README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: roberta-large-finetuned-mnli-batch_size_4_100000_samples
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          config: mnli
          split: train
          args: mnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.3544574630667346

roberta-large-finetuned-mnli-batch_size_4_100000_samples

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

• Loss: 1.0980
• Accuracy: 0.3545

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: 4
• eval_batch_size: 4
• 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
1.1026	1.0	25000	1.0980	0.3545

Framework versions

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