README.md

metadata

language:
  - en
license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
base_model: roberta-base
model-index:
  - name: roberta-base-mrpc
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: GLUE MRPC
          type: glue
          args: mrpc
        metrics:
          - type: accuracy
            value: 0.9019607843137255
            name: Accuracy
          - type: f1
            value: 0.9295774647887324
            name: F1
      - task:
          type: natural-language-inference
          name: Natural Language Inference
        dataset:
          name: glue
          type: glue
          config: mrpc
          split: validation
        metrics:
          - type: accuracy
            value: 0.9019607843137255
            name: Accuracy
            verified: true
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          - type: precision
            value: 0.9134948096885813
            name: Precision
            verified: true
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          - type: recall
            value: 0.946236559139785
            name: Recall
            verified: true
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          - type: auc
            value: 0.9536411880747964
            name: AUC
            verified: true
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          - type: f1
            value: 0.9295774647887324
            name: F1
            verified: true
            verifyToken: >-
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          - type: loss
            value: 0.48942330479621887
            name: loss
            verified: true
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mrpc

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

• Loss: 0.4898
• Accuracy: 0.9020
• F1: 0.9296
• Combined Score: 0.9158

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_ratio: 0.06
• num_epochs: 5.0

Training results

Framework versions

• Transformers 4.20.0.dev0
• Pytorch 1.11.0+cu113
• Datasets 2.1.0
• Tokenizers 0.12.1