metadata
language:
- en
license: mit
base_model: microsoft/mdeberta-v3-base
tags:
- generated_from_trainer
datasets:
- tmnam20/VieGLUE
metrics:
- accuracy
model-index:
- name: mdeberta-v3-base-vsfc-1
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: tmnam20/VieGLUE/VSFC
type: tmnam20/VieGLUE
config: vsfc
split: validation
args: vsfc
metrics:
- name: Accuracy
type: accuracy
value: 0.950726468730259
mdeberta-v3-base-vsfc-1
This model is a fine-tuned version of microsoft/mdeberta-v3-base on the tmnam20/VieGLUE/VSFC dataset. It achieves the following results on the evaluation set:
- Loss: 0.2229
- Accuracy: 0.9507
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 |
|---|---|---|---|---|
| 0.1695 | 1.4 | 500 | 0.2297 | 0.9425 |
| 0.1095 | 2.79 | 1000 | 0.2185 | 0.9482 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0