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roberta-base-mnli-negnli

Text Classification

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roberta2-base-mnli-negnli

This model is a fine-tuned version of sileod/roberta-base-mnli on the GLUE MNLI dataset and the MNLI subset in NegNLI. It achieves the following results on the evaluation set:

Loss: 0.8397
Accuracy: 0.8400

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: 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: 5.0

Training results

Framework versions

Transformers 4.21.0.dev0
Pytorch 1.8.0
Datasets 1.18.3
Tokenizers 0.12.1

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Evaluation results

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