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testing

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

• Loss: 0.6644
• Accuracy: 0.6814
• F1: 0.8105
• Combined Score: 0.7459

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: 1
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• training_steps: 10

Training results

Framework versions

• Transformers 4.11.0.dev0
• Pytorch 1.9.0+cu111
• Datasets 1.11.0
• Tokenizers 0.10.3