---
language:
- mn
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-base-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. -->

# roberta-base-ner-demo

This model is a fine-tuned version of [bayartsogt/mongolian-roberta-base](https://huggingface.co/bayartsogt/mongolian-roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1444
- Precision: 0.9066
- Recall: 0.9148
- F1: 0.9107
- Accuracy: 0.9794

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1657        | 1.0   | 477  | 0.0976          | 0.8844    | 0.8947 | 0.8895 | 0.9692   |
| 0.0631        | 2.0   | 954  | 0.0917          | 0.8871    | 0.9084 | 0.8976 | 0.9709   |
| 0.0387        | 3.0   | 1431 | 0.1079          | 0.8978    | 0.9099 | 0.9038 | 0.9714   |
| 0.0272        | 4.0   | 1908 | 0.1198          | 0.8993    | 0.9119 | 0.9056 | 0.9716   |
| 0.017         | 5.0   | 2385 | 0.1235          | 0.9038    | 0.9108 | 0.9073 | 0.9783   |
| 0.007         | 6.0   | 2862 | 0.1272          | 0.9085    | 0.9151 | 0.9118 | 0.9795   |
| 0.0038        | 7.0   | 3339 | 0.1295          | 0.9064    | 0.9172 | 0.9118 | 0.9796   |
| 0.0029        | 8.0   | 3816 | 0.1368          | 0.9045    | 0.9167 | 0.9106 | 0.9795   |
| 0.0019        | 9.0   | 4293 | 0.1425          | 0.9076    | 0.9173 | 0.9124 | 0.9796   |
| 0.0015        | 10.0  | 4770 | 0.1444          | 0.9066    | 0.9148 | 0.9107 | 0.9794   |


### Framework versions

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