transformers pytorch tensorboard bert text-classification generated_from_trainer dataset:glue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- text-classification
- generated_from_trainer
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:
      type: text-classification
      name: Text Classification
    dataset:
      name: glue
      type: glue
      config: mrpc
      split: validation
      args: mrpc
    metrics:
    - type: accuracy
      value: 0.8627450980392157
      name: Accuracy
    - type: f1
      value: 0.9
      name: F1
---

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# platzi-distilroberta-base-mrpc-glue

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/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
