README.md

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