---
language:
- mn
base_model: bayartsogt/mongolian-roberta-base
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: 0.1834
- Precision: 0.6839
- Recall: 0.7644
- F1: 0.7219
- Accuracy: 0.9459

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.7672        | 1.0   | 20   | 0.5162          | 0.0825    | 0.0401 | 0.0540 | 0.8256   |
| 0.3886        | 2.0   | 40   | 0.3017          | 0.4778    | 0.5113 | 0.4939 | 0.9061   |
| 0.2163        | 3.0   | 60   | 0.2214          | 0.5543    | 0.6266 | 0.5882 | 0.9225   |
| 0.1199        | 4.0   | 80   | 0.1942          | 0.6346    | 0.7268 | 0.6776 | 0.9359   |
| 0.0742        | 5.0   | 100  | 0.1852          | 0.6396    | 0.7293 | 0.6815 | 0.9409   |
| 0.0555        | 6.0   | 120  | 0.1811          | 0.6943    | 0.7569 | 0.7242 | 0.9449   |
| 0.0407        | 7.0   | 140  | 0.1860          | 0.6804    | 0.7469 | 0.7121 | 0.9439   |
| 0.0346        | 8.0   | 160  | 0.1876          | 0.6952    | 0.7544 | 0.7236 | 0.9463   |
| 0.0302        | 9.0   | 180  | 0.1820          | 0.6868    | 0.7694 | 0.7258 | 0.9459   |
| 0.0289        | 10.0  | 200  | 0.1834          | 0.6839    | 0.7644 | 0.7219 | 0.9459   |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1