---
language:
- mn
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: xlm-roberta-large-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. -->

# xlm-roberta-large-ner-demo

This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1273
- Precision: 0.8961
- Recall: 0.9143
- F1: 0.9051
- Accuracy: 0.9775

## 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.4849        | 1.0   | 64   | 0.1678          | 0.7415    | 0.7950 | 0.7673 | 0.9511   |
| 0.1432        | 2.0   | 128  | 0.1370          | 0.8276    | 0.8591 | 0.8430 | 0.9667   |
| 0.096         | 3.0   | 192  | 0.1122          | 0.8096    | 0.8593 | 0.8337 | 0.9685   |
| 0.0607        | 4.0   | 256  | 0.1246          | 0.8550    | 0.8829 | 0.8687 | 0.9725   |
| 0.0363        | 5.0   | 320  | 0.1153          | 0.8878    | 0.9089 | 0.8982 | 0.9768   |
| 0.0228        | 6.0   | 384  | 0.1229          | 0.8974    | 0.9148 | 0.9060 | 0.9775   |
| 0.0147        | 7.0   | 448  | 0.1273          | 0.8961    | 0.9143 | 0.9051 | 0.9775   |


### Framework versions

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