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# mdeberta-v3-base-vnrte-100

This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the tmnam20/VieGLUE/VNRTE dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0063
- Accuracy: 0.9987

## 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

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0031        | 1.28  | 500  | 0.0002          | 1.0      |
| 0.0002        | 2.55  | 1000 | 0.0011          | 0.9997   |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"language": ["en"], "license": "mit", "tags": ["generated_from_trainer"], "datasets": ["tmnam20/VieGLUE"], "metrics": ["accuracy"], "base_model": "microsoft/mdeberta-v3-base", "model-index": [{"name": "mdeberta-v3-base-vnrte-100", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "tmnam20/VieGLUE/VNRTE", "type": "tmnam20/VieGLUE", "config": "vnrte", "split": "validation", "args": "vnrte"}, "metrics": [{"type": "accuracy", "value": 0.9987248963978324, "name": "Accuracy"}]}]}]}
transformers safetensors deberta-v2 text-classification generated_from_trainer en dataset:tmnam20/VieGLUE base_model:microsoft/mdeberta-v3-base license:mit model-index autotrain_compatible endpoints_compatible region:us