9694   |
| 0.0094        | 9.0   | 5148 | 0.1675          | 0.8683    | 0.8883 | 0.8782 | 0.9688   |
| 0.0077        | 10.0  | 5720 | 0.1687          | 0.8684    | 0.8891 | 0.8786 | 0.9693   |


### Framework versions

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