README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
base_model: roberta-base
model-index:
  - name: roberta-base-finetuned-mnli
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: glue
          type: glue
          config: mnli
          split: train
          args: mnli
        metrics:
          - type: accuracy
            value: 0.865206316861946
            name: Accuracy

roberta-base-finetuned-mnli

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

• Loss: 0.3914
• Accuracy: 0.8652

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: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3982	1.0	49088	0.3914	0.8652

Framework versions

• Transformers 4.25.1
• Pytorch 1.12.1+cu113
• Datasets 2.7.1
• Tokenizers 0.13.2