wnli

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

• Loss: 0.6898
• Accuracy: 0.5634

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: 4.0

Training results

Framework versions

• Transformers 4.9.1
• Pytorch 1.9.0+cu102
• Datasets 1.10.2
• Tokenizers 0.10.3