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:
      - >-
        According to the federal Centers for Disease Control and Prevention (
        news - web sites ) , there were 19 reported cases of measles in the
        United States in 2002.
      - >-
        The Centers for Disease Control and Prevention said there were 19
        reported cases of measles in the United States in 2002.
    example_title: Equivalent
model-index:
  - name: platzi-distilroberta-base-mrpc-glue
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          config: mrpc
          split: validation
          args: mrpc
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8627450980392157
          - name: F1
            type: f1
            value: 0.9

platzi-distilroberta-base-mrpc-glue

This model is a fine-tuned version of bert-base-uncased on the glue and the mrpc datasets. It achieves the following results on the evaluation set:

Loss: 0.4414
Accuracy: 0.8627
F1: 0.9

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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.5624	1.09	500	0.4727	0.7990	0.8591
0.4063	2.18	1000	0.4414	0.8627	0.9
0.2612	3.27	1500	0.5972	0.8529	0.8986

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2