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
base_model: distilroberta-base
model-index:
  - name: platzi-distilroberta-base-mrpc-glue-jose-alcocer
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: glue
          type: glue
          config: mrpc
          split: validation
          args: mrpc
        metrics:
          - type: accuracy
            value: 0.8259803921568627
            name: Accuracy
          - type: f1
            value: 0.875219683655536
            name: F1

platzi-distilroberta-base-mrpc-glue-jose-alcocer

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

Loss: 0.5314
Accuracy: 0.8260
F1: 0.8752

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
0.5317	1.09	500	0.5314	0.8260	0.8752
0.3602	2.18	1000	0.6965	0.8358	0.8855
0.2204	3.27	1500	0.7159	0.8529	0.8962

Framework versions

Transformers 4.28.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3