README.md

metadata

language:
  - en
license: apache-2.0
base_model: bert-large-cased
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: bert-large-qqp
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE QQP
          type: glue
          args: qqp
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9132574820677715
          - name: F1
            type: f1
            value: 0.8825794354973717

bert-large-qqp

This model is a fine-tuned version of bert-large-cased on the GLUE QQP dataset. It achieves the following results on the evaluation set:

• Loss: 0.4196
• Accuracy: 0.9133
• F1: 0.8826
• Combined Score: 0.8979

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
• num_epochs: 5.0

Training results

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu117
• Datasets 2.18.0
• Tokenizers 0.13.3