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
bert-base-multilingual-cased-wnli-10
This model is a fine-tuned version of bert-base-multilingual-cased on the tmnam20/VieGLUE/WNLI dataset. It achieves the following results on the evaluation set:
- Loss: 0.6919
- Accuracy: 0.5634
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: 10
- 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 4.35.2
- Pytorch 2.2.0.dev20231203+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Downloads last month
- 10
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/bert-base-multilingual-cased-wnli-10
Base model
google-bert/bert-base-multilingual-casedDataset used to train tmnam20/bert-base-multilingual-cased-wnli-10
Collection including tmnam20/bert-base-multilingual-cased-wnli-10
Evaluation results
- Accuracy on tmnam20/VieGLUE/WNLIvalidation set self-reported0.563