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metadata
license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: deberta-base-finetuned-sst2
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          config: sst2
          split: train
          args: sst2
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9495412844036697

deberta-base-finetuned-sst2

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

  • Loss: 0.2411
  • Accuracy: 0.9495

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.1946 1.0 4210 0.2586 0.9278
0.1434 2.0 8420 0.2296 0.9472
0.1025 3.0 12630 0.2411 0.9495

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.8.0
  • Tokenizers 0.13.2