metadata
license: mit
tags:
- text-classification
- generated_from_trainer
datasets:
- paws-x
metrics:
- accuracy
model-index:
- name: paws_x_xlm_r_only_de
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: paws-x
type: paws-x
config: de
split: train
args: de
metrics:
- name: Accuracy
type: accuracy
value: 0.87
paws_x_xlm_r_only_de
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: 0.5602
- Accuracy: 0.87
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 |
|---|---|---|---|---|
| 0.4751 | 1.0 | 386 | 0.4272 | 0.826 |
| 0.2308 | 2.0 | 772 | 0.3728 | 0.8575 |
| 0.1753 | 3.0 | 1158 | 0.4369 | 0.845 |
| 0.1387 | 4.0 | 1544 | 0.3616 | 0.8645 |
| 0.1169 | 5.0 | 1930 | 0.4507 | 0.8635 |
| 0.0975 | 6.0 | 2316 | 0.4476 | 0.8595 |
| 0.0829 | 7.0 | 2702 | 0.5073 | 0.8675 |
| 0.072 | 8.0 | 3088 | 0.5038 | 0.8655 |
| 0.0626 | 9.0 | 3474 | 0.5009 | 0.868 |
| 0.0562 | 10.0 | 3860 | 0.5602 | 0.87 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1