roberta-base-mnli

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

• eval_loss: 0.7539
• eval_accuracy: 0.8697
• eval_runtime: 25.5655
• eval_samples_per_second: 384.581
• eval_steps_per_second: 48.073
• step: 0

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
• lr_scheduler_warmup_ratio: 0.06
• num_epochs: 10.0

Framework versions

• Transformers 4.20.0.dev0
• Pytorch 1.11.0+cu113
• Datasets 2.1.0
• Tokenizers 0.12.1