---
language:
- mn
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
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:
- eval_loss: 0.0728
- eval_precision: 0.9070
- eval_recall: 0.9260
- eval_f1: 0.9164
- eval_accuracy: 0.9789
- eval_runtime: 99.382
- eval_samples_per_second: 25.568
- eval_steps_per_second: 0.805
- epoch: 2.0
- step: 954

## 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

### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1