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# mdeberta-v3-base-mnli-10

This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the tmnam20/VieGLUE/MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4642
- Accuracy: 0.8431

## 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

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.5294        | 0.41  | 5000  | 0.4986          | 0.8037   |
| 0.4856        | 0.81  | 10000 | 0.4593          | 0.8250   |
| 0.3976        | 1.22  | 15000 | 0.4776          | 0.8271   |
| 0.4154        | 1.63  | 20000 | 0.4680          | 0.8222   |
| 0.2933        | 2.04  | 25000 | 0.5138          | 0.8304   |
| 0.3186        | 2.44  | 30000 | 0.4813          | 0.8320   |
| 0.3196        | 2.85  | 35000 | 0.4795          | 0.8331   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.2.0.dev20231203+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-mnli-10", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "tmnam20/VieGLUE/MNLI", "type": "tmnam20/VieGLUE", "config": "mnli", "split": "validation_matched", "args": "mnli"}, "metrics": [{"type": "accuracy", "value": 0.8430634662327096, "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