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---
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: 0.1352
- Precision: 0.9297
- Recall: 0.9366
- F1: 0.9331
- Accuracy: 0.9801
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1678 | 1.0 | 477 | 0.0929 | 0.8136 | 0.8806 | 0.8457 | 0.9679 |
| 0.0635 | 2.0 | 954 | 0.0894 | 0.8477 | 0.8933 | 0.8699 | 0.9708 |
| 0.0291 | 3.0 | 1431 | 0.0840 | 0.9262 | 0.9357 | 0.9309 | 0.9809 |
| 0.0163 | 4.0 | 1908 | 0.0928 | 0.9269 | 0.9357 | 0.9313 | 0.9805 |
| 0.0087 | 5.0 | 2385 | 0.1048 | 0.9259 | 0.9352 | 0.9305 | 0.9802 |
| 0.0059 | 6.0 | 2862 | 0.1179 | 0.9271 | 0.9339 | 0.9305 | 0.9794 |
| 0.0032 | 7.0 | 3339 | 0.1230 | 0.9278 | 0.9353 | 0.9316 | 0.9800 |
| 0.002 | 8.0 | 3816 | 0.1335 | 0.9285 | 0.9337 | 0.9311 | 0.9795 |
| 0.0016 | 9.0 | 4293 | 0.1341 | 0.9287 | 0.9358 | 0.9322 | 0.9799 |
| 0.0013 | 10.0 | 4770 | 0.1352 | 0.9297 | 0.9366 | 0.9331 | 0.9801 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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