metadata

language:
  - en
license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: deberta-v3-base-mrpc
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MRPC
          type: glue
          config: mrpc
          split: validation
          args: mrpc
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8946078431372549
          - name: F1
            type: f1
            value: 0.9244288224956063

deberta-v3-base-mrpc

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

Loss: 0.5681
Accuracy: 0.8946
F1: 0.9244
Combined Score: 0.9095

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: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5.0

Framework versions

Transformers 4.28.1
Pytorch 1.12.1+cu113
Datasets 2.11.0
Tokenizers 0.13.3