---
language:
- mn
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mongolian-gpt2-ner-finetuning
  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-gpt2-ner-finetuning

This model is a fine-tuned version of [bayartsogt/mongolian-gpt2](https://huggingface.co/bayartsogt/mongolian-gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3230
- Precision: 0.0989
- Recall: 0.2277
- F1: 0.1380
- Accuracy: 0.9078

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5225        | 1.0   | 477  | 0.3650          | 0.0743    | 0.1674 | 0.1030 | 0.8821   |
| 0.322         | 2.0   | 954  | 0.3129          | 0.0853    | 0.1903 | 0.1178 | 0.8966   |
| 0.2681        | 3.0   | 1431 | 0.3008          | 0.0915    | 0.2034 | 0.1262 | 0.9022   |
| 0.232         | 4.0   | 1908 | 0.2963          | 0.0914    | 0.2070 | 0.1269 | 0.9053   |
| 0.2029        | 5.0   | 2385 | 0.2974          | 0.0933    | 0.2120 | 0.1295 | 0.9071   |
| 0.1791        | 6.0   | 2862 | 0.3038          | 0.0949    | 0.2140 | 0.1315 | 0.9076   |
| 0.1603        | 7.0   | 3339 | 0.3100          | 0.0958    | 0.2186 | 0.1332 | 0.9079   |
| 0.146         | 8.0   | 3816 | 0.3174          | 0.0950    | 0.2156 | 0.1319 | 0.9079   |
| 0.1355        | 9.0   | 4293 | 0.3233          | 0.1001    | 0.2274 | 0.1390 | 0.9080   |
| 0.1291        | 10.0  | 4770 | 0.3230          | 0.0989    | 0.2277 | 0.1380 | 0.9078   |


### Framework versions

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