qqp

This model is a fine-tuned version of albert-base-v2 on the GLUE QQP dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3695
  • Accuracy: 0.9050
  • F1: 0.8723
  • Combined Score: 0.8886

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: 64
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4.0

Training results

Framework versions

  • Transformers 4.9.1
  • Pytorch 1.9.0+cu102
  • Datasets 1.10.2
  • Tokenizers 0.10.3
Downloads last month
9
Hosted inference API
Text Classification
Examples
Examples
This model can be loaded on the Inference API on-demand.