---
license: mit
tags:
- generated_from_trainer
datasets:
- xtreme
metrics:
- f1
model-index:
- name: xlm-roberta-base-finetuned-ko-tjdrms
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: xtreme
      type: xtreme
      config: PAN-X.ko
      split: validation
      args: PAN-X.ko
    metrics:
    - name: F1
      type: f1
      value: 0.8975178176456132
---

<!-- 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-base-finetuned-ko-tjdrms

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3122
- F1: 0.8975

## 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: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.383         | 1.0   | 834  | 0.2389          | 0.8459 |
| 0.2142        | 2.0   | 1668 | 0.2235          | 0.8530 |
| 0.1524        | 3.0   | 2502 | 0.1992          | 0.8794 |
| 0.1101        | 4.0   | 3336 | 0.2284          | 0.8767 |
| 0.0816        | 5.0   | 4170 | 0.2290          | 0.8854 |
| 0.0592        | 6.0   | 5004 | 0.2512          | 0.8876 |
| 0.0417        | 7.0   | 5838 | 0.2705          | 0.8891 |
| 0.0293        | 8.0   | 6672 | 0.2942          | 0.8924 |
| 0.0206        | 9.0   | 7506 | 0.2961          | 0.8952 |
| 0.0142        | 10.0  | 8340 | 0.3122          | 0.8975 |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3