platzi-distilroberta-base-mrpc-glue

This model is a fine-tuned version of bert-base-uncased on the glue and the mrpc datasets. It achieves the following results on the evaluation set:

• Loss: 0.4414
• Accuracy: 0.8627
• F1: 0.9

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: 8
• 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

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.5624	1.09	500	0.4727	0.7990	0.8591
0.4063	2.18	1000	0.4414	0.8627	0.9
0.2612	3.27	1500	0.5972	0.8529	0.8986

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.1+cu116
• Datasets 2.9.0
• Tokenizers 0.13.2