---
language:
- mn
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mongolian-Davlan-distilbert-base-multilingual-cased-ner-hrl
  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-Davlan-distilbert-base-multilingual-cased-ner-hrl

This model is a fine-tuned version of [Davlan/distilbert-base-multilingual-cased-ner-hrl](https://huggingface.co/Davlan/distilbert-base-multilingual-cased-ner-hrl) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1589
- Precision: 0.8750
- Recall: 0.8977
- F1: 0.8862
- Accuracy: 0.9714

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1974        | 1.0   | 477  | 0.1235          | 0.8022    | 0.8510 | 0.8259 | 0.9600   |
| 0.0953        | 2.0   | 954  | 0.1128          | 0.8315    | 0.8697 | 0.8502 | 0.9641   |
| 0.0621        | 3.0   | 1431 | 0.1149          | 0.8537    | 0.8832 | 0.8682 | 0.9675   |
| 0.0414        | 4.0   | 1908 | 0.1245          | 0.8534    | 0.8842 | 0.8686 | 0.9676   |
| 0.0289        | 5.0   | 2385 | 0.1400          | 0.8630    | 0.8895 | 0.8760 | 0.9692   |
| 0.0214        | 6.0   | 2862 | 0.1448          | 0.8612    | 0.8908 | 0.8758 | 0.9693   |
| 0.0156        | 7.0   | 3339 | 0.1534          | 0.8664    | 0.8924 | 0.8792 | 0.9699   |
| 0.0114        | 8.0   | 3816 | 0.1568          | 0.8755    | 0.8957 | 0.8855 | 0.9711   |
| 0.009         | 9.0   | 4293 | 0.1580          | 0.8710    | 0.8953 | 0.8830 | 0.9713   |
| 0.0076        | 10.0  | 4770 | 0.1589          | 0.8750    | 0.8977 | 0.8862 | 0.9714   |


### Framework versions

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