README.md

metadata

language:
  - en
license: mit
base_model: microsoft/deberta-v3-base
tags:
  - generated_from_trainer
datasets:
  - swag
metrics:
  - accuracy
model-index:
  - name: llm-deberta-v3-swag
    results:
      - task:
          name: Multiple Choice
          type: multiple-choice
        dataset:
          name: SWAG
          type: swag
          config: regular
          split: validation
          args: regular
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8679895997047424

llm-deberta-v3-swag

This model is a fine-tuned version of microsoft/deberta-v3-base on the SWAG dataset. It achieves the following results on the evaluation set:

• Loss: 0.7839
• Accuracy: 0.8680

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 4.36.0.dev0
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0