platzi-diltilroberta-base-mrpc-glue-santiago-toledo

This model is a fine-tuned version of distilroberta-base on the datasetX dataset. It achieves the following results on the evaluation set:

• Loss: 0.6731
• Accuracy: 0.8284
• F1: 0.8723

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.4044	1.09	500	0.6731	0.8284	0.8723
0.231	2.18	1000	0.8025	0.8260	0.8748

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cpu
• Datasets 2.14.4
• Tokenizers 0.13.3