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
mdeberta-v3-base-rte-100
This model is a fine-tuned version of microsoft/mdeberta-v3-base on the tmnam20/VieGLUE/RTE dataset. It achieves the following results on the evaluation set:
- Loss: 0.6043
- Accuracy: 0.6931
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: 100
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
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/mdeberta-v3-base-rte-100
Base model
microsoft/mdeberta-v3-baseDataset used to train tmnam20/mdeberta-v3-base-rte-100
Collection including tmnam20/mdeberta-v3-base-rte-100
Evaluation results
- Accuracy on tmnam20/VieGLUE/RTEvalidation set self-reported0.693