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# llm-mdeberta-v3-swag

This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the SWAG dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8202
- Accuracy: 0.7778

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0

{"language": ["en"], "license": "mit", "tags": ["generated_from_trainer"], "datasets": ["swag"], "metrics": ["accuracy"], "base_model": "microsoft/mdeberta-v3-base", "model-index": [{"name": "llm-mdeberta-v3-swag", "results": [{"task": {"type": "multiple-choice", "name": "Multiple Choice"}, "dataset": {"name": "SWAG", "type": "swag", "config": "regular", "split": "validation", "args": "regular"}, "metrics": [{"type": "accuracy", "value": 0.777816653251648, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors deberta-v2 multiple-choice generated_from_trainer en dataset:swag base_model:microsoft/mdeberta-v3-base license:mit model-index endpoints_compatible region:us