ViGLUE
Collection
A collection to store all the artifacts of the paper: ViGLUE: A Vietnamese General Language Understanding Benchmark and Analysis of Vietnamese LMs.
•
145 items
•
Updated
xlm-roberta-large-qqp-1
This model is a fine-tuned version of xlm-roberta-large on the tmnam20/VieGLUE/QQP dataset. It achieves the following results on the evaluation set:
- Loss: 0.2725
- Accuracy: 0.9048
- F1: 0.8722
- Combined Score: 0.8885
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: 32
- eval_batch_size: 16
- seed: 1
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
|---|---|---|---|---|---|---|
| 0.3045 | 0.88 | 10000 | 0.2747 | 0.8808 | 0.8324 | 0.8566 |
| 0.2256 | 1.76 | 20000 | 0.2695 | 0.8957 | 0.8617 | 0.8787 |
| 0.1643 | 2.64 | 30000 | 0.2808 | 0.9019 | 0.8684 | 0.8851 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Downloads last month
- 6
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for tmnam20/xlm-roberta-large-qqp-1
Base model
FacebookAI/xlm-roberta-largeDataset used to train tmnam20/xlm-roberta-large-qqp-1
Collection including tmnam20/xlm-roberta-large-qqp-1
Evaluation results
- Accuracy on tmnam20/VieGLUE/QQPvalidation set self-reported0.905
- F1 on tmnam20/VieGLUE/QQPvalidation set self-reported0.872