roberta-base_mnli_bc

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

• Loss: 0.2125
• Accuracy: 0.9584

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: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3.0
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.2015	1.0	16363	0.1820	0.9470
0.1463	2.0	32726	0.1909	0.9559
0.0768	3.0	49089	0.2117	0.9585

Framework versions

• Transformers 4.13.0
• Pytorch 1.10.1+cu111
• Datasets 1.17.0
• Tokenizers 0.10.3