distilbert-base-uncased-finetuned-mrpc

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

• Loss: 0.3962
• Accuracy: 0.8382
• F1: 0.8893

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: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	230	0.4131	0.8186	0.875
No log	2.0	460	0.3962	0.8382	0.8893

Framework versions

• Transformers 4.28.0
• Pytorch 2.1.2+cu121
• Datasets 2.15.0
• Tokenizers 0.13.3