ViGLUE
Collection
A collection to store all the artifacts of the paper: ViGLUE: A Vietnamese General Language Understanding Benchmark and Analysis of Vietnamese LMs.
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145 items
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Updated
xlm-roberta-base-vsmec-1
This model is a fine-tuned version of xlm-roberta-base on the tmnam20/VieGLUE/VSMEC dataset. It achieves the following results on the evaluation set:
- Loss: 1.3235
- Accuracy: 0.5131
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 |
|---|---|---|---|---|
| 1.2379 | 2.87 | 500 | 1.3185 | 0.5146 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.2.0.dev20231203+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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Finetuned from
Dataset used to train tmnam20/xlm-roberta-base-vsmec-1
Collection including tmnam20/xlm-roberta-base-vsmec-1
Evaluation results
- Accuracy on tmnam20/VieGLUE/VSMECvalidation set self-reported0.513