NLP_sequences_example

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

• Loss: 0.6412
• Accuracy: 0.6649
• F1: 0.7987

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: 0.0002
• 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
0.6576	1.09	500	0.6249	0.6838	0.8122
0.6424	2.18	1000	0.6427	0.6838	0.8122

Framework versions

• Transformers 4.29.0
• Pytorch 2.1.0+cu121
• Datasets 2.15.0
• Tokenizers 0.13.3