README.md

metadata

license: apache-2.0
tags:
  - text-classification
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
widget:
  - text:
      - >-
        Yucaipa owned Dominick 's before selling the chain to Safeway in 1998
        for $ 2.5 billion.
      - >-
        Yucaipa bought Dominick's in 1995 for $ 693 million and sold it to
        Safeway for $ 1.8 billion in 1998.
    example_title: Not Equivalent
  - text:
      - >-
        Revenue in the first quarter of the year dropped 15 percent from the
        same period a year earlier.
      - >-
        With the scandal hanging over Stewart's company revenue the first
        quarter of the year dropped 15 percent from the same period a year
        earlier.
    example_title: Equivalent
model-index:
  - name: platzi-distilroberta-base-mrpc-glue-santiago
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: datasetX
          type: glue
          config: mrpc
          split: validation
          args: mrpc
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8137254901960784
          - name: F1
            type: f1
            value: 0.8633093525179856

platzi-distilroberta-base-mrpc-glue-santiago

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

• Loss: 0.7037
• Accuracy: 0.8137
• F1: 0.8633

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: 5e-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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.5083	1.09	500	0.7037	0.8137	0.8633
0.3404	2.18	1000	0.7367	0.8235	0.8719

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.1+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3