metadata
license: mit
tags:
- text-classification
- generated_from_trainer
datasets:
- paws-x
metrics:
- accuracy
model-index:
- name: paws_x_xlm_r_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: 0.8455
paws_x_xlm_r_only_ko
This model is a fine-tuned version of xlm-roberta-base on the paws-x dataset. It achieves the following results on the evaluation set:
- Loss: 0.5742
- Accuracy: 0.8455
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 |
|---|---|---|---|---|
| 0.5604 | 1.0 | 386 | 0.5049 | 0.779 |
| 0.356 | 2.0 | 772 | 0.4272 | 0.8235 |
| 0.2846 | 3.0 | 1158 | 0.3901 | 0.835 |
| 0.2375 | 4.0 | 1544 | 0.4433 | 0.8395 |
| 0.2 | 5.0 | 1930 | 0.4665 | 0.8375 |
| 0.1717 | 6.0 | 2316 | 0.4815 | 0.8385 |
| 0.1487 | 7.0 | 2702 | 0.4973 | 0.8445 |
| 0.1288 | 8.0 | 3088 | 0.5234 | 0.8365 |
| 0.1158 | 9.0 | 3474 | 0.5528 | 0.844 |
| 0.1061 | 10.0 | 3860 | 0.5742 | 0.8455 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1