README.md

metadata

language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
base_model: bert-large-uncased-whole-word-masking
model-index:
  - name: mrpc
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: GLUE MRPC
          type: glue
          args: mrpc
        metrics:
          - type: accuracy
            value: 0.8823529411764706
            name: Accuracy
          - type: f1
            value: 0.9180887372013652
            name: F1

mrpc

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

• Loss: 0.3680
• Accuracy: 0.8824
• F1: 0.9181
• Combined Score: 0.9002

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: 3e-05
• train_batch_size: 32
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
• lr_scheduler_type: linear
• num_epochs: 3.0

Training results

Framework versions

• Transformers 4.18.0
• Pytorch 1.10.0a0+gitfe03f8c
• Datasets 2.1.0
• Tokenizers 0.12.1