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metadata
language:
  - en
license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: roberta-base_mnli_bc
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MNLI
          type: glue
          args: mnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9583768461882739

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