metadata

language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: bert-base-uncased-mrpc
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MRPC
          type: glue
          args: mrpc
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8602941176470589
          - name: F1
            type: f1
            value: 0.9042016806722689
      - task:
          type: natural-language-inference
          name: Natural Language Inference
        dataset:
          name: glue
          type: glue
          config: mrpc
          split: validation
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8602941176470589
            verified: true
          - name: Precision
            type: precision
            value: 0.8512658227848101
            verified: true
          - name: Recall
            type: recall
            value: 0.96415770609319
            verified: true
          - name: AUC
            type: auc
            value: 0.8985718651885194
            verified: true
          - name: F1
            type: f1
            value: 0.9042016806722689
            verified: true
          - name: loss
            type: loss
            value: 0.6978028416633606
            verified: true

bert-base-uncased-mrpc

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

Loss: 0.6978
Accuracy: 0.8603
F1: 0.9042
Combined Score: 0.8822

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
num_epochs: 5.0

Framework versions

Transformers 4.17.0
Pytorch 1.10.0+cu102
Datasets 1.14.0
Tokenizers 0.11.6