---
license: apache-2.0
tags:
- text-classification
- generated_from_trainer
datasets:
- paws-x
metrics:
- accuracy
model-index:
- name: paws_x_m_bert_only_ko
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: paws-x
      type: paws-x
      config: ko
      split: train
      args: ko
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8215
---

<!-- 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. -->

# paws_x_m_bert_only_ko

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the paws-x dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7649
- Accuracy: 0.8215

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5446        | 1.0   | 386  | 0.4837          | 0.768    |
| 0.3443        | 2.0   | 772  | 0.4530          | 0.8125   |
| 0.258         | 3.0   | 1158 | 0.4496          | 0.8145   |
| 0.2023        | 4.0   | 1544 | 0.4944          | 0.81     |
| 0.1581        | 5.0   | 1930 | 0.5040          | 0.814    |
| 0.1263        | 6.0   | 2316 | 0.5937          | 0.8145   |
| 0.1041        | 7.0   | 2702 | 0.6578          | 0.8115   |
| 0.0828        | 8.0   | 3088 | 0.6841          | 0.8215   |
| 0.0697        | 9.0   | 3474 | 0.7239          | 0.82     |
| 0.0596        | 10.0  | 3860 | 0.7649          | 0.8215   |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1