README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: deberta-v3-base-finetuned-rte
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          config: rte
          split: train
          args: rte
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8194945848375451

deberta-v3-base-finetuned-rte

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

• Loss: 0.8234
• Accuracy: 0.8195

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	156	0.5610	0.7545
No log	2.0	312	0.6270	0.7617
No log	3.0	468	0.6565	0.7906
0.3919	4.0	624	0.8234	0.8195
0.3919	5.0	780	0.9628	0.7978

Framework versions

• Transformers 4.25.1
• Pytorch 1.13.0+cu116
• Datasets 2.7.1
• Tokenizers 0.13.2