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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: platzidisrtobertabasemrpcglueml
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          config: mrpc
          split: validation
          args: mrpc
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8382352941176471
          - name: F1
            type: f1
            value: 0.8804347826086956

platzidisrtobertabasemrpcglueml

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

  • Loss: 0.6256
  • Accuracy: 0.8382
  • F1: 0.8804

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

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.516 1.09 500 0.4554 0.8260 0.8725
0.358 2.18 1000 0.6256 0.8382 0.8804

Framework versions

  • Transformers 4.30.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3